Search

The potential of salicylic acid (SA) in delaying postharvest fruit senescence has been extensively documented; nevertheless, its effect on antioxidant activity and quality of ‘France’ prune fruit is largely unknown. The study investigated the effects of SA (0.5 mM) on postharvest quality deterioration of ‘France’ prune fruit. Results indicated that SA impeded the increase in respiration rate and weight loss, and mitigated the decrease of soluble solids content (SSC), titratable acidity (TA) content, firmness, and hue angle. SA sustained the ascorbate-glutathione cycle by inducing the production of ascorbic acid (AsA) and glutathione (GSH) and attenuates flavonoids, total phenols, and anthocyanins degradation by inhibiting polyphenol oxidase (PPO) activity and PdPPO. Moreover, SA significantly improved superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), peroxidase (POD), and glutathione reductase (GR) activities and gene expression levels, sustained higher 2,2′-Azinobis-(3-ethylbenzthiazoline-6-sulphonate) (ABTS) and 1,1-diphenyl-2-picryl-hydrazyl (DPPH) free radical scavenging capacity, ferric reducing antioxidant power (FRAP), and hydroxyl radical (·OH) inhibition capacity, and impeded the production of hydrogen peroxide (H2O2) and superoxide anion (O2•−). Overall, SA improved the antioxidant capacity by inducing the synthesis of defense response-related substances and promoting antioxidant enzyme activities to sustain the storage quality of ‘France’ prune fruit.

Nitrification is the core step of the soil nitrogen cycle and directly affects the nitrogen use efficiency in agricultural systems. Biochar and gypsum are two important soil amendments widely used in coastal saline farmland. However, little is known about their effects on nitrification and ammonia-oxidizing microorganisms. A one-year pot experiment with three treatments including biochar application (BC), gypsum application (SG), and no amendment (CK) was conducted, and the responses of the nitrification rate, amoA gene copies, and the diversity and community structure of ammonia-oxidizing archaea (AOA) and bacteria (AOB) to biochar and gypsum were evaluated. The results indicated that biochar and gypsum application both resulted in alterations to the soil properties. They both had inhibiting effects on nitrification and AOB amoA gene copies, whereas they had no significant effect on AOA amoA gene copies. Biochar had no significant effect on the diversity indexes of AOA, but it significantly reduced the Shannon index of AOB. Meanwhile, gypsum had no significant influence on the diversity indexes of both AOA and AOB. Biochar and gypsum did not significantly affect the community structure of AOA but did induce changes in that of AOB. In detail, biochar significantly enhanced the relative abundance of the dominant cluster Nitrosospira, whereas gypsum led to a notable increase in the relative abundance of unclassified_o_Nitrosomonadales. The Shannon index of AOB had a significant negative correlation with soil TOC, TN, and NH4+ content, and soil pH was the first primary environmental factor that affected the AOB community structure. In conclusion, biochar and gypsum inhibited nitrification by suppressing the activities of AOB and changed the diversities and community structure of AOB by altering related soil properties.

The design and preparation of high-performance separators for lithium-ion batteries (LIBs) have far-reaching practical significance in enhancing the overall performance of LIBs. Electrospun nanofiber separators (ENSs) have the characteristics of large specific surface area, high porosity, small pore size and good affinity with the electrolyte, making them become ideal candidates for LIB separators. In this work, polyacrylonitrile (PAN)/polyurethane (PU) (PAU) ENSs loaded with boehmite (BM) particles (BM/PAU ENSs) were mass-produced using spherical section free surface electrospinning (SSFSE), and used as LIB separators. Their morphology, structures and performances were tested and characterized. The results showed that all BM/PAU ENSs maintained excellent thermal dimensional stability in the range of 140–180 °C, and had good electrolyte wettability and high porosity. The composite BM/PAU-2 ENS with the best performance had a porosity of 52.5%, an electrolyte uptake rate of 822.1%, and an ionic conductivity of 1.97 mS/cm. Additionally, the battery assembled with BM/PAU-2 separator also demonstrated best electrochemical performance, cycling performance, and rate capability, with a capacity retention rate of 94.4% after 80 cycles at 0.5 C, making it a promising high-performance separator for LIBs.

A visual system is a key tool for automatic fruit harvesting. It faces the challenges of varied occlusion and illumination in the field, resulting in difficulties in fruit recognition and picking. At present, there are many studies that lack a comprehensive analysis of the impact of the environment on harvesting. This study proposes an object–environment fusion visual system. It comprises modules for object perception, environment perception, and picking pose estimation. The object perception module aims to identify and locate pears. The environment perception module is deployed to analyze the three-dimensional (3D) information of objects and obstacles. Finally, the picking pose estimation module fuses the information of the objects and environment to calculate the collision-free picking position and orientation. Additionally, specific implementations are employed for each module. It compares three networks to identify pears for object perception. Voxel-based representation is used to simplify point clouds for environmental perception. A sampler and evaluator are applied for picking pose estimation. The S1 and S2 datasets were acquired in a laboratory pear tree model and the orchard of Zhejiang Academy of Agricultural Sciences, respectively, to evaluate the proposed method. In the S2 dataset, the success rate for picking pose estimation reached 87.11% within the distance range of 30∼50 cm. All of the results demonstrate that the proposed method can be applied to visual perception for automatic pear harvesting.

The Hetao irrigation region is located in Inner Mongolia, China, within a dry and semi-dry region. This region suffers from poor agricultural productivity and environmental damage due to the presence of saline soil. To explore the growth of salty lands using a more environmentally friendly method, this research employed three eco-conscious amendments to improve the soil. These include flue gas desulfurization gypsum (S), humic acid (H), and biochar (C). During a two-year study, the amendments were utilized to enhance the soil quality for planting sunflowers. Humic acid was used prior to every seedling season, whereas the remaining two substances were only used once. These additions increased the soil’s water-holding capacity, reduced soil salinity during sunflower growth, and improved the macroaggregate proportion. The most effective treatment for decreasing the soil’s salt content after the seedling stage was the application of humic acid (0.6 t ha−1). Biochar (15 t ha−1) decreased the soil’s bulk density (from 1.49 to 1.34 g cm−3) and mostly increased the sunflower seed yield up to 3133−3964 kg ha−1. Humic acid addition significantly increased the aggregate (>0.25 mm) content up to 27.88% after the experiment, but it led to a lower seed yield (2607−3686 kg ha−1). In 2019, the temperature was lower compared to 2018, which may have led to a reduction in the yield. However, these three amendments could potentially increase yields by more than conventional methods. These three environmentally friendly amendments are useful for improving saline soil and increasing yields. More studies are required to understand their impacts on larger areas and over extended periods.

Automatic speech recognition (ASR) that relies on audio input suffers from significant degradation in noisy conditions and is particularly vulnerable to speech interference. However, video recordings of speech capture both visual and audio signals, providing a potent source of information for training speech models. Audiovisual speech recognition (AVSR) systems enhance the robustness of ASR by incorporating visual information from lip movements and associated sound production in addition to the auditory input. There are many audiovisual speech recognition models and systems for speech transcription, but most of them have been tested based in a single experimental setting and with a limited dataset. However, a good model should be applicable to any scenario. Our main contributions are: (i) Reproducing the three best-performing audiovisual speech recognition models in the current AVSR research area using the most famous audiovisual databases, LSR2 (Lip Reading Sentences 2) LSR3 (Lip Reading Sentences 3), and comparing and analyzing their performances under various noise conditions. (ii) Based on our experimental and research experiences, we analyzed the problems currently encountered in the AVSR domain, which are summarized as the feature-extraction problem and the domain-generalization problem. (iii) According to the experimental results, the Moco (momentum contrast) + word2vec (word to vector) model has the best AVSR effect on the LRS datasets regardless of whether there is noise or not. Additionally, the model also produced the best experimental results in the experiments of audio recognition and video recognition. Our research lays the foundation for further improving the performance of AVSR models.

With the gradual depletion of fossil energy sources and the improvement in environmental protection attention, efficient use of energy and reduction in carbon emissions have become urgent issues. The integrated electricity and heating energy system (IEHS) is a significant solution to reduce the proportion of fossil fuel and carbon emissions. In this paper, a stochastic optimization model of the IEHS considering the uncertainty of wind power (WP) output and carbon capture power plants (CCPs) is proposed. The WP output in the IEHS is represented by stochastic scenarios, and the scenarios are reduced by fast scenario reduction to obtain typical scenarios. Then, the conventional thermal power plants are modified with CCPs, and the CCPs are equipped with flue gas bypass systems and solution storage to form the integrated and flexible operation mode of CCPs. Furthermore, based on the different load demand responses (DRs) in the IEHS, the optimization model of the IEHS with a CCP is constructed. Finally, the results show that with the proposed optimization model and shunt-type CCP, the integrated operation approach allows for a better reduction in carbon capture costs and carbon emissions.

To investigate the physiological and molecular properties relating to cell wall carbohydrate metabolism in fruit, the ultrastructure and polysaccharides compositions of the cell wall, as well as the fruit quality and activities of enzymes relating to fruit softening, were studied for three Hami melon varieties (‘Xizhoumi 17’, ‘Jinhuami 25’, and ‘Chougua’) representing three different storability levels. The results showed that ‘Chougua’ maintained a higher firmness on day 18, with the lowest decay incidence (0%). ‘Chougua’ showed a better storage quality and intact cell wall structure. The molecular weight and monosaccharide composition of cell wall polysaccharides for Hami melons underwent great changes during storage, and the degradation of pectin polysaccharides was obvious, involving the depolymerization of macromolecular polymers accompanied by the production of new macromolecular polymers and composition changes in pectin monosaccharides (glucose, galactose, and arabinose) during the softening process of the Hami melons. Polygalacturonase, pectin methylesterase, xyloglucan endo-transglycosylase/hydrolase, α-arabinofuranosidase, β-galactosidase, and cellulase were associated with fruit softening at different stages of storage. There were similar softening mechanisms in the three Hami melons. This study will provide reference for further study on the fruit softening mechanisms of Hami melons.

This study analyzes and evaluates the feasibility of a harmonic suppression traction transformer (HSTT) for harmonic reduction in railway systems. This new type of transformer can improve the power quality of railway systems by preventing high-frequency harmonic currents from injecting into the traction grid. As the physical size of available space in high-speed trains is strictly limited, low space-occupying filtering techniques are needed. Therefore, an HSTT with integrated filtering inductors (IFIs) capable of being implemented in regular trains is proposed. Taking advantage of the HSTT, a specially constructed inductive-capacitive-inductive (LCL)-type filter is used for harmonic suppression instead of a regular LCL-type filter. The proposed filter is composed of an integrated inductor, leakage inductor of the traction transformer, and an external filter capacitor. In this paper, we analyze the topology of the proposed system, construct a mathematical model to reveal the magnetic decoupling theory of IFIs, and discuss the design and calculation procedures of the HSTT with IFIs. The field circuit coupling simulation of the HSTT with IFIs is performed to validate the effectiveness of the proposed system. Finally, the practical operation based on a 10 kVA prototype shows that the proposed scheme can not only suppress the high-order frequency harmonics but also decrease the installed space of filter devices.

Coal is among the most important energy sources, and gob-side entry retention by roof cutting (GERRC) is an innovative non-pillar mining technique that can effectively increase coal recovery rates and avoid coal wastage. To investigate the characteristics of mine strata pressure using the GERRC technique, a field case study under conditions involving a medium-thick coal seam and a compound roof was performed, and the mine strata behavior mechanisms were studied by theoretical analysis. Field monitoring shows that the distributions of the weighting step and strength along the longwall working face are asymmetrical. The periodic weighting length on the entry retaining side is longer than that on the other sides of the longwall working face, and the average increase is appropriately 4 m. Compared to the other sides of the longwall, on the entry retaining side, the periodic weighting strength is weaker, the average pressure is reduced by 2.1 MPa, and the peak pressure is reduced by 10.2 MPa. The lateral distance affected by roof cutting along the longwall is approximately 29.75 m, and the closer to the cutting slit, the more significant the roof cutting effect is. The retained entry becomes stable when it is more than 230 m behind the mining face, and the final cross section of the retained entry can meet the reuse demand of the next mining face. Theoretical analysis shows that the roof pressure mechanism in GERRC can be explained using cantilever beam theory. Within the area affected by roof cutting, the thickness of the immediate roof increases, and the suspension plate length of the roof immediately behind the longwall decreases. Then, the gangue pile in the goaf behind the longwall formed by the immediate roof’s collapse and expansion can support the main roof and other overlying strata much better. Therefore, the rotational breaking angle of the main roof is smaller, the periodic weighting step strength increases, and the periodic weighting decreases. According to the structural state of the surrounding rocks during the entire entry retaining process, the retained entry can be divided into coal support, dynamic pressure and stable entry areas.