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Nowadays, meteorological data plays a crucial role in various fields such as remote sensing, weather forecasting, climate change, and agriculture. The regional and local studies call for high spatial resolution gridded meteorological data to identify refined details, which however is generally limited due to the models, platforms, sensors, etc. Downscaling has been a significant and practical way to improve spatial resolution. In recent years, with superior feature extraction and expression abilities, deep learning (DL) has outperformed traditional methods in various areas, and exhibits huge potential to establish a complicated mapping between large-scale and local-scale meteorological data. Therefore, this paper provides a systematic review of DL in statistical downscaling for deriving high spatial resolution gridded meteorological data. This review first presents the background, including a taxonomy of downscaling methods, the role of DL in statistical downscaling, and the analogy between downscaling and image super-resolution. It shows evidence of how downscaling can benefit from DL, particularly super-resolution networks. Subsequently, this review focuses on the recent development of the DL-based statistical downscaling of gridded meteorological data, especially the deep architectures, including convolutional neural networks to capture the spatial dependencies of meteorological variables, recurrent neural networks to reveal the temporal states from time series, and generative adversarial networks to facilitate the reconstruction of high-frequency details, as well as the major structure residual learning and attention mechanism. In addition, this review demonstrates the specific issues towards downscaling, including scaling factors, spatial–temporal and variable correlations, and paired datasets construction, and then gives a comprehensive summary of the status of datasets, toolsets and metrics. The future challenges from the perspective of unsupervised models, transformer architecture, data fusion, physical-informed learning, generalization capacity, and uncertainty quantification for downscaling are finally discussed. • Deep learning maps large-scale predictors to local-scale predictand for downscaling. • The major deep structures for downscaling networks and enhancement are reviewed. • The specific issues on downscaling factor, correlations, and datasets are addressed. • Unsupervised, physical-informed learning, uncertainty etc. pose great challenges. [ABSTRACT FROM AUTHOR]

This paper presents a hybrid prediction and search approach (HPS) for building visualization systems of big data. The basic idea is training a regression model to predict a coarse range on the dataset and then searching target records that satisfy the query conditions within the range. The prediction reduces the storage cost without preprocessing a data structure storing aggregate values of queriable attribute range combinations. Meanwhile, the search eliminates the prediction bias inevitable for machine learning models. Experiments on multiple open datasets demonstrate HPS's comparable query speed to existing techniques and the potential of continuous performance improvement by investing more hardware resources. In addition, the feature of returning original records instead of aggregate values brings better use flexibility, enabling to construct visualization systems with display/query functions that are unavailable for existing techniques. [ABSTRACT FROM AUTHOR]

In this paper, in order to solve the calculation problem of creep damage of steam turbine rotor, a real-time calculation method based on finite element model is proposed. The temperature field and stress field of the turbine rotor are calculated using finite element analysis software. The temperature data and stress data of the crucial positions are extracted. The data of temperature, pressure, rotational speed, and stress relating to creep damage calculation are normalized. A real-time creep stress calculation model is established by multiple regression method. After that, the relation between stress and damage function is analyzed and fitted, and creep damage is calculated in real-time. A creep damage real-time calculation system is constructed for practical turbine engineering. Finally, a numerical simulation experiment is designed and carried out to verify the effectiveness of this novel approach. Contributions of present work are that a practical solution for real-time creep damage prediction of steam turbine is supplied. It relates the real-time creep damage prediction to process parameters of steam turbine, and it bridges the gap between the theoretical research works and practical engineering. [ABSTRACT FROM AUTHOR]

As a classical sparse reconstruction algorithm, iterative soft thresholding (IST) is often used in SAR sparse imaging applications. However, for moving targets, the radar echo contains an unknown phase error, so it is difficult to directly apply the IST algorithm to reconstruct the SAR moving target image. In this article, a parametric IST (P-IST) algorithm is proposed for refocusing of moving targets in synthetic aperture radar (SAR) images. In this algorithm, the echo phase error is modeled as a function of the phase compensation factor, and in the iteration process, a phase compensation factor optimization selection step based on residual energy minimization is added. Compared with the existing algorithms, the proposed P-IST algorithm can obtain the global optimal solution and has better efficiency and robustness. Both simulated data and measured data are used to validate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In the modern manufacturing industry, mechanical equipment plays a crucial role. Equipment working in harsh environments for a long time is more likely to break down, which can lead to economic losses or potential safety hazards. It is of significant importance to develop prognostic and health management technologies that correspond with the machines. Due to the non-stationarity of vibration signals in mechanical equipment, identifying fault features becomes challenging. Transforming the signals into images has been identified as a promising approach for fault diagnosis. This review provides an overview of recent data conversion imaging methods in the field of mechanical equipment. Additionally, it organizes the methods of feature enhancement and extraction based on these images. In the field of fault diagnosis for mechanical equipment, this review presents an overview of the framework used in intelligent fault diagnosis based on image-based techniques. With the development of artificial intelligence, image classification methods have more advantages compared to raw signal analysis. The purpose of this review is to provide readers with references on using image diagnosis methods for mechanical equipment. The significance of this review research is to provide readers with improved methods for image processing and image classification in the field of mechanical equipment. In addition, future development trends in this field were predicted, providing valuable insights and ideas for mechanical equipment fault diagnosis. • In mechanical equipment, the methods of image feature enhancement are summarized and reviewed. • The intelligent mechanical fault diagnosis using images is feasible, and the advantages of different image methods in fault diagnosis. • The organization of image feature extraction methods and their improvement methods. • The conversion of mechanical equipment signals into images for diagnosis lays the foundation for intelligent diagnosis. [ABSTRACT FROM AUTHOR]

Microanalyses of the reverse-bias leakage current increase in the laser lift off (LLO) GaN-based light emitting diodes were performed. It was found that the amount of dislocations did not obviously change after LLO process in our experiments. The conductive-atomic force microscopy images and transmission electron microscope (TEM) images results revealed that almost all screw dislocations became to be related with leakage current and the current intensity increased over 100 times after the LLO process; however, only nanopipes corresponded to leakage current in the sample without the laser irradiation. Scanning TEM images indicated microstructure changes induced by LLO process. Amount of point defects around dislocations might be responsible for the increase in leakage current by providing more levels for tunneling. [ABSTRACT FROM AUTHOR]

In order to optimize N application and understand how the different combinations of water and N management affect grain filling characteristics and yield, we designed three irrigation regimes (W1 submerged irrigation, W2 alternate irrigation, W3 dry cultivation), and different N application strategies at 180 kg ha−1 in 2010 and 2011. The relationship between grain filling characteristics and grain yield formation were respectively investigated. The results revealed that there were obvious interacting effects of irrigation regime and N application strategies on grain yield and grain-filling characteristics as well. Compared with W1 and W3 treatments, under W2, the N-fertilizer should account for 30% base, 30% tillering, and 40% panicle fertilizer with the last being applied equally at 4th and 2nd leaves emerged from the top. Correlation analysis revealed that grain filling rate during middle grain-filling stage was the largest and contribute more than 50% to grain-filling. Grain yield was significantly related to grain filling rate (Gmax or Gmean), final weight of a kernel (A), and mean grain filling rate (MGR) of the early, mid and late stages during grain filling in inferior spikelets, which is the important reason for water and N coupling effect further to increase yield and fertilizer use efficiency. [ABSTRACT FROM AUTHOR]

Building materials machinery equipment play an important role in the production of cement, brick and tile, glass and other building materials, which are high energy consumption industries. Due to advanced sensors, continuous improvement of signal acquisition technologies and increasing data storage space, a large amount of data can be used by scholars, which makes data-based fault diagnosis gradually studied by more and more scholars. With increasing amount of data, new challenges are as follows: there is very little data that can really be used; the research on compound fault diagnosis and weak fault diagnosis is still not mature; the diagnosis accuracy of variable speed components is low. These problems restrict the further development of fault diagnosis. In this paper, the characteristics of fault diagnosis of building materials equipment are first expounded, the principles and characteristics of main building materials equipment, signal classification, sensor selection and error correction are briefly introduced, then the research status are discussed, the existing difficulties and challenges are summarized, and the potential development directions and trends in this field are given. • Equipment fault diagnosis in high energy consumption industries in China is reviewed. • Common signal types, measurement points, sensor selection and error correction are reviewed. • Current research of equipment fault diagnosis is summarized. • Difficulties and challenges in mechanical fault diagnosis is analyzed. [ABSTRACT FROM AUTHOR]

In this study, aluminum nitride ( AlN) ceramics were first prepared by aqueous gelcasting. The effect of various parameters such as concentration of N, N-dimethylacrylamide ( DMAA, as monomers), N, N′-methylenbisacrylamide ( MBAM, as cross-linking agent), ammonium persulfate amount ( APS, as initiator), solid content and polymerization temperature on AlN ceramics was discussed for aqueous gelcasting system. Finally, drying methods of aqueous gelcasting AlN green bodies were investigated. Aqueous gelcasting AlN ceramics, sintered at 1850°C for 4 h, had homogeneous grain size and little grain boundary phase, and the relative density, flexural strength and thermal conductivity of aqueous gelcasting AlN ceramics were 99.9%, 333(±10) MPa, 136(±9) W/(m·K), respectively. [ABSTRACT FROM AUTHOR]

In order to clarify yield formation mechanism of mechanical dry direct-sowing rice, the objective of this experiment was to study the effects of different mechanical dry direct-sowing modes on growth and development characteristics and yield of rice. Two different rice cultivars of indica hybrid rice F you 498 (143 days growth duration) and conventional japonica rice Xudao 4 (145 days growth duration) were planted with two mechanical dry direct-sowing modes, including a shallow rotary tillage land and mechanic drilling simultaneously (B1), regulating soil moisture and two rotary tillage before mechanic drilling (B2). Manual broad-cast sowing (B3) was set as control at the same time. We investigated and performed growth analysis during different growth periods, and determined yield formation and physiological characteristics under different direct-sowing treatments. The dry direct-sowing machine in this study was modified by Nanjing Agricultural University and was re-modified by Sichuan Agricultural University. This machine has six drills and sowed depth 2.0 cm, drill spacing 28.0 cm, working area 1.50 m. Motive power of this machine was the Shanghai New Holland tractor (SNH504). This test adopted row spacing 20 m × 1.5 m, each plot covered 30 m2 of seeding amount was 30.0 kg/hm2 of indica hybrid rice F you 498, 37.5 kg/hm2 of conventional japonica rice Xudao 4 respectively. The nitrogen fertilizer amount was 180 kg/hm2, and the amount of potash and phosphate were 90 and 180 kg/hm2, respectively. The N application ratios was applied on 4 splits: 50% basal, 30% tillering fertilizer at the third leaf stage, 10% panicle N-fertilizer at the 4th leaves emerged from the top, 10% ear granular fertilizer at the full heading stage. The phosphate fertilizer was applied as base fertilizer. The potash fertilizer application ratio of basic fertilizer, tillering fertilizer and ear granular fertilizer was 2:1:1. The other management measures were at a uniform with high-yield cultivation. The results showed that the variety difference and direct-sowing modes significantly affected dry matter accumulation and leaf area index (LAI) at the mainly growth periods, net photosynthetic rate (Pn) and protective enzyme activities of flag leaves, root bleeding intensity, culm lodging resistance during the grain filling stage and the grain yield. Under different direct-sowing modes, the various indicators on yield and growth characteristics of F you 498 were significantly higher than those of Xudao 4. Compared with B3 treatment, rice under mechanical direct-seeding modes could optimize the number of rice tillering, improve the percentage of earbearing tiller, maintain an appropriate LAI and increase efficient leaf area ratio at the full-heading stage. Besides mechanical direct-seeding could improve photosynthetic capacity at the grain filling stage and therefore increase the accumulation of photosynthetic products. In addition, Pn and protective enzyme activities in flag leaves, root bleeding intensity, culm lodging resistance during the grain filling stage under mechanical direct-seeding modes were superior, and rice could gain higher seed-setting rate and 1000-grain weight with a number of effective panicles. These outstanding traits should be the important reason for mechanical direct-sowing rice further to increase yield. Under different mechanical direct-sowing modes, compared with B3, B2 treatment was the best model in this study referred as the mechanical direct-sowing treatments, which could further promote the dry matter accumulation, alleviate LAI decay, increase root vigor and the ability of culm lodging resistance during grain filling stage, consequently, promoting the seed-setting rate and 1000-grain weight as well as the grain yield. [ABSTRACT FROM AUTHOR]

Artificial intelligence method does not need artificial operation to extract fault characteristics, and greatly reduces the error of human operation. According to the principle of convolution neural network, a new method of optimal convolution neural network (CNN) model is proposed. Firstly, according to the principle of symmetrized dot pattern (SDP), the vibration signal is transformed into a symmetrical image in polar coordinates, which is also called snowflake image. Then, the SDP images are input into the input layer of the convolutional neural network, and the model can diagnose the fault type automatically. By adjusting the number of convolution layers and the size of convolution kernel, the convolution neural network model is determined according to a new index involving accuracy and time ratio. Finally, the test set is used to validate the robustness of the method under different bearing operating conditions. • Vibration signal is transmitted to SDP image as feature. • Sensitive indicator of optimal CNN is advanced. • Optimal structure of convolutional neural network is determined. • Comparative experiments are carried out to indicate the advantage. [ABSTRACT FROM AUTHOR]

Sea surface wind (SSW) is a crucial parameter for meteorological and oceanographic research, and accurate observation of SSW is valuable for a wide range of applications. However, most existing SSW data products are at a coarse spatial resolution, which is insufficient, especially for regional or local studies. Therefore, in this paper, to derive finer-resolution estimates of SSW, we present a novel statistical downscaling approach for satellite SSW based on generative adversarial networks and dual learning scheme, taking WindSat as a typical example. The dual learning scheme performs a primal task to reconstruct high resolution SSW, and a dual task to estimate the degradation kernels, which form a closed loop and are simultaneously learned, thus introducing an additional constraint to reduce the solution space. The integration of a dual learning scheme as the generator into the generative adversarial network structure further yield better downscaling performance by fine-tuning the generated SSW closer to high-resolution SSW. Besides, a model adaptation strategy was exploited to enhance the capacity for downscaling from low-resolution SSW without high-resolution ground truth. Comprehensive experiments were conducted on both the synthetic paired and unpaired SSW data. In the study areas of the East Coast of North America and the North Indian Ocean, in this work, the downscaling results to 0.25° (high resolution on the synthetic dataset), 0.03125° (8× downscaling), and 0.015625° (16× downscaling) of the proposed approach achieve the highest accuracy in terms of root mean square error and R-Square. The downscaling resolution can be enhanced by increasing the basic blocks in the generator. The highest downscaling reconstruction quality in terms of peak signal-to-noise ratio and structural similarity index was also achieved on the synthetic dataset with high-resolution ground truth. The experimental results demonstrate the effectiveness of the proposed downscaling network and the superior performance compared with the other typical advanced downscaling methods, including bicubic interpolation, DeepSD, dual regression networks, and adversarial DeepSD. [ABSTRACT FROM AUTHOR]

Biodegradable long-chain branched(LCB) poly(butylene succinate-co-butyleneterephthalate) (PBST) copolyesters were prepared via a two-step directesterification and melt polycondensation process, using a small amount(0–2 mol %) of diglycidyl 1,2,3,6-tetrahydrophthalate (DGT)as an in situ branching agent (BA). The chemical structures of LCBPBSTs were characterized and the thermal, mechanical, and rheologicalproperties were investigated. With increasing DGT loading, PBSTs withhigher branching degree, broader molecular weight distribution, andlower melt flow index were synthesized in shorter polycondensationtime. The branching of PBSTs results in a slight decrease in crystallizability,melting, and Vicat softening temperatures, but leads to an obviousdecrease in elongation at break. On the other hand, the existenceof LCB greatly improved the rheological properties of PBSTs. PBSTwith higher branching degree possesses higher storage and loss modulus,higher zero-shear viscosity, longer relaxation time, more obviousshear-thinning, and lower loss angle tangent. The Han plot of therheological data also indicates higher elasticity of LCB PBSTs. [ABSTRACT FROM AUTHOR]

Abstract: The water and nitrogen (N) managements play a vital role in hybrid rice production aimed at high yield, high nitrogen use efficiency (NUE), and water-saving irrigation. In order to optimize N application and understand how the different combinations of water and N management affect yield and the relative physiological parameters, we designed three irrigation regimes, standing irrigation (W1), alternation irrigation (W2), and dry cultivation (W3), combined with different N application managements at 180kgha−1 of total N condition in our study. The relationship between yield or NUE and ammonia assimilation enzyme activities, photosynthetic rate and root activity were respectively investigated. Our data revealed that there were obvious interacting effects of irrigation regime and N application strategies on grain yield and NUE as well. Our correlation analysis revealed that the grain yield or NUE was significantly related to ammonium assimilation enzyme activities, photosynthetic rate, and root activity, respectively, at several rice growth stages. Our correlation analysis also revealed that the grain yield was significantly related to the N uptake and utilization, and that the root activity was significantly related to the ammonium assimilation enzymes and photosynthetic rate. Further more, we found that the ammonium assimilation enzyme activities and the photosynthetic rate in flag leaves, or root activity at heading stage was able to be used as indicators for grain yield, total N accumulation, and NUE as well. These results suggest that the N application strategy should be adjusted according to different irrigation regimes in order to obtain the highest yield and the best NUE. Under standing irrigation, on the basis of 40–60% base-tiller N fertilizer, panicle N-fertilizer should account for 40–60% applied equally at 4th and 2nd leaves emerged or 3rd and 1st leaves emerged from the top. Under alternation irrigation, the N application ratio should be split into 30% base, 30% tillering, and 40% panicle fertilizer with the last being applied equally at 4th and 2nd leaves emerged from the top. Under dry cultivation, however, panicle N-fertilizer should account for 20–40% applied equally at 5th and 3rd leaves emerged from the top. [Copyright &y& Elsevier]

• A novel feature index named improved manhattan distance is proposed. • Vibration signal is transmitted as SDP image. • Testing experiment based on practical data is carried out to verify the effectiveness. The vibration signal of rolling bearing is typical non-stationary signal, it is difficult for traditional time–frequency analysis technology to apply. Therefore, a novel fault diagnosis approach based on improved manhattan distance in Symmetrized Dot Pattern (SDP) image is proposed. In this method, the sample vibration signal data is divided as 10 equal parts on average, and empirical mode decomposition (EMD) is used to decompose the equally-divided signals into several Intrinsic Mode Function (IMF) components. The first five IMF components are adopted to transform into five symmetrical snowflake image in polar coordinates, after denoising corresponding feature matrices are calculated, and the mean feature matrix and the maximal characteristic root may be obtained. In this way the improved manhattan distance between the local matrix of each IMF components and corresponding mean matrix is extracted. Different vibration signal of rolling bearing is classified according to this improved manhattan distance. Finally, an experimental experiment is carried out to verify the feasibility and effectiveness of this novel fault diagnosis approach. [ABSTRACT FROM AUTHOR]

A novel bearing fault diagnosis on basis of empirical mode decomposition (EMD) and improved Chebyshev distance is presented. After normalization, each group of sample data is divided into 10 equal parts on average. EMD is used to decompose the equal part signal into several eigenmode functions, and the first five intrinsic mode function (IMF) components are retained and transformed into symmetrical in polar coordinates by symmetrized dot pattern (SDP) method, each SDP image is processed via binarization and localization, then the local SDP images are averaged to obtained the mean image as benchmark. The maximum eigenvalue of the average matrix after denoising is computed, in this way the improved Chebyshev distance is constructed and bridges the gap between the local matrix of each IMF component and the average matrix. Using the improved Chebyshev distance of IMF1 as feature, this method can effectively diagnose the faults of rolling bearing. Finally, test experiments are carried out to verify the accuracy and robustness of present approach. • A novel feature index named improved Chebyshev distance is advanced. • Vibration signal is decomposed via EMD and transmitted as SDP image. • Testing experiment based on practical data is carried out to demonstrate the effectiveness. [ABSTRACT FROM AUTHOR]

We sought to explore the role of postanthesis carbon and nitrogen (C-N) metabolism of hybrid rice in increasing yield and nitrogen utilization efficiency (NUE). We used the 13C and 15N dual-isotope tracer method and physiological/biochemical analysis and established different irrigation and nitrogen fertilization (W-N) regimes to investigate the relationship of C-N metabolism characteristics, yield, and NUE. The results showed that W-N regimes had significant effects on postanthesis absorption and translocation of N and photosynthate, yield and NUE. Aerobic irrigation combined with the N fertilization regime 30% base, 30% tillering, 40% booting was the best W-N coupling regime for rice yield and NUE increase. The regime enhanced flag leaf photosynthesis rate and the activities of ribulose 1,5-diphosphate carboxylase/oxygenase (RuBPCase), glutamine synthetase (GS), and other key enzymes of C-N metabolism, and improved the total accumulations of photoassimilates (0.97–21.57 mg 13C plant−1) and N (1.55–23.36 mg 15N plant−1), respectively. Correlation analysis showed that, under the W-N interaction, C-N metabolism enzymes promoted the positive synergistic effect between 13C and 15N accumulation in panicles (r = 0.825). In addition, the change in C/N ratio can be used as an indicator of the simultaneous improvement in yield and NUE in hybrid rice. [ABSTRACT FROM AUTHOR]

Electroconductive hydrogels offer a promising avenue for enhancing the repair efficacy of spinal cord injuries (SCI) by restoring disrupted electrical signals along the spinal cord's conduction pathway. Nonetheless, the application of hydrogels composed of diverse electroconductive materials has demonstrated limited capacity to mitigate the post-SCI inflammatory response. Recent research has indicated that the transplantation of M2 microglia effectively fosters SCI recovery by attenuating the excessive inflammatory response. Exosomes (Exos), small vesicles discharged by cells carrying similar biological functions to their originating cells, present a compelling alternative to cellular transplantation. This investigation endeavors to exploit M2 microglia-derived exosomes (M2-Exos) successfully isolated and reversibly bonded to electroconductive hydrogels through hydrogen bonding for synergistic promotion of SCI repair to synergistically enhance SCI repair. In vitro experiments substantiated the significant capacity of M2-Exos-laden electroconductive hydrogels to stimulate the growth of neural stem cells and axons in the dorsal root ganglion and modulate microglial M2 polarization. Furthermore, M2-Exos demonstrated a remarkable ability to mitigate the initial inflammatory reaction within the injury site. When combined with the electroconductive hydrogel, M2-Exos worked synergistically to expedite neuronal and axonal regeneration, substantially enhancing the functional recovery of rats afflicted with SCI. These findings underscore the potential of M2-Exos as a valuable reparative factor, amplifying the efficacy of electroconductive hydrogels in their capacity to foster SCI rehabilitation. [ABSTRACT FROM AUTHOR]

BACKGROUND: Chalkiness in rice reduces its market value and affects consumer acceptance. Research on the mechanism of chalkiness formation has focused primarily on the activity of key enzymes of carbon metabolism and starch accumulation. The relationship between the formation of chalkiness induced by N fertilizer and rice starch's multi‐level structure and thermal properties still needs to be fully elucidated. RESULTS: In this study, the rates of chalky grains and degree of chalkiness decreased with the increase in N fertilizer dosage. This was attributed to an increased proportion of short chains, ordered structure carbon chains, small starch granules, and branched starches, and a higher degree of crystallinity and ΔHg in protein, and a decreased proportion of amylose, large starch granules, and weighted average diameter of starch granule surface area and volume. Application of N fertilizer promoted an increased proportion of short‐branched chain amylopectin to develop a more ordered carbohydrate structure and crystalline lamella. These effects enhanced the normal development and compactness of starch granules in grains, and improved their arrangement morphology, thereby reducing the chalkiness in rice. CONCLUSION: These changes in starch multi‐level structure and protein improve the physicochemical characteristics of starch and enhance the fullness, crystallinity and compactness of starch granules, while synergistically increasing the regularity and homogeneity of starch granules and thus optimizing the stacking pattern of starch granules, leading to a reduction in rice chalkiness under nitrogen fertilization and thus improving the appearance of rice. © 2023 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Rice lacks sufficient amounts of zinc despite its vitality for human health. Leaf senescence enables redistribution of nutrients to other organs, yet Zn retransfer during deficiency is often overlooked. In this hydroponic experiment, we studied the effect of Zn deficiency on rice seedlings, focusing on the fourth leaf under control and deficient conditions. Growth phenotype analysis showed that the growth of rice nodal roots was inhibited in Zn deficiency, and the fourth leaf exhibited accelerated senescence and increased Zn ion transfer. Analyzing differentially expressed genes showed that Zn deficiency regulates more ZIP family genes involved in Zn ion retransfer. OsZIP3 upregulation under Zn-deficient conditions may not be induced by Zn deficiency, whereas OsZIP4 is only induced during Zn deficiency. Gene ontology enrichment analysis showed that Zn-deficient leaves mobilized more biological pathways (BPs) during aging, and the enrichment function differed from that of normal aging leaves. The most apparent "zinc ion transport" BP was stronger than that of normal senescence, possibly due to Zn-deficient leaves mobilizing large amounts of BP related to lipid metabolism during senescence. These results provide a basis for further functional analyses of genes and the study of trace element transfer during rice leaf senescence. [ABSTRACT FROM AUTHOR]

As the human population grows rapidly, food shortages will become an even greater problem; therefore, increasing crop yield has become a focus of rice breeding programs. The maize gene, ZmDUF1645, encoding a putative member of the DUF1645 protein family with an unknown function, was transformed into rice. Phenotypic analysis showed that enhanced ZmDUF1645 expression significantly altered various traits in transgenic rice plants, including increased grain length, width, weight, and number per panicle, resulting in a significant increase in yield, but a decrease in rice tolerance to drought stress. qRT-PCR results showed that the expression of the related genes regulating meristem activity, such as MPKA, CDKA, a novel crop grain filling gene (GIF1), and GS3, was significantly changed in the ZmDUF1645-overexpression lines. Subcellular colocalization showed that ZmDUF1645 was primarily localized on cell membrane systems. Based on these findings, we speculate that ZmDUF1645, like the OsSGL gene in the same protein family, may regulate grain size and affect yield through the cytokinin signaling pathway. This research provides further knowledge and understanding of the unknown functions of the DUF1645 protein family and may serve as a reference for biological breeding engineering to increase maize crop yield. [ABSTRACT FROM AUTHOR]

Summary: More than half of the world's food is provided by cereals, as humans obtain >60% of daily calories from grains. Producing more carbohydrates is always the final target of crop cultivation. The carbohydrate partitioning pathway directly affects grain yield, but the molecular mechanisms and biological functions are poorly understood, including rice (Oryza sativa L.), one of the most important food sources. Here, we reported a prolonged grain filling duration mutant 1 (gfd1), exhibiting a long grain‐filling duration, less grain number per panicle and bigger grain size without changing grain weight. Map‐based cloning and molecular biological analyses revealed that GFD1 encoded a MATE transporter and expressed high in vascular tissues of the stem, spikelet hulls and rachilla, but low in the leaf, controlling carbohydrate partitioning in the stem and grain but not in the leaf. GFD1 protein was partially localized on the plasma membrane and in the Golgi apparatus, and was finally verified to interact with two sugar transporters, OsSWEET4 and OsSUT2. Genetic analyses showed that GFD1 might control grain‐filling duration through OsSWEET4, adjust grain size with OsSUT2 and synergistically modulate grain number per panicle with both OsSUT2 and OsSWEET4. Together, our work proved that the three transporters, which are all initially classified in the major facilitator superfamily family, could control starch storage in both the primary sink (grain) and temporary sink (stem), and affect carbohydrate partitioning in the whole plant through physical interaction, giving a new vision of sugar transporter interactome and providing a tool for rice yield improvement. [ABSTRACT FROM AUTHOR]

Rice yields have stabilized in the Chengdu Plain, and the implementation of integrated paddy field farming has shown potential for enhancing resource utilization. However, further investigation is required to clarify its impact on production sustainability. Accordingly, this study compared grain yields, energy use, greenhouse gas emissions, and economic benefits of single cropping rice (SCR), rice-duck symbiosis (RDS), and rice-fish symbiosis (RFS) over a three-year period (2018–2020). The grain yields were 16.24%–23.96 % higher in SCR than in RDS and RFS, but nitrogen fertilizer use was reduced by 31.93%–32.15 % in RDS and RFS, and the partial factor productivity of nitrogen was increased by 21.96–23.82 %. RDS and RFS required 1.87–2.00 times more energy than SCR and were only 55.36%–57.80 % as efficient as SCR. They also had higher CO 2 (36.10%–42.20 %) and CH 4 (8.01%–28.88 %) emissions but lower N 2 O (0.02%–21.18 %) emissions than SCR. Economically, RDS and RFS produced 1.30–1.48 times higher net benefits with 1.44–1.47 times higher costs than SCR. The benefit-cost ratio of RFS was comparable to SCR and 11.38%–11.87 % higher than RDS. In summary, RDS and RFS consume more energy (feed accounts for more than half) but provide higher yields and better-quality proteins, which are crucial to improving farmer motivation and ensuring protein availability. [Display omitted] • A 3-year field experiment was conducted to assess integrated paddy field farming. • Yields, energy use, greenhouse gas emissions, and economic benefits are assessed. • Rice-fish symbiosis is a low-pollution, high-yield farming mode. [ABSTRACT FROM AUTHOR]

• This work provides a new model framework for predicting grain yield. • Combining spectral data and RGB images to develop the fusion models of grain yield. • Multi-source remotely sensed data can improve the estimation accuracy of rice LCC. • Multi-source remotely sensed data has the potential for grain yield prediction. Predicting rice grain yield using multi-source remotely sensed data is crucial for improving prediction accuracy, optimizing nitrogen management, and advancing precision agricultural development. However, the feasibility and reliability of using multi-source remotely sensed data to predict the grain yield remain unclear. Therefore, this study aimed to explore the possibility of providing rice leaf chlorophyll content (LCC) estimations and predictions of the grain yield using multi-source remotely sensed data. Two rice field experiments were conducted with various rice cultivars and nitrogen rates, and a field spectrometer and an unmanned aerial vehicle (UAV) equipped with a digital camera were employed to acquire the spectral reflectance and red–green–blue (RGB) images at the tillering, jointing, and full-heading stages. Destructive sampling was then conducted to measure the LCC and grain yield. The LCC was used as a bridge to develop remotely sensed prediction models for the grain yield. First, the linear relationship between grain yield and the LCC was determined at the tillering, jointing, and full-heading stages. A multiple linear regression (MLR) model was then developed to predict grain yield using multi-temporal LCCs at three growth stages. Second, multiple stepwise regression, support vector regression, and back propagation neural network were used to evaluate the estimation performance of spectral reflectance, RGB image data, and their combination for LCC. Third, the most accurate LCC estimation model was selected and coupled with the linear and MLR models of grain yield. The results showed that grain yield was significantly and positively related to the LCC at the tillering, jointing, and full-heading stages, and that the MLR model of grain yield achieved the best estimation accuracy using multi-temporal LCCs. The fusion models established by combining spectral reflectance and RGB image data improved LCC estimation accuracies. Using multi-growth stages, the most accurate predictions of grain yield were obtained from LCC estimation models (R 2 = 0.698, RMSE = 0.742 t ha−1, rRMSE = 9.004 %) compared to those using single growth stages. Our study concluded that multi-source remotely sensed data fused from ground-based spectral reference and UAV-based RGB images can better predict and explain the grain yield for both single and multi-growth stages. This study provides a novel method of estimating the crop chlorophyll content and grain yield. [ABSTRACT FROM AUTHOR]

Background: As a heterogeneous hereditary connective tissue disorder, osteogenesis imperfecta (OI) is clinically characterized by increased fracture susceptibility. Analysis of genetic pathogenic variants in patients with OI provides a basis for genetic counseling and prenatal diagnosis.Methods: In this study, 14 diagnosed OI patients from sporadic Chinese families were enrolled to be screened for potential mutations from these patients by next-generation sequencing technology.Results: 34 different variants were identified. 18 variants were from 4 OI-related genes including COL1A1, COL1A2, P3H1, and WNT1, and 10 variants are novel. Most OI patients (11 out of 14, 78%) harbor variants in type I collagen genes.Conclusions: Our results support previously established estimates of the distribution and prevalence of OI mutations and highlight both phenotype and genetic heterogeneity among and within families. We report several novel variants of OI, which expands the clinical spectrum of OI. In summary, our data provides disease-causing genes information for genetic counseling towards OI patients and families and also provides a reference for clinicians in the diagnosis of OI, also in prenatal diagnosis of this disease. [ABSTRACT FROM AUTHOR]

Electroconductive hydrogels are very attractive candidates for accelerated spinal cord injury (SCI) repair because they match the electrical and mechanical properties of neural tissue. However, electroconductive hydrogel implantation can potentially aggravate inflammation, and hinder its repair efficacy. Bone marrow stem cell‐derived exosomes (BMSC‐exosomes) have shown immunomodulatory and tissue regeneration effects, therefore, neural tissue‐like electroconductive hydrogels loaded with BMSC‐exosomes are developed for the synergistic treatment of SCI. These exosomes‐loaded electroconductive hydrogels modulate microglial M2 polarization via the NF‐κB pathway, and synergistically enhance neuronal and oligodendrocyte differentiation of neural stem cells (NSCs) while inhibiting astrocyte differentiation, and also increase axon outgrowth via the PTEN/PI3K/AKT/mTOR pathway. Furthermore, exosomes combined electroconductive hydrogels significantly decrease the number of CD68‐positive microglia, enhance local NSCs recruitment, and promote neuronal and axonal regeneration, resulting in significant functional recovery at the early stage in an SCI mouse model. Hence, the findings of this study demonstrate that the combination of electroconductive hydrogels and BMSC‐exosomes is a promising therapeutic strategy for SCI repair. [ABSTRACT FROM AUTHOR]

To promote the reduction and efficiency of chemical fertilizers in rice production, two hybrid rice varieties with different amylose contents (16.43% and 27.58%) were selected to study the yield and quality performance of different quality rice varieties under reduced nitrogen/phosphorus conditions. Thus, the specific mechanism of the long‐term nitrogen/phosphorus reduction effect on the quality of low‐ and high‐amylose content (16.43% and 27.58%) rice was investigated by comparative analyses of the rapid visco analyzer and X‐ray diffraction patterns, amylose contents, and starch structures of the samples. The results revealed that the effect of nitrogen fertilizer on the quality and yield of the hybrid rice was greater than that of phosphorus fertilizer. Indeed, reducing the former increased the Wx gene expression and amylose content of the rice varieties. Moreover, it reduced the starch crystallinity of Yixiangyou 1108 (2.16%), increasing the space between the starch grains and thus, chalkiness. Reducing nitrogen/phosphorus application did not significantly affect the yield and quality of the high‐amylose rice but affected that of the high‐quality rice with lower amylose contents. Thus, for high‐amylose rice created for processing, appropriate chemical fertilizer reduction will not affect their yield and processing demand. Practical applications: Fertilization with different nitrogen and phosphorus fertilizers will seriously affect rice quality. The rice varieties with low amylose content (AC) could produce high taste quality rice by increasing nitrogen fertilizer and decreasing phosphorus fertilizer. The rice varieties with relatively high ACs should reduce the application of nitrogen/phosphorus fertilizer to appropriately increase AC, which can be used to produce healthy food with high resistant starch. [ABSTRACT FROM AUTHOR]

Abstract: AuSn bonding and laser lift-off (LLO) were employed to fabricate GaN-based vertical structure light emitting diodes (VSLEDs) on Si substrates. The phase distribution of ζ and δ phases in the eutectic AuSn layers was analyzed by electron back scattering diffraction (EBSD) measurements. It was found that the phase distribution changed regularly with the temperature ramping rate of the AuSn eutectic bonding. Raman scattering spectra indicated that more δ phase with good plasticity in the solder joint played an important role on the stress relaxation of the GaN. Light output power versus current (L–I) results showed that ζ phase penetration across AuSn layer enhanced the thermal and electrical conductivity, which could reduce the junction temperature and spread the current uniformly. The red shift of electroluminescence peaks under large current was caused by the large thermal mismatch stress in VSLEDs. [ABSTRACT FROM AUTHOR]

Summary: Rice sheath blight caused by Rhizoctonia solani is the major disease of rice that seriously threatens food security worldwide. Efficient and eco‐friendly biological approaches are urgently needed since no resistant cultivars are available. In this study, fallow and paddy soils were initially subjected to microbiome analyses, and the results showed that Talaromyces spp. were significantly more abundant in the paddy soil, while Trichoderma spp. were more abundant in the fallow soil, suggesting that Talaromyces spp. could live and survive better in the paddy soil. Five Talaromyces isolates, namely, TF‐04, TF‐03, TF‐02, TF‐01 and TA‐02, were isolated from the paddy soil using sclerotia of R. solani as baits and were further evaluated for their activity against rice sheath blight. These isolates efficiently parasitized the hyphae and rotted the sclerotia even at higher water contents in the sterilized sand and the soil. Isolate TF‐04 significantly promoted rice growth, reduced the severity of rice sheath blight and increased the rice yield under outdoor conditions. Defence‐related genes were upregulated and enzyme activities were enhanced in rice treated with isolate TF‐04. Our research supplies a microbiome‐guided approach to screen biological control agents and provides Talaromyces isolates to biologically control rice sheath blight. [ABSTRACT FROM AUTHOR]

In this study, field data from 148 farmers were combined with energy equivalents, greenhouse gas emission factors, and product prices obtained from the literature and official statistics to evaluate and compare the energy use, environmental impact, and economic benefits between smallholders' rice production mode (SHM) and scale rice production modes (Big grain growers' rice production mode; Micro cooperatives' rice production mode). Compared with SHM, the scale rice production modes increased the net energy by 425.02 MJ ha−1–13148.29 MJ ha−1, increased the energy use efficiency by 16.85%–22.89%, increased the net economic return by 15.67 USD ha−1–531.31 USD ha−1, increased the net profit-to-labor use ratio by 26.02%–393.87%, decreased the global warming potential (GWP) by 19.48%–27.23%, and decreased the yield-scaled GWP by 19.93%–29.50%. These results demonstrate that the scale rice production modes can satisfy the needs of reduced labor inputs, energy conservation, emission reduction, and increased profitability of rice production, thereby promoting sustainable and low-carbon development of the agricultural industry in China. Based on these findings, it is recommended that the government increase its support for developing scale rice production modes and encourage farmers to take equity in their lands or lease them to micro cooperatives for more efficient production. [Display omitted] • The performance of scale rice production modes in China is unknown. • To evaluate the performance of three rice production modes. • Scale rice production modes reduce energy input and greenhouse gas emissions. • Scale rice production modes ensure rice yield and increase the economic income. • It is recommended that government and farmers develop scale rice production modes. [ABSTRACT FROM AUTHOR]

Background: Seed dormancy, a quality characteristic that plays a role in seed germination, seedling establishment and grain yield, is affected by multiple genes and environmental factors. The genetic and molecular mechanisms underlying seed dormancy in rice remain largely unknown. Results: Quantitative trait loci (QTLs) for seed dormancy were identified in two different mapping populations, a chromosome segment substitution line (CSSL) and backcross inbred line (BIL) population, both derived from the same parents Nipponbare, a japonica cultivar with seed dormancy, and 9311, an indica cultivar lacking seed dormancy. A total of 12 and 27 QTL regions for seed dormancy were detected in the CSSLs and BILs, respectively. Among these regions, four major loci (qSD3.1, qSD3.2, qSD5.2 and qSD11.2) were commonly identified for multiple germination parameters associated with seed dormancy in both populations, with Nipponbare alleles delaying the seed germination percentage and decreasing germination uniformity. Two loci (qSD3.1 and qSD3.2) were individually validated in the near-isogenic lines containing the QTL of interest. The effect of qSD3.2 was further confirmed in a CSSL-derived F2 population. Furthermore, both qSD3.1 and qSD3.2 were sensitive to abscisic acid and exhibited a significant epistatic interaction to increase seed dormancy. Conclusions: Our results indicate that the integration of the developed CSSLs and BILs with high-density markers can provide a powerful tool for dissecting the genetic basis of seed dormancy in rice. Our findings regarding the major loci and their interactions with several promising candidate genes that are induced by abscisic acid and specifically expressed in the seeds will facilitate further gene discovery and a better understanding of the genetic and molecular mechanisms of seed dormancy for improving seed quality in rice breeding programs. [ABSTRACT FROM AUTHOR]

In the background of retail side's marketability reform, the method of choosing high-quality users of the power distribution company based on multidimension characteristics mining is studied. First, the evaluation model concerning the user's multidimensional feature is established, and the user's feature mining is carried out from five different aspects, including curve type, response ability, economic value, credit rating and predictability of electricity. The improved k-mean clustering algorithm is used to classify the user's curves, and the curves are evaluated and quantified through the load index. The other four indexes' quantitative values are obtained by analytic hierarchy process. After the quantization of indexes, the user's characteristic index vector is obtained. Then the optimized combination model of premium users is set up to make the combination performs better in many different aspects. The actual user data in Baoding is used to validate the results, demonstrating that the proposed model is practical and effective. [ABSTRACT FROM AUTHOR]

To provide a modified formula consistent with the Monte Carlo (MC) algorithm for dose calculations during stereotactic ablative body radiotherapy for non–small cell lung cancer. Seventy CyberKnife treatment plans were calculated and analyzed by MC and ray-tracing (RT) algorithms, separately. Parameters of treatment plans were compared, and those associated with differences of dose distributions were analyzed to establish a modified formula. Gross tumor volume and tumor tracking volume (TTV) were defined as the evident disease on the sequences of the window width and level of the lung and the mediastinum. Additionally, the formula was validated by another 20 plans. The prescription dose of the 90 patients was 60 Gy/5f. The RT algorithm overestimated the planning target volume (PTV) D 95 by an average of 8.59 Gy and the gross tumor volume D 99 by an average of 5.84 Gy. The homogeneity index of PTV was underestimated by 0.11 on average, whereas the conformity index and new conformity index was underestimated by 0.05. The RT algorithm overestimated the dose distribution to the spinal cord by 2.23 Gy, the esophagus by 1.96 Gy, the trachea by 1.89 Gy, the left-sided bronchus by 1.77 Gy, the right-sided bronchus by 1.64 Gy, and the heart by 2.16 Gy. The average whole-lung dose volumes of lung tissues and dose volumes of V 5 were overestimated by 2.69 Gy and 7.52%, respectively. A power function distribution ( R 2  = 0.8626) was confirmed between PTV D 95 and TTV volumes. PTV D 95 calculated by the MC algorithm could be computed easily with TTV and PTV D 95 calculated by the RT algorithm based on the formula. The modified equation was more consistent with MC algorithm than with other formula, which could be a reference to those not accessible to the MC algorithm. [ABSTRACT FROM AUTHOR]

To investigate the development direction of mechanized rice production in China, we compared the differences between two production modes, namely, unmanned aerial vehicle direct seeding (UDS) and integrated mechanical transplanting (IMT) in energy use efficiency (EUE) and economic benefits from 2017 to 2019. Fertilizer, fuel, and water account for the top three largest proportions of total energy input under both production modes. The energy inputs in fuel, irrigation water, and plastic film under UDS were 4611.34 MJ ha−1, 1355.21 MJ ha−1, and 3913.02 MJ∙ha−1 lower than those under IMT, respectively. The application of transplanting and fertilizer-pesticide spraying integration machine under IMT contributed to its energy-saving advantages in electricity, fertilizer and pesticide; however, the energy inputs in these three aspects were only reduced by 30.74 MJ ha−1, 355.98 MJ ha−1 and 69.34 MJ ha−1, respectively. The total energy input under IMT from 2017 to 2019 was 45.11%–45.69% higher than that under UDS. There was no significant difference in rice grain yield and straw yield. The EUE, energy productivity and energy profitability under UDS were 41.03%, 41.87%, and 46.69% higher than those under IMT, respectively. The cost under UDS was 13.8% lower than that under IMT. In addition, under UDS, the net return was 7.5% higher, and the benefit-to-cost ratio was 24.7% higher. Energy input and cost under UDS were reduced compared with those under IMT on the premise of stable yield. It can be concluded that IMT is a more promising mechanized rice production mode in China. • Performances of IMT and UDS were analyzed in a three-year field experiment. • Grain yield and rice straw via UDS was similar to that in IMT. • Energy input under UDS was 31.19% (10061.38 MJ ha−1) lower than that under IMT. • UDS had significant lower cost with net return of US $2253.81 ha–1 • UDS is a high-yield and high-profitability production mode. [ABSTRACT FROM AUTHOR]

The single-step prediction of burning zone temperature plays an important role in the safety and stability control of cement rotary kiln. This is because, the abnormal temperature events can be found as early as possible and the operator can take effective emergency measures in time. In this paper, the burning zone temperature single-step prediction method based on real-time wavelet filtering and kernel extreme learning machine is studied. Firstly, the visual inspection device is used to detect the burning zone temperature. And then, the amplitude limited filtering method is used to weaken the effects of temperature anomalies. On this basis, the real-time filtering of the burning zone temperature is realized by combining the sliding time window and wavelet filtering method. After that, the single-step prediction of burning zone temperature is realized by combining the sliding time window and kernel extreme learning machine method. At last, the burning zone temperature prediction method is validated. The minimum root mean squared error of the 5 consecutive days is 0 . 4259 ° C . The single average running time of model training and prediction of kernel extreme learning machine is much less than support vector regression, which is very helpful for the online prediction of burning zone temperature. The result shows that the burning zone temperature single-step prediction method proposed in this paper is feasible and effective. [ABSTRACT FROM AUTHOR]

Background: To identify optimization of dose distributions of target volumes and decrease of radiation doses to normal tissues during stereotactic body radiation therapy (SBRT) for pancreatic cancer with dose-limiting auto-shells.Methods: With the same prescription dose, dose constraints of normal organs and calculation algorithm, treatment plans of each eligible patient were re-generated with 3 shells, 5 shells and 7 shells, respectively. The prescription isodose line and beam number of each patient in 3-shell, 5-shell and 7-shell plan remained the same. Hence, a triplet data set of dosimetric parameters was generated and analyzed.Results: As the increase of shell number, the conformal index, volumes encompassed by 100% prescription isodose line and 30% prescription isodose line significantly decreased. The new conformal index was higher in 3-shell group than that in 5-shell and 7-shell group. A sharper dose fall-off was found in 5-shell and 7-shell group compared to 3-shell group. And the tumor coverage in 7-shell was better than that of 3-shell and 5-shell. Lower D5cc of the intestine, D10cc of the stomach, Dmax of the spinal cord and smaller V10 of the spleen was confirmed in 7-shell group compared to 3-shell group.Conclusions: More conformal dose distributions of target volumes and lower radiation doses to normal organs could be performed with the increase of dose-limiting auto-shells, which may be more beneficial to potential critical organs without established dose constraints. [ABSTRACT FROM AUTHOR]

Bone and joint diseases are prevalent and often fatal conditions in elderly individuals. Additionally, bone-derived cells may release exosomes that package and distribute a range of active substances, such as proteins, miRNAs, and numerous active factors, thereby facilitating material and information interchange between cells. Exososmes generated from bone may be utilized to manage bone production and resorption balance or even as biological or gene therapy carriers, depending on their properties and composition. In this review, we will discuss the composition, secretion, and uptake theory of exososmes, the role of exososmes in bone metabolism regulation, the pathogenesis and diagnosis of bone and joint diseases, and the application of exososmes in regenerative medicine. The findings will expand our understanding of the potential research and application space regarding exososmes. [Display omitted] [ABSTRACT FROM AUTHOR]

Purpose: To test whether a novel guide template we designed can facilitate accurate insertion of antegrade lag screws in the fixation of acetabular posterior column fractures.Methods: We created virtual three-dimensional reconstruction models of the pelvis from CT scan data obtained from 96 adult patients without any bony problems. A virtual cylindrical implant was placed along the longitudinal axis of the acetabular posterior column passing through the ischial tuberosity. The diameter of cylindrical implant was augmented to 6.5 mm, and the direction was adjusted until the optimal screw path was found using the reverse engineering technique. The orifice of this cylinder from the iliac fossa was determined as the entry point for the antegrade lag screw. The anatomical parameters of the screw entry path were measured and saved in .stl format. The guide template was designed according to the acetabular morphology and the measured anatomical parameters before it was put into manufacture of a solid template with the rapid prototyping technique. The feasibility and accuracy of the guide template were tested in cadaveric pelvises. Finally, the guide template was used in real surgery for five patients. Furthermore, the time required for surgery was recorded.Results: Under the guide of this navigation template, antegrade lag screws were successfully placed in the posterior column of the acetabulum in the cadaveric test. And five lag screws were successfully placed in five patients. The mean time of antegrade lag screw insertion required 5.8 (3-10) min.Conclusions: Antegrade lag screws can be more accurately put into the posterior column of the acetabulum with the help of this navigation template. [ABSTRACT FROM AUTHOR]

Environmental factors and plant hormones are major players in seed germination. Abscisic acid (ABA) not only delays seed germination but also acts as a central regulator in plant growth, development and response to stress conditions. In this study, a rice C2H2-type zinc finger protein, OsZFP15, was screened by microarray and characterized. RT-qPCR and GUS staining assays revealed that OsZFP15 was significantly induced by ABA and multiple abiotic stresses. Subcellular localization assay indicated that OsZFP15 protein was located in the nucleus of rice protoplast. Overexpression of OsZFP15 reduced the sensitivity to ABA and down-regulated transcript levels of ABA-responsive genes including LEA3 and LIP9 , but increased transcript level of OsABA8ox2 , suggesting that OsZFP15 is a positive regulator of ABA catabolism. Additionally, overexpression of OsZFP15 in rice enhanced ABA catabolism and thus accelerated seed germination. We further investigated the role of OsZFP15 in abiotic stress response. Overexpression of OsZFP15 promoted reactive oxygen species (ROS) production and accordingly reduced the tolerance to oxidative stress. Conversely, improvements in salinity and drought tolerance were observed in OsZFP15 overexpression plants. • Overexpression of OsZFP15 decreases the height of rice, but increases the seed setting rate and grain number per panicle. • Overexpression of OsZFP15 improves rice tolerance to drought and salt stress. • OsZFP15 enhances ABA catabolism through OsABA8ox2 to promote seed germination [ABSTRACT FROM AUTHOR]

Triangle planting geometry (TPG) is a new rice arrangement mode, whereby plants form a “dense intra-hill, sparse inter-hill” group structure. This allows them to have more spatial options, thus avoiding excessive infra-hill competition when compared to conventional row configurations. However, there is limited information on how TPG might affect rice production, especially for newly-bred varieties featuring a heavy panicle size (5 g panicle −1 ). This study was conducted to evaluate grain yield performance and yield component changes of heavy panicle varieties under TPG. Moreover, to identify any promising agronomy traits and population structural features that might explain the difference in yield performance as well as to probe whether the high-yielding performance of TPG is reproducible in other circumstances. In 2012, Eryou498 (a heavy panicle variety) was grown under four planting geometries (PGs) in two fields that had similar soil fertility, but that were conducted with either conventional tillage or zero-tillage systems. In 2013, two heavy panicle varieties and two medium panicle varieties (2–5 g panicle −1 ) were grown under three PGs in two ecological regions. Grain yield and effective panicles were significantly affected by both variety and PG. A significant interaction of PG and variety was seen on grain yield, but the high-yielding performance of TPG was consistent with all varieties. Sufficient total spikelets were the basis of achieving a high grain yield. Effective panicles predominantly attributed to total spikelets across all four experiments. Robust spikelets were crucial when grain yield was at a high level. Heavy panicle varieties and TPG showed some similar high-yielding traits. These included rapid crop growth rate (CGR) during the two weeks before full heading, plenty non-structural carbohydrate (NSC) accumulated at full heading, mass NSC output in two weeks after full heading, and high radiation use efficiency (RUE). Rice under TPG presented a more compact top three leaves as well as more stretched lower leaves when compared to other PGs. Overall, all leaves of heavy panicle varieties were more stretched than those found in medium ones. Heavy panicle varieties accumulated more nitrogen (N) in leaves from elongation to 30 days after full heading while PG showed no significant effect on leaf N concentration during the late grain-filling period. These results suggest that the high-yielding performance of TPG is reproducible in other circumstances. The combination of TPG and heavy panicle varieties is advantageous, allowing for a more efficient canopy structure for heavy panicle varieties and a more robust photosynthetic ability at late grain-filling period under TPG. [ABSTRACT FROM AUTHOR]

This study performed energy analyses of fully mechanized rice production mode (FM) and semi-mechanized rice production mode (SM) in China. Fertilizer, fuel, and water were the three largest inputs, accounting for 92.02% of the total energy input. FM adopted side-deep fertilization with machine transplanting and implemented intermittent irrigation regime to improve water and fertilizer use efficiency. Compared with SM, FM reduced fertilizer and water energy inputs by 1252.62 MJ ha−1 and 2187.87 MJ ha−1, respectively. Because of the lower degree of mechanization, the fuel energy input of SM was 691.19 MJ ha−1 less than that of FM. The total average energy input of FM was 23,610 MJ ha−1, which was 10.80% lower than SM (26,470.01 MJ ha−1), whereas the rice and straw yields of FM were not significantly different from SM. The energy use efficiency, energy productivity, and energy profitability of FM were 11.10, 0.41 kg MJ−1, and 10.10, respectively, corresponding to increases of 8.56%, 8.61%, and 9.49% compared to SM. With appropriate agronomic measures in rice production, a higher degree of mechanization would not necessarily lead to an increase in energy input in Southwest China. [Display omitted] • Fully mechanized (FM) and semi-mechanized (SM) rice production modes were compared. • The energy consumption of SM increased by 12.11% on average compared to that of FM. • Fertilizer, fuel, and water accounted for about 92% of the total energy input. • Energy use efficiency and energy productivity of FM were higher than that of SM. • FM has more advantages than the SM. [ABSTRACT FROM AUTHOR]

As a modern and high efficient rice production mode, rice mechanized transplanting has been a principle development trend in China. Subject to geographical conditions, the development of rice mechanized transplanting in Sichuan, the largest rice production region in southwest China, is very slow, only account for 6.2% of total rice planting area in 2012, while the average ratio was 26% across the country. So the development of rice mechanized transplanting in Sichuan is urgent and meaningful. The optimal seedling age and variety is an essential problem should be solved. In this experiment, the effects of different seedling ages on yield and population quality of middle and late maturing hybrid rice in mechanized transplanting were studied. The experiment was conducted in Wenjiang, a representative plain region in Sichuan, from April to October during 2011 growing season. The experiment was designed as split plot with seedling age as main plot and variety as sub-plot with three replicates. Three different seedling ages as the main plot were 21, 28 and 35 days, and four rice varieties were selected with growth duration of middle and late maturating, respectively. Chuanxiang 3 and Fuyou 838 (142 days and 145 days growth duration) are middle maturing rice, while F-You 498 and Gangyou 725 (148 days and 150 days growth duration) are late maturing rice. The climate conditions during seedling stage in 2011 were representative and consistent with that of recent 5 years in precipitation, sunshine and temperature. The seedling rate of each seedling tray was 80 gram and seedlings were transplanted at a hill spacing of 30 cm × 15 cm, each plot covered 19.2 m². The nitrogen fertilizer amount was 150 kg/hm², and the amount of potash and phosphate are 90 kg/hm² and 75 kg/hm², respectively. The other managent measures were at a uniform with high-yield cultivation. The experiment results showed that all indexes were better than that of larger seedlings rice in mechanized transplanting, including grain yield, tillers at the effective tillering of critical leaf age(N-n), percentage of productive tiller, leaf area index, photosynthetic rate of flag leaf after heading, light transmission of groups, leaf area rate of productive tillers at heading and its ratio, leaf area from flag leaf to 3rd leaf from top of productive tillers at heading and its ratio. As for varieties, on both grain yield and various rice population indexes, the late maturing varieties were better than the middle maturing ones significantly, especially for F-You 498. F-You 498 showed medium tillering ability and ideal plant type, which is beneficial for improving light interception and reducing unproductive tillers, contributing to an excellent population photosynthetic production and a larger grain number per spike. Besides its impressed yield ability, F-You 498 got a better seedling flexibility, it can remained a relative high grain yield when seedling age extended to appropriately 28 days. In the middle maturity group, although Fuyou 838 have more number of panicles, their spikelets per panicle are poor, which restrict the yield increase. In this progress, too many unproductive tillers caused by immoderate tillers should be the main reason. [ABSTRACT FROM AUTHOR]

As a special micro-motion feature of rotor target, rotational angular velocity can provide a discriminant basis for target classification and recognition. In this paper, the authors focus on an efficient rotational angular velocity estimation method of the rotor target is based on the combination of the time–frequency analysis algorithm and Hough transform. In order to avoid the problems of low time–frequency resolution and cross-term interference in short-time Fourier transform and Wigner–Ville distribution algorithm, a modified short-time fractional Fourier transform (M-STFRFT) is proposed to obtain the time-FRFT domain (FRFD)-frequency spectrum with the highest time–FRFD–frequency resolution. In particular, an orthogonal matching pursuit (OMP)-based algorithm is proposed to reduce the computational complexity when estimating the matched transform order in the proposed M-STFRFT algorithm. Firstly, partial transform order candidates are selected randomly from the complete candidates. Then, a partial entropy vector corresponding to partial transform order candidates is calculated from the FRFT results and utilized to reconstruct the complete entropy vector via the OMP algorithm, and the matched transform order can be estimated by searching minimum entropy. Based on the estimated matched transform order, STFRFT is performed to obtain the time–FRFD–frequency spectrum. Moreover, Hough transform is employed to obtain the energy accumulation spectrum, and the micro-Doppler parameter of rotational angular velocity can be estimated by searching the peak value from the energy accumulation spectrum. Both simulated data and measured data collected by frequency modulated continuous wave radar validate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

To evaluate the efficient use of nitrogen (N) for rice in a rapeseed–wheat–rice rotation system, a pot experiment was conducted. The results indicated that in the conventional 15N-labeled (Nc) and reduced 15N-labeled (Nr) urea applications, absorbed N and soil residual N was higher in rapeseed than in wheat. In the rice season, the higher accumulation of 15N was achieved with an Nr application rate during the rapeseed season and an N fertilizer management model (40% as basal fertilizer, 40% as tillering fertilizer, and 20% as panicle fertilizer) during the rice season (PrNrM3). A high 15N accumulation was also achieved under the Nc application rate during the wheat season and the N fertilizer management model during the rice season (PwNcM3). The accumulation of 15N in PrNrM3 and PwNcM3 accounted for 21.35% and 36.72% of the residual N under the Nr application rate in the rapeseed season and the Nc application rate in the wheat season, respectively. Compared with the Nc application rate in the rapeseed season and M3 N management in the rice season (PrNcM3), the N agronomy efficiency (NAE) and the N partial factor efficiency (NPFP) of rice were increased by 23.85% and 1.59%, respectively, in PrNrM3. The annual crop yield was 3.95% lower in PrNrM3, which was not significant. PrNrM3 was a stable yield, N-saving application rate for rapeseed-rice rotation systems in southern China. [ABSTRACT FROM AUTHOR]

This investigation aims to provide theoretical and practical evidence for the efficient utilization of nitrogen (N) in paddy-upland rapeseed-rice rotation systems because a lack of previous research on such rotation systems leads to inefficient management practices. The effects of the N application rates and the N fertilizer management strategies for rapeseed and rice were examined, respectively, in relation to the photosynthetic productivity and yields of hybrid rice. The results indicated that the leaf area, Pn, with 40% as basal fertilizer, 40% as tillering fertilize, and 20% as panicle fertilizer and a reduced N rate (30 kg/ha) during the rape season, were higher than other nitrogen management strategies trialed, with conventional N rates in the rape season. The average rice grain yield (9545.15 kg/ha) over the two years with 40% as basal fertilizer, 40% as tillering fertilizer, and 20% as panicle fertilizer was higher than other N treatments with the reduced N rates during the rape season. The reduced N rate during the rapeseed season and 40% as basal fertilizer, 40% as tillering fertilizer, and 20% as panicle fertilizer management during the rice season for the rape-rice rotation system exhibited the highest rice yields. Our findings indicated that the N fertilizer management model was a high-yielding, N-saving, and environmentally friendly measure for rape–rice rotation systems in southern China. [ABSTRACT FROM AUTHOR]

• Methodical nitrogen–water distribution management (MNWD) couples nitrogen and water application in rice production. • MNWD stabilized rice yield and reduced nitrogen and water input in rice production simultaneously. • Larger amount of root in soil layers deeper than 10 cm of MNWD was the key for higher water and nitrogen use efficiencies. Methodical nitrogen–water (N–W) distribution management (MNWD) is a comprehensive N–W management technique designed to meet the requirements of rice production in China and specifically, the stabilization of grain yield and reduction of input resources. In this study, four split plot field experiments were conducted in two locations to examine the impact of MNWD on N use efficiency (NUE) and water use efficiency (WUE). We used high N efficiency rice varieties, Dexiang 4103 and Fyou 498, and low N efficiency varieties, Yixiang 3724 and Chuanyou 6203, and three N–W management techniques were established as subplot treatments, including farmers' usual management (FU), N–W coupling management (NWC), and MNWD. Under MNWD, N application rates were 20% lower than those under NWC and FU, whereas the amounts of irrigation water were reduced by 20%–25% and 42%–48%, respectively. Yields under MNWD were similar to those under NWC (–2.51–0.45%), and there was an average yield increase of 8.13%–13.95% over FU. Rice plants under MNWD had larger amounts of roots, particularly in soil depth > 10 cm There were significant positive correlations between root dry mass in the various soil depths and WUE and irrigation WUE (IWUE), with the impact of roots in soil depth > 10 cm on rice plant WUE (IWUE) pronounced. MNWD's IWUE was higher than that of NWC and FU by 22.95%–38.79% and 86.49%–126.69%, respectively, and its WUE was higher by 6.75%–20.74% and 37.05%–71.80%, respectively. Correlation analysis showed that the N absorption and accumulation capacities of rice plants under MNWD increased along with increases in soil fertility. The MNWD's NUE advantage was apparent in soil depth > 10 cm where its root dry mass was especially large, with an average biomass productivity of N higher than that of NWC and FU by 4.16%–10.78% and 7.49%–18.01%, respectively and an N internal efficiency higher by 0.33%–8.29% and 5.32%–10.04%, respectively. Overall, MNWD effectively improved WUE and NUE of rice without significant grain yield reduction. [ABSTRACT FROM AUTHOR]

For a conventional narrow-band radar system, the detectable information of the target is limited, and it is difficult for the radar to accurately identify the target type. In particular, the classification probability will further decrease when part of the echo data is missed. By extracting the target features in time and frequency domains from multi-wave gates sparse echo data, this paper presents a classification algorithm in conventional narrow-band radar to identify three different types of aircraft target, i.e., helicopter, propeller and jet. Firstly, the classical sparse reconstruction algorithm is utilized to reconstruct the target frequency spectrum with single-wave gate sparse echo data. Then, the micro-Doppler effect caused by rotating parts of different targets is analyzed, and the micro-Doppler based features, such as amplitude deviation coefficient, time domain waveform entropy and frequency domain waveform entropy, are extracted from reconstructed echo data to identify targets. Thirdly, the target features extracted from multi-wave gates reconstructed echo data are weighted and fused to improve the accuracy of classification. Finally, the fused feature vectors are fed into a support vector machine (SVM) model for classification. By contrast with the conventional algorithm of aircraft target classification, the proposed algorithm can effectively process sparse echo data and achieve higher classification probability via weighted features fusion of multi-wave gates echo data. The experiments on synthetic data are carried out to validate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]