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In order to solve the problem that the data distribution of the source domain and the target domain of rolling bearing is different in the variable working condition environment and the samples of the target domain do not contain labels, a fault diagnosis model of the rolling bearing based on the deep adaptive transfer learning network (DATLN) is proposed. Firstly, a domain-shared characteristic extraction network is built, and multiscale convolutional neural network (MSCNN) is used to suppress noise interference, so as to effectively extract local fault information contained in vibration signals. Secondly, combined with a bi-directional long short-term memory network (BiLSTM), the temporal characteristics in the local fault information are further learned. Finally, transfer learning is introduced to build a domain adaptive module with domain adversarial (DA) training combined with adaptive joint distribution (AJD) metrics. By maximizing the domain classification loss and minimizing the AJD distance, the source and target domain characteristic samples are aligned. The anti-noise experiment and transfer experiment are carried out on the open source CWRU data set and the measured data set of the mechanical fault platform respectively. The anti-noise experiments show the following points. ① The identification accuracy of MSCNN-BiLSTM network is above 99% in the noise-free environment, which shows that MSCNN-BiLSTM network has a good characteristic extraction capability. ② The identification accuracy of MSCNN-BiLSTM, LeNet-5, MSCNN and BiLSTM decreases with the increase of noise intensity. ③ Under the noise environment of 3, 5 and 10 dB, the average identification accuracy of MSCNN-BiLSTM network is higher than that of LeNet-5, MSCNN and BiLSTM networks, indicating that MSCNN-BiLSTM network has better anti-noise interference performance. ④ The MSCNN-BiLSTM network converges first with less fluctuation in both the noise-free environment and the 3 dB noise environment. The transfer experiments show the following points. ① The average identification accuracy of DA+AJD method is 97.36% on unlabeled target domain dataset, which is higher than that of Baseline, transfer component analysis(TCA) and domain adversarial neural network (DANN). ② On the test set confusion matrix, only one sample of the DA+AJD method is incorrectly identified, indicating that the DA+AJD method based on domain adaptation has better fault transfer diagnosis performance. ③ The t-SNE algorithm is used to visualize the processed source and target domain characteristic samples. The DA+AJD method only has a small number of rolling element fault and outer ring fault characteristic samples in the target domain that are incorrectly aligned to the inner ring fault characteristic samples area in the source domain. This result indicates that the DA+AJD method can effectively reduce the edge distribution and conditional distribution differences between the source domain and the target domain, and thus achieves better characteristic sample alignment.

Unpredicted variability in temperature is associated with frequent extreme low-temperature events. Wheat is a leading crop in fulfilling global food requirements. Climate-driven temperature extremes influence the vegetative and reproductive growth of wheat, followed by a decrease in yield. This review describes how low temperature induces a series of modifications in the morphophysiological, biochemical, and molecular makeup of wheat and how it is perceived. To cope with these modifications, crop plants turn on their cold-tolerance mechanisms, characterized by accumulating soluble carbohydrates, signaling molecules, and cold tolerance gene expressions. The review also discusses the integrated management approaches to enhance the performance of wheat plants against cold stress. In this review, we propose strategies for improving the adaptive capacity of wheat besides alleviating risks of cold anticipated with climate change.

In the context of global warming, low temperature (LT) disasters in major crops are also becoming more common. LT stress in the Huang-Huai-Hai Plain, the central wheat region in China, caused a massive reduction in wheat yields. A step towards ensuring wheat yield stability and food security, this study investigated the effects of optimizing phosphorus application on the root physiology, dry matter phosphorus accumulation, translocation, and partitioning of wheat under LT stress, using the representative cultivar Yannong 19 as the test material. The treatments included conventional phosphorus application (R1) and twice-split phosphorus application (R2), followed by −4 °C LT treatment and normal temperature (NT) treatment during the anther interval stage. Analysis of the root physiology (enzymatic activities and acid phosphatase, contents of malondialdehyde, soluble sugar, and soluble protein), phosphorus and dry matter accumulation, translocation, partitioning, and agronomic and yield-related components was carried during this research study. The results showed that the wheat root activity was significantly reduced and the antioxidant enzyme activities were increased to mitigate the damage of LT stress. Moreover, LT treatments damaged root function. The root activity and antioxidant properties were significantly lower than those of the NT treatment at the flowering stage. The dry matter and phosphorus accumulations were reduced by 30.6~33.6% and 15.1~21.3% at the flowering and maturity stages, resulting in final yield losses of 10.3~13.0%. In contrast, root activity increased by 16.1~27.2% in the twice-split phosphorus application treatments, and the root antioxidant characteristics were higher. As a result, dry matter and phosphorus accumulation increased after twice-split phosphorus application and their translocation to the grains was more; the final yield increased by 5.5~7.3%. Overall, the twice-split phosphorus application enhanced the physiological function of the root system and promoted the accumulation of nutrients and their transport to the grain, and alleviated the yield loss of wheat caused by LT stress. [ABSTRACT FROM AUTHOR]

As one of the most important wheat-producing areas in China, wheat is prone to heat stress during the grain filling period in the Huang-Huai-Hai Plain (3HP), which lowers yields and degrades the grain quality of wheat. To assess the effects of spraying potassium dihydrogen phosphate (KH2PO4) on the physiological traits in flag leaves and grain yield (GY) and quality under heat stress during the filling period, we conducted a two-year field experiment in the winter wheat growing seasons of 2020–2022. In this study, spraying water combined with heat stress (HT), 0.3% KH2PO4 (KDP), and 0.3% KH2PO4 combined with heat stress (PHT) were designed, and spraying water alone was used as a control (CK). The dates for the spraying were the third and eleventh day after anthesis, and a plastic film shed was used to impose heat stress on the wheat plants during the grain filling period. The results showed that spraying KH2PO4 significantly improved the chlorophyll content and net photosynthesis rate (Pn) in flag leaves compared with the non-sprayed treatments. Compared with CK, the Pn in HT decreased by 8.97% after heat stress, while Pn in PHT decreased by 7.44% compared to that of KDP. The activities of superoxide dismutase, catalase, and peroxidase in flag leaves were significantly reduced when the wheat was subjected to heat stress, while malonaldehyde content increased, and the enzyme activities were significantly enhanced when KH2PO4 was sprayed. Heat stress significantly decreased the contribution rate of dry matter accumulation (DM) after anthesis of wheat to grain (CRAA), whereas spraying KH2PO4 significantly increased the CRAA and harvest index. At maturity, the DM in CK was significantly higher than that in HT, KDP was significantly higher than PHT, and KDP had the highest DM. Compared with CK, the GY in KDP significantly increased by 9.85% over the two years, while the GY in HT decreased by 11.44% compared with that of CK, and the GY in PHT decreased by 6.31% compared to that of KDP. Spraying KH2PO4 after anthesis primarily helped GY by maintaining a high thousand grain weight to lessen the negative effects of heat stress on wheat. Moreover, heat stress significantly reduced protein concentration, wet gluten content, dough development time, and hardness index in grains of mature, while spraying KH2PO4 maintained a sufficient grain quality under the conditions of achieving higher yields. Overall, spraying KH2PO4 after anthesis could enhance the heat stress resistance of wheat and maintain the photosynthetic capacity of flag leaves, ensuring the dry matter production and reducing the negative effects on grain yield and quality in the 3HP. [ABSTRACT FROM AUTHOR]

In order to solve the problems of soaring costs and supply fluctuation in permanent magnet materials, this paper investigates and develops a magnetless wound field synchronous motor (WFSM) drive system for electric vehicle (EV) application. As the crucial drive component for EVs, the proposed WFSM in this paper has a two-stage structure which is described as the exciter and the main motor. The excitation characteristics of the exciter that provide power to the rotor field winding are emphatically analyzed. In addition, the discrete time domain armature current regulator and excitation current regulator are designed and analyzed for the high-performance WFSM drive system. A current coordinated control strategy for the full speed range is proposed to expand the constant power region. The experiment shows that the excitation characteristics and torque capability of the WFSM are consistent with the analysis, and proves that the WFSM is a potential solution for the magnetless motor for EV application. [ABSTRACT FROM AUTHOR]

Coronary heart disease (CHD) is defined by atherosclerosis, which may result in stenosis or blockage of the arterial cavity, leading to ischemic cardiac diseases such as angina and myocardial infarction (MI). Accumulating evidence indicates that the gut microbiota play a critical role in the initiation and progression of CHD. The gut microbial metabolite trimethylamine N‐oxide (TMAO) is intimately linked to the pathophysiology of CHD. The hepatic flavin‐containing monooxygenases (FMOs) convert trimethylamine (TMA) to TMAO. As a result, it is critical to prevent TMA generation. Stilbenes could reduce cardiovascular disease mortality. Twelve stilbenes with inhibitory activity against TMA‐lyase were compiled and evaluated in this study. Docking results showed Resveratroloside had the highest Vina score, indicating that it was the most active and might be employed as a lead molecule for further structural modification. [ABSTRACT FROM AUTHOR]

With the rapid development of computer vision, techniques of machine vision and visual inspection have been applied into the inspection of catenary on high-speed railways. Visual inspection systems have been developed and super-high-resolution images are captured to check the status of catenary components. Automatic recognition of defects becomes very important since the number of images is too huge to be manually checked one by one. However, it is not easy for the development of recognition algorithms on catenary components. There are many types of defects to be checked on different kinds of catenary components, but the number of defect images is too small in real world. In this paper, a solution was proposed and implemented. An on-site data acquisition system was designed and developed, and different types of defects were manually made on different catenary components beforehand. Finally, a visual inspection database was successfully constructed, including plenty of different kinds of catenary components, different types of defects, in different inspection conditions. The visual inspection database will be of great use in the development and test of recognition algorithms for catenary.