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Abstract Background This study aimed to identify the risk factors of acute ischemic stroke (AIS) occurring during hospitalization in patients following off-pump coronary artery bypass grafting (OPCABG) and utilize Bayesian network (BN) methods to establish predictive models for this disease. Methods Data were collected from the electronic health records of adult patients who underwent OPCABG at Beijing Anzhen Hospital from January 2018 to December 2022. Patients were allocated to the training and test sets in an 8:2 ratio according to the principle of randomness. Subsequently, a BN model was established using the training dataset and validated against the testing dataset. The BN model was developed using a tabu search algorithm. Finally, receiver operating characteristic (ROC) and calibration curves were plotted to assess the extent of disparity in predictive performance between the BN and logistic models. Results A total of 10,184 patients (mean (SD) age, 62.45 (8.7) years; 2524 (24.7%) females) were enrolled, including 151 (1.5%) with AIS and 10,033 (98.5%) without AIS. Female sex, history of ischemic stroke, severe carotid artery stenosis, high glycated albumin (GA) levels, high D-dimer levels, high erythrocyte distribution width (RDW), and high blood urea nitrogen (BUN) levels were strongly associated with AIS. Type 2 diabetes mellitus (T2DM) was indirectly linked to AIS through GA and BUN. The BN models exhibited superior performance to logistic regression in both the training and testing sets, achieving accuracies of 72.64% and 71.48%, area under the curve (AUC) of 0.899 (95% confidence interval (CI), 0.876–0.921) and 0.852 (95% CI, 0.769–0.935), sensitivities of 91.87% and 89.29%, and specificities of 72.35% and 71.24% (using the optimal cut-off), respectively. Conclusion Female gender, IS history, carotid stenosis (> 70%), RDW-CV, GA, D-dimer, BUN, and T2DM are potential predictors of IS in our Chinese cohort. The BN model demonstrated greater efficiency than the logistic regression model. Hence, employing BN models could be conducive to the early diagnosis and prevention of AIS after OPCABG.

Abstract Background Phytophthora sojae, a soil-borne oomycete pathogen, has been a yield limiting factor for more than 60 years on soybean. The resurgence of P. sojae (Phytophthora sojae) is primarily ascribed to the durable oospores found in soil and remnants of the disease. P. sojae is capable of infesting at any growth periods of the soybean, and the succeed infestation of P. sojae is predominantly attributed to long-lived oospores present in soil. Comprehending the molecular mechanisms that drive oospores formation and their significance in infestation is the key for effective management of the disease. However, the existing challenges in isolating and extracting significant quantities of oospores pose limitations in investigating the sexual reproductive stages of P. sojae. Results The study focused on optimizing and refining the culture conditions and extraction process of P. sojae, resulting in establishment of an efficient and the dependable method for extraction. Novel optimized approach was yielded greater quantities of high-purity P. sojae oospores than traditional methods. The novel approach exceeds the traditional approaches with respect to viability, survival ability, germination rates of new oospores and the pathogenicity of oospores in potting experiments. Conclusion The proposed method for extracting P. sojae oospores efficiently yielded a substantial quantity of highly pure, viable, and pathogenic oospores. The enhancements in oospores extraction techniques will promote the research on the sexual reproductive mechanisms of P. sojae and lead to the creation of innovative and effective approaches for managing oomycete diseases.

DNA-protein binding is crucial for the normal development and function of organisms. The significance of accurately identifying DNA-protein binding sites lies in its role in disease prevention and the development of innovative approaches to disease treatment. In the present study, we introduce a precise and robust identifier for DNA-protein binding residues. In the context of protein representation, we combine the evolutionary information of the protein, represented by its position-specific scoring matrix, with the spatial information of the protein's secondary structure, enriching the overall informational content. This approach initially employs a combination of Bi-directional Long Short-Term Memory and Transformer encoder to jointly extract the interdependencies among residues within the protein sequence. Subsequently, convolutional operations are applied to the resulting feature matrix to capture local features of the residues. Experimental results on the benchmark dataset demonstrate that our method exhibits a higher level of competitiveness when compared to contemporary classifiers. Specifically, our method achieved an MCC of 0.349, SP of 96.50%, SN of 44.03% and ACC of 94.59% on the PDNA-41 dataset.

This paper examines the impact of psychological factors on consumer purchase intention for electric vehicles (EVs) through the lens of Self-Determination Theory (SDT). By integrating the three dimensions of autonomy, relatedness, and competence, this study addresses a research gap in consumer innovative consumption, offering a deeper understanding of green transportation. The research reveals that psychological factors significantly influence innovative consumption and the purchase intention of EVs, aligning with the existing literature. In sustainable transportation, psychological factors such as motivation, attitude, and inner activities increasingly drive purchase decisions. This study examines the direct and indirect effects of psychological factors on purchase intention by employing Partial Least Squares Structural Equation Modeling (PLS-SEM) and Necessary Condition Analysis (NCA). It also considers the moderating role of driving experience in the relationship between psychological factors and innovative consumption. This combined data analysis approach provides a comprehensive understanding of the mechanisms influencing purchase intention, highlighting the intricate interplay between psychological determinants and consumer behavior in the adoption of electric vehicles.

Abstract Gray mold is a destructive disease caused by Botrytis cinerea, a pervasive plant pathogen, which poses a threat to both tomato growth and postharvest storage. The utilization of induced resistance presents a potential strategy for combating plant pathogenic attacks. ZNC (zhinengcong), an extract derived from the endophytic fungus Paecilomyces variotii, has been discovered to play a vital role in preventing diverse forms of bacterial infections. Nevertheless, the precise mechanism behind its ability to enhance tomato resistance to fungi remains unclear. In this study, we found that the exogenous spraying of ZNC could significantly improve the resistance of tomato plants to B. cinerea. The results of both the metabolomic analysis and high-performance liquid chromatography (HPLC) demonstrated that tomato plants responded to ZNC treatment by accumulating high levels of rutin. Additional transcriptome analysis uncovered that rutin enhances tomato resistance possible by initiating the generation of reactive oxygen species (ROS) and phosphorylation of mitogen-activated protein kinases (MPKs) related genes expression during the initial phase of invasion by B. cinerea. In addition, we also found that rutin might activate plant immunity by eliciting ethylene (ET) and jasmonic acid (JA)-mediated pathways. Therefore, plant immune inducer ZNC and rutin has bright application prospects and high utilization value to control gray mold. Graphical Abstract

Human activities are causing frequent and drastic changes in land use and land cover, which have had important impacts on ecology and the environment. Assessing land use changes is an accurate and valuable approach to assessing the effect of these activities on ecosystem health. Pakistan is currently experiencing ecological stress caused by agricultural development, urbanization, and uncontrolled deforestation. This study examined the spatiotemporal variation of land use and land cover in Pakistan at a resolution of 30 m and evaluated the ecosystem health in the country from 2010 to 2020 using the Vigor–Organization–Resilience–Services framework at a precision of 500 m. Results indicate that the construction land area in Pakistan increased by 4,084.92 km2, and water body by 3,329.62 km2 between 2010 and 2020. The decrease in forest area was very significant in 2015 (by 5,625 km2), and this situation was brought under control by 2020. However, the regions with an ecosystem health index above 0.8 decreased by 61%, primarily in Islamabad. The spatial clustering of the Ecosystem Health Index in Pakistan became more evident, with Moran’s I increasing from 0.834 in 2010 to 0.871 in 2020. Based on these findings, this study recommends that Pakistan establishes a national ecosystem health management system to monitor significant changes in land use and land cover. Furthermore, it emphasizes the need for increased investment in green development to promote sustainable regional development.

Abstract Background To explore the characteristics of retina microvascular changes in patients with diabetic nephropathy (DN) and its risk factors. Methods Retrospective, observational study. 145 patients with type 2 diabetic mellitus (DM) and DN were included in the study. Demographic and clinical parameters were obtained from medical records. Presence of diabetic retinopathy (DR), hard exudates (HEs) and diabetic macular edema (DME) were evaluated according to the color fundus images, optical coherence tomography (OCT) and fluorescence angiography (FFA). Results DR accounted for 61.4% in type 2 DM patients with DN, of which proliferative diabetic retinopathy (PDR) accounted for 23.6% and sight threatening DR accounted for 35.7%. DR group had significantly higher levels of low-density lipoprotein cholesterol (LDL-C) (p = 0.004), HbA1c (P = 0.037), Urine albumin creatine ratio (ACR) (p

This study aims to expand the current understanding of the antecedents and consequences of green purchase intention within the context of perceived green value (PGV). This study uniquely combines PLS-SEM and NCA to provide a comprehensive analysis of the factors influencing green purchase intention, offering a novel methodological contribution to the field. By examining the roles of influence and interaction as key precursors to perceived responsibility and self-efficacy, the research adds new dimensions to understanding how these factors shape green purchase intentions. Additionally, we explore how PER and PSE impact green purchase intention (GPI), primarily through their mediating effects. The survey data collected from consumers reveal that PGV positively influences GPI. Furthermore, both PER and PSE exhibit significant chain mediation effects, with the mediation effect of perceived environmental responsibility being particularly strong. This study provides actionable insights for policymakers and electric vehicle manufacturers, emphasizing the importance of green education, certification systems, and the promotion of environmental and economic attributes to foster green purchasing behavior. The findings suggest that government efforts should focus on intensifying green education and promoting the establishment of certification and evaluation systems for electric vehicle products. Meanwhile, electric vehicle manufacturers should highlight the environmental and economic benefits of their products to stimulate green purchasing behavior.

Abstract Background By 2050, the world population will increase to 10 billion which urged global demand for food production to double. Plant disease and land drought will make the situation more dire, and safer and environment-friendly materials are thus considered as a new countermeasure. The rice blast fungus, Magnaporthe oryzae, causes one of the most destructive diseases of cultivated rice worldwide that seriously threatens rice production. Unfortunately, traditional breeding nor chemical approaches along control it well. Nowadays, nanotechnology stands as a new weapon against these mounting challenges and silica nanoparticles (SiO2 NPs) have been considered as potential new safer agrochemicals recently but the systematically studies remain limited, especially in rice. Results Salicylic acid (SA) is a key plant hormone essential for establishing plant resistance to several pathogens and its further affected a special form of induced resistance, the systemic acquired resistance (SAR), which considered as an important aspect of plant innate immunity from the locally induced disease resistance to the whole plant. Here we showed that SiO2 NPs could stimulate plant immunity to protect rice against M. oryzae through foliar treatment that significantly decreased disease severity by nearly 70% within an appropriate concentration range. Excessive concentration of foliar treatment led to disordered intake and abnormal SA responsive genes expressions which weaken the plant resistance and even aggravated the disease. Importantly, this SA-dependent fungal resistance could achieve better results with root treatment through a SAR manner with no phytotoxicity since the orderly and moderate absorption. What’s more, root treatment with SiO2 NPs could also promote root development which was better to deal with drought. Conclusions Taken together, our findings not only revealed SiO2 NPs as a potential effective and safe strategy to protect rice against biotic and abiotic stresses, but also identify root treatment for the appropriate application method since it seems not causing negative effects and even have promotion on root development. Graphical Abstract

Measurement(s) atmospheric carbon dioxide concentrations Technology Type(s) satellite observations • spatial statistical analysis

Mucor hiemalis BO-1 is an entomopathogenic fungus that infects Bradysia odoriphaga, a destructive root maggot. M. hiemalis BO-1 possesses stronger pathogenicity to the larvae than to other stages of B. odoriphaga, and provides satisfactory field control. However, the physiological response of B. odoriphaga larvae to infection and the infection mechanism of M. hiemalis are unknown. We detected some physiological indicators of diseased B. odoriphaga larvae infected by M. hiemalis BO-1. These included changes in consumption, nutrient contents, and digestive and antioxidant enzymes. We performed transcriptome analysis of diseased B. odoriphaga larvae, and found that M. hiemalis BO-1 showed acute toxicity to B. odoriphaga larvae and was as toxic as some chemical pesticides. The food consumption of diseased B. odoriphaga after inoculation with M. hiemalis spores decreased significantly, and there was a significant decrease in total protein, lipid, and carbohydrates in diseased larvae. Key digestive enzymes (protease, α-amylase, lipase, and cellulase) were significantly inhibited during infection. Peroxidase maintained high activity, and the activity of other antioxidant enzymes (catalase, superoxide dismutase, and glutathione S-transferases) first increased and then decreased. Combined with the transcriptional signatures of diseased B. odoriphaga larvae, M. hiemalis BO-1 infection resulted in decreased food consumption, reduced digestive enzyme activity, and altered energy metabolism and material accumulation. Infection was also accompanied by fluctuations in immune function, such as cytochrome P450 and the Toll pathway. Therefore, our results laid a basis for the further study of the interactions between M. hiemalis BO-1 and B. odoriphaga and promoted the genetic improvement of entomopathogenic fungi.

Spodoptera frugiperda is an agricultural pest causing substantial damage and losses to commercial crops. Sex pheromones are critical for successful mating in Lepidoptera and have been used for monitoring and control of many pest species. The sex pheromone of S. frugiperda is known, but the genes involved in its biosynthesis have not been identified. We systematically studied 99 candidate sex pheromone genes in the genome of S. frugiperda including 1 acetyl-CoA carboxylase (ACC), 11 fatty acid synthases (FASs), 17 desaturases (DESs), 4 fatty acid transport proteins (FATPs), 29 fatty acyl-CoA reductases (FARs), 17 acetyl-CoA acetyltransferases (ACTs), 5 acyl-CoA dehydrogenase (ACDs), 3 enoyl-CoA hydratases (ECHs), 3 hydroxyacyl-CoA dehydrogenases (HCDs), 6 ethyl-CoA thiolases (KCTs), and 3 acyl-CoA-binding proteins (ACBPs). Based on the comparative transcriptome results, we found 22 candidate sex pheromone biosynthesis genes predominately expressed in pheromone glands (PGs) than abdomens without PGs including SfruFAS4, SfruFATP3, SfruACD5, SfruKCT3, SfruDES2, SfruDES5, SfruDES11, SfruDES13, SfruFAR1, SfruFAR2, SfruFAR3, SfruFAR6, SfruFAR7, SfruFAR8, SfruFAR9, SfruFAR10, SfruFAR11, SfruFAR14, SfruFAR16, SfruFAR29, SfruACT6, and SfruACT10. A combination of phylogenetic and tissue-specific transcriptomic analyses indicated that SfruDES5, SfruDES11, SfruFAR2, SfruFAR3, and SfruFAR9 may be key genes involved in the sex pheromone synthesis of S. frugiperda. Our results could provide a theoretical basis for understanding the molecular mechanisms of sex pheromone biosynthesis in S. frugiperda, and also provide new targets for developing novel pest control methods based on disrupting sexual communication.

Abstract Extreme precipitation over drylands, especially deserts, has been observed, whereas the precipitation changes in Chinese deserts have been rarely studied. Here, we used a daily grid precipitation data set generated via weather station data (0.25° horizontal grid spacing) to investigate the spatial and temporal changes in extreme precipitation in Chinese deserts. Extreme precipitation based on the changes in the total precipitation (PRCPTOT) and the annual maximum daily precipitation (Rx1day) in the Chinese desert exhibited markedly increasing trends and presented a spatial distribution of wetting in the western deserts and drying in the eastern deserts. The increase in extreme precipitation could minimize wind erosion and intensify dune stabilization in the western Chinese deserts.

MnO2–CuO–Fe2O3/CNTs catalysts, as a low-dimensional material, were fabricated by a mild redox strategy and used in denitration reactions. A formation mechanism of the catalysts was proposed. NO conversions of 4% MnO2–CuO–Fe2O3/CNTs catalyst of 43.1–87.9% at 80–180 °C were achieved, which was ascribed to the generation of amorphous MnO2, CuO and Fe2O3, and a high surface-oxygen (Os) content.

Bemisia tabaci Middle East-Asia Minor 1 (MEAM1) is a cosmopolitan, highly polyphagous agricultural pest, which has the capacity to displace other native insect herbivores. Here, equipped with an integrated approach, the effect of developmental stages and feeding density of whiteflies on Myzus persicae performance in tobacco plants are investigated. Bioassay results showed that B. tabaci nymphs, but not adult, pre-infestation significantly reduced survival and fecundity of M. persicae, and the strongest resistance to M. persicae was detected at the medium density (9–10 nymphs/cm2). Neither low nor high feeding density of B. tabaci nymphs triggered visible resistance to aphids. However, no significant results were detected in salicylate-deficient NahG plants after B. tabaci nymph infestation. In addition to performance distinctions, hormone quantification and qPCR results revealed very different effects for nymph and adult whitefly stages on the defense responses in tobacco. B. tabaci nymph infestation significantly increased SA accumulation and SA-responsive genes (PR-1a, PR-2a) expression but suppressed JA-regulated responses. In contrast, tobacco plants responded to adult infestation by slightly increasing in both SA- and JA-regulated defenses. Furthermore, higher transcription level of Bt56, coding gene of a secretory salivary effector, was recorded in nymphs vs. adults, while silencing of Bt56 by virus-induced gene silencing (VIGS) partly impaired the aphid resistance induced by B. tabaci nymphs. These results proved that the induction of tobacco defense responses varied with the feeding stages of whiteflies: nymphs of B. tabaci, but not adults, induced a defense response against aphids, with a density threshold for this induced resistance.

The intimate relationships between plants and insects start with herbivory, which can be traced back to approximately 420 million year ago. Like many other relationships, a plant–insect interaction can be mutualistic, commensalistic, or antagonistic. Within antagonistic relationships, plants deploy inducible defense to insect phytophagy. Insects, however, can evade/suppress effectual plant defenses by manipulating plant defense signaling. Previously, we showed that the sweet potato whitefly, Bemisia tabaci, a global invasive insect pest, can suppress jasmonic acid (JA)-dependent defenses, thereby enhancing their performance on host plants. Given that nitric oxide (NO), a multifunctional signaling molecule, interacts closely with JA signaling pathway, we hypothesized that NO is involved in the suppression of JA defensive responses. Equipped with an integrated approach, we comprehensively examined this overarching hypothesis. We showed that: (1) tobacco plants responded to B. tabaci infestation by accumulating high levels of NO, (2) the exogenous application of sodium nitroprusside, a NO donor, in tobacco plants attracted B. tabaci adults and accelerated nymphal development, whereas plants treated with 2-(4-carboxyphenyl)-4,4,5,5-tetramethylimidazoline-1-oxyl-3-oxide (cPTIO), a NO scavenger, repelled B. tabaci adults and prolonged nymphal development, and, more importantly, (3) silencing of NO-associated protein 1, a gene associated with NO accumulation, and cPTIO application disrupted the B. tabaci-mediated suppression of JA in plants. Collectively, these results suggest that: (1) NO signaling is activated by B. tabaci infestation, (2) NO is involved in the suppression of JA-dependent plant defense, and, consequently, (3) NO improves B. tabaci performance on host plants. Our study reflects the remarkable arm race that co-evolved for millions of years between plants and insects and offers a potential novel target (nitric oxide) for the long-term sustainable management of this global invasive pest.

Tomato is an economically crucial vegetable/fruit crop globally. Tomato is rich in nutrition and plays an essential role in a healthy human diet. Phenylpropanoid, a critical compound in tomatoes, reduces common degenerative and chronic diseases risk caused by oxidative stress. As an MYB transcription factor, ATMYB12 can increase phenylpropanoid content by activating phenylpropanoid synthesis related genes, such as PAL, C4H, 4CL, CHS. However, the heterologous expression of AtMYB12 in tomatoes can be altered through transgenic technologies, such as unstable expression vectors and promoters with different efficiency. In the current study, the efficiency of other fruit-specific promoters, namely E8S, 2A12, E4, and PG, were compared and screened, and we determined that the expression efficiency of AtMYB12 was driven by the E8S promoter was the highest. As a result, the expression of phenylpropanoid synthesis related genes was regulated by AtMYB12, and the phenylpropanoid accumulation in transgenic tomato fruits increased 16 times. Additionally, the total antioxidant capacity of fruits was measured through Trolox equivalent antioxidant capacity (TEAC) assay, which was increased by 2.4 times in E8S transgenic lines. TEAC was positively correlated with phenylpropanoid content. Since phenylpropanoid plays a crucial role in the human diet, expressing AtMYB12 with stable and effective fruit-specific promoter E8S could improve tomato’s phenylpropanoid and nutrition content and quality. Our results can provide genetic resources for the subsequent improvement of tomato varieties and quality, which is significant for human health.

A new species of brown frog Rana luanchuanensis Zhao & Yuan, sp. n. is described from Luanchuan County, western Henan, central China. The mitochondrial genealogy suggests that the new species is the sister taxon to the clade including R. amurensis and R. coreana, and is separated by uncorrected pairwise distances more than 12.5%. Morphologically, this new species differs from its congeners by a suite of characters. Analyses of partial sequences of cytochrome oxidase subunit I (COI) resolve the new species as a single matriline.

Abstract Garlic, a widely cultivated global vegetable crop, is threatened by the underground pest Bradysia odoriphaga in China. Previous reports indicated that garlic essential oil, of which the dominant components are sulfides or thiosulfinates, exhibits insecticidal activity against pests. However, it is unclear whether the resistance of garlic to B. odoriphaga is related to thiosulfinates. Here, we compared the resistance of 10 garlic cultivars at various growth stages to B. odoriphaga by field investigation and indoor life-table data collection. Furthermore, the relationship between thiosulfinates content and resistance, as well as the toxicity of garlic oil and allicin against B. odoriphaga larvae was determined. Field surveys demonstrated that the garlic cultivars Qixian and Cangshan possessed the highest resistance, while Siliuban and Yishui were the most sensitive. When reared on Qixian, B. odoriphaga larval survival and fecundity declined by 26.2% and 17.7% respectively, but the development time was prolonged by 2.8 d compared with Siliuban. A positive correlation was detected between thiosulfinates content and resistance. Furthermore, garlic oil and allicin exhibited strong insecticidal activity. We screened out 2 pest-resistant cultivars, for which thiosulfinate content was highest. Additionally, the insecticidal activity displayed by sulfides and allcin suggests their potential for exploitation as botanical insecticides.

Timely and accurate fault location for a 35-kVhigh-reliability distribution network is one of the key technologies to improve the safety and efficiency of distribution network operations. A novel fault location method of 35-kV high-reliability distribution network is proposed in this paper. First, the distributed multipoint fault location model is established based on the power structure of a 35-kV high-reliability distribution network. The distribution of voltage and current traveling waves along the lines is comprehensively considered in this model. Secondly, we analyze the influence of noise interference, analog-digital conversion frequency, and conversion bits on the location accuracy. The simulation method of noise and analog-digital conversion is proposed based on simulated samples. Then, a wavelet filter is used to reduce the influence of noise on the calibration of the traveling wave arrival time, and matrix modulus of S transform is used to identify the arrival time for the wave. Finally, the simulation model of a 35-kV high-reliability distribution network is established to analyze the location accuracy in the case of single-phase to ground via resistance, two-phase short-circuit to ground via resistance, and three-phase short-circuit faults. The simulation results indicate that the proposed method has high location accuracy under the above fault conditions.

Embedded and mobile smart devices face problems related to limited computing power and excessive power consumption. To address these problems, we propose Mixed YOLOv3-LITE, a lightweight real-time object detection network that can be used with non-graphics processing unit (GPU) and mobile devices. Based on YOLO-LITE as the backbone network, Mixed YOLOv3-LITE supplements residual block (ResBlocks) and parallel high-to-low resolution subnetworks, fully utilizes shallow network characteristics while increasing network depth, and uses a “shallow and narrow” convolution layer to build a detector, thereby achieving an optimal balance between detection precision and speed when used with non-GPU based computers and portable terminal devices. The experimental results obtained in this study reveal that the size of the proposed Mixed YOLOv3-LITE network model is 20.5 MB, which is 91.70%, 38.07%, and 74.25% smaller than YOLOv3, tiny-YOLOv3, and SlimYOLOv3-spp3-50, respectively. The mean average precision (mAP) achieved using the PASCAL VOC 2007 dataset is 48.25%, which is 14.48% higher than that of YOLO-LITE. When the VisDrone 2018-Det dataset is used, the mAP achieved with the Mixed YOLOv3-LITE network model is 28.50%, which is 18.50% and 2.70% higher than tiny-YOLOv3 and SlimYOLOv3-spp3-50, respectively. The results prove that Mixed YOLOv3-LITE can achieve higher efficiency and better performance on mobile terminals and other devices.

Diesel engines, as power equipment, are widely used in the fields of the automobile industry, ship industry, and power equipment. Due to wear or faulty adjustment, the valve train clearance abnormal fault is a typical failure of diesel engines, which may result in the performance degradation, even valve fracture and cylinder hit fault. However, the failure mechanism features mainly in the time domain and angular domain, on which the current diagnosis methods are based, are easily affected by working conditions or are hard to extract accurate enough from, as the diesel engine keeps running in transient and non-stationary processes. This work aimed at diagnosing this fault mainly based on frequency band features, which would change when the valve clearance fault occurs. For the purpose of extracting a series of frequency band features adaptively, a decomposition technique based on improved variational mode decomposition was investigated in this work. As the connection between the features and the fault was fuzzy, the random forest algorithm was used to analyze the correspondence between features and faults. In addition, the feature dimension was reduced to improve the operation efficiency according to importance score. The experimental results under variable speed condition showed that the method based on variational mode decomposition and random forest was capable to detect the valve clearance fault effectively.

Diesel engine fault diagnosis is vital due to enhanced reliability and economic efficiency requirements. The extracted features in traditional fault diagnosis are constructed manually, which is very cumbersome because of the requirement for lots of expertise. To handle this issue, this paper proposed a variational stacked autoencoder (VSAE) to adaptively extract features from angular domain signals. As an unsupervised algorithm, VSAE can extract high-level features with the help of multiple encoding layers. Layer-wise pre-training and fine-tuning are introduced to get a better network initialization value. Moreover, the dropout technique and the batch normalization technique are carried out to prevent over-fitting and implement fast convergence. Finally, the harmony search optimizer (HSO) algorithm is introduced to get an appropriate hyper-parameter setting in the VSAE model, as well as make adaptive adjustment of the network structure. In order to verify the proposed method, the valve train fault data is collected on the diesel engine test rig under twelve operating conditions. The results indicate that the proposed scheme can effectively diagnose different degrees of intake valve fault, exhaust valve fault, and coupling fault under various operating conditions. Furthermore, the classification accuracy improved from 94.10% to 98.85%VSAE compared with stacked autoencoder (SAE) and some other traditional fault diagnosis algorithms.

The diesel engine has been a significant component of large-scale mechanical systems for the intelligent manufacturing industry. Because of its complex structure and poor working environment, it has trouble effectively acquiring the representative fault features. Further, fault diagnosis of the diesel engine faces great challenges. This paper presents a new fault diagnosis method for the detection of diesel engine faults under multiple operation conditions instead of conventional methods confined to a single condition. First, an adaptive correlation threshold process is designed as a preprocessing unit to enhance data quality by weakening non-impact region characteristics. Next, a feature extraction method for sound signals based on the Mel frequency cepstrum (MFC) is improved and introduced into the machinery fault diagnosis. Then, the combination of the improved feature and vibrational mode decomposition (VMD) is proposed to incorporate VMD into an effective adaptive decomposition of non-stationary signals to combine it with an excellent feature representation of the vibration signal. Finally, the vector quantization algorithm is adopted to reduce the feature dimensions and generate codebook model bases, which trains the K-Nearest Neighbor classifiers. Five comparative methods were carried out, and the experimental results show that the proposed method offers a good effect of the common valve clearance fault of diesel engines under different conditions.

Bemisia tabaci MEAM1 (Middle East-Asia Minor 1) feeding alters antioxidative enzyme activity in some plant species. Infestation of B. tabaci nymphs decreases Myzus persicae performance on systemic, but not local leaves of tobacco plants. However, it is unclear if B. tabaci nymphs induced antioxidant activities contributing to the aphid resistance.We investigated the relationship between antioxidants induced by nymphs of B. tabaci feeding on tobacco and aphid resistance. The activities of catalase (CAT), peroxidase (POD), superoxide dismutase (SOD) and the concentration of hydrogen peroxide (H2O2) were assayed in tobacco leaves at different feeding times following infestation of B. tabaci nymphs. The infestation altered the activities of CAT and POD, but had no significant effect on SOD activity. The highest CAT activity was observed at 15 d after infestation. This was 98.2% greater than control systemic leaves, but 32.6% lower than the control in local leaves. Higher POD activity was recorded in local vs. systemic leaves after 15 d of infestation. POD activity was 71.0% and 112.9% higher in local and systemic leaves, respectively, than in the controls. The changes of CAT, but not POD or SOD activity were correlated to levels of aphid resistance. H2O2 levels were higher in local than in systemic leaves in contrast to CAT activity. Tobacco curly shoot virus mediated virus-induced gene silencing was employed to determine if CAT activation was involved in the aphid resistance induced by B. tabaci nymphs. B. tabaci induced CAT activity decreased when the Cat1 expression was silenced. The performance assay indicated that Cat1 silencing made B. tabaci infested plants a more suitable host for aphids than infested control plants. The aphid survival rate was reduced by 40.4% in infested control plants, but reduced by only 26.1% in Cat1-silenced plants compared to uninfested controls. Also, qPCR results showed that silencing of Cat1 led to the suppression of the B. tabaci mediated PR-2a expression.Aphid resistance in plants infested with B. tabaci nymphs is associated with enhanced antioxidant activities in which CAT may play a dominant role. This resistance probably acted via interactions with SA-mediated defense responses.

The feeding of Bemisia tabaci nymphs trigger the SA pathway in some plant species. A previous study showed that B. tabaci nymphs induced defense against aphids (Myzus persicae) in tobacco. However, the mechanism underlying this defense response is not well understood.Here, the effect of activating the SA signaling pathway in tobacco plants through B. tabaci nymph infestation on subsequent M. persicae colonization is investigated. Performance assays showed that B. tabaci nymphs pre-infestation significantly reduced M. persicae survival and fecundity systemically in wild-type (WT) but not salicylate-deficient (NahG) plants compared with respective control. However, pre-infestation had no obvious local effects on subsequent M. persicae in either WT or NahG tobacco. SA quantification results indicated that the highest accumulation of SA was induced by B. tabaci nymphs in WT plants after 15 days of infestation. These levels were 8.45- and 6.14-fold higher in the local and systemic leaves, respectively, than in controls. Meanwhile, no significant changes of SA levels were detected in NahG plants. Further, biochemical analysis of defense enzymes polyphenol oxidase (PPO), peroxidase (POD), β-1,3-glucanase, and chitinase demonstrated that B. tabaci nymph infestation increased these enzymes' activity locally and systemically in WT plants, and there was more chitinase and β-1, 3-glucanase activity systemically than locally, which was opposite to the changing trends of PPO. However, B. tabaci nymph infestation caused no obvious increase in enzyme activity in any NahG plants except POD.In conclusion, these results underscore the important role that induction of the SA signaling pathway by B. tabaci nymphs plays in defeating aphids. It also indicates that the activity of β-1, 3-glucanase and chitinase may be positively correlated with resistance to aphids.

Identifying and protecting hotspots of endemism and species richness is crucial for mitigating the global biodiversity crisis. However, our understanding of spatial diversity patterns is far from complete, which severely limits our ability to conserve biodiversity hotspots. Here, we report a comprehensive analysis of amphibian species diversity in China, one of the most species-rich countries on Earth. Our study combines 20 y of field surveys with new molecular analyses of 521 described species and also identifies 100 potential cryptic species. We identify 10 hotspots of amphibian diversity in China, each with exceptional species richness and endemism and with exceptional phylogenetic diversity and phylogenetic endemism (based on a new time-calibrated, species-level phylogeny for Chinese amphibians). These 10 hotspots encompass 59.6% of China's described amphibian species, 49.0% of cryptic species, and 55.6% of species endemic to China. Only four of these 10 hotspots correspond to previously recognized biodiversity hotspots. The six new hotspots include the Nanling Mountains and other mountain ranges in South China. Among the 186 species in the six new hotspots, only 9.7% are well covered by protected areas and most (88.2%) are exposed to high human impacts. Five of the six new hotspots are under very high human pressure and are in urgent need of protection. We also find that patterns of richness in cryptic species are significantly related to those in described species but are not identical. [ABSTRACT FROM AUTHOR]