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To address the problem that the faults in axial piston pumps are complex and difficult to effectively diagnose, an integrated hydraulic pump fault diagnosis method based on the modified ensemble empirical mode decomposition (MEEMD), autoregressive (AR) spectrum energy, and wavelet kernel extreme learning machine (WKELM) methods is presented in this paper. First, the non-linear and non-stationary hydraulic pump vibration signals are decomposed into several intrinsic mode function (IMF) components by the MEEMD method. Next, AR spectrum analysis is performed for each IMF component, in order to extract the AR spectrum energy of each component as fault characteristics. Then, a hydraulic pump fault diagnosis model based on WKELM is built, in order to extract the features and diagnose faults of hydraulic pump vibration signals, for which the recognition accuracy reached 100%. Finally, the fault diagnosis effect of the hydraulic pump fault diagnosis method proposed in this paper is compared with BP neural network, support vector machine (SVM), and extreme learning machine (ELM) methods. The hydraulic pump fault diagnosis method presented in this paper can diagnose faults of single slipper wear, single slipper loosing and center spring wear type with 100% accuracy, and the fault diagnosis time is only 0.002 s. The results demonstrate that the integrated hydraulic pump fault diagnosis method based on MEEMD, AR spectrum, and WKELM methods has higher fault recognition accuracy and faster speed than existing alternatives.The diagnostics of prostate cancer are currently based on three pillars prostate biomarker panel, imaging techniques, and histological verification. This paper presents a diagnostic algorithm that can serve as a “road map” from initial patient stratification to the final decision regarding treatment. The algorithm is based on a review of the current literature combined with our own experience. Diagnostic algorithms are a feature of an advanced healthcare system in which all steps are consciously coordinated and optimized to ensure the proper individualization of the treatment process. The prostate cancer diagnostic algorithm was created using the prostate specific antigen and in particular the Prostate Health Index in the first line of patient stratification. It then continued on the diagnostic pathway via imaging techniques, biopsy, or active surveillance, and then on to the treatment decision itself. In conclusion, the prostate cancer diagnostic algorithm presented here is a functional tool for initial patient stratification, comprehensive staging, and aggressiveness assessment. Above all, emphasis is placed on the use of the Prostate Health Index (PHI) in the first stratification of the patients as a predictor of aggressiveness and clinical stage of prostrate cancer (PCa). The inclusion of PHI in the algorithm significantly increases the accuracy and speed of the diagnostic procedure and allows to choose the optimal pathway just from the beginning. The use of advanced diagnostic techniques allows us to move towards to a more advanced level of cancer care. This diagnostics algorithm has become a standard of care in our hospital. The algorithm is continuously validated and modified based on our results.Vegetables of the Allium genus are prone to infection by Fusarium fungi. Chitinases of the GH19 family are pathogenesis-related proteins inhibiting fungal growth through the hydrolysis of cell wall chitin; however, the information on garlic (Allium sativum L.) chitinases is limited. In the present study, we identified seven class I chitinase genes, AsCHI1-7, in the A. sativum cv. Ershuizao genome, which may have a conserved function in the garlic defense against Fusarium attack. The AsCHI1-7 promoters contained jasmonic acid-, salicylic acid-, gibberellins-, abscisic acid-, auxin-, ethylene-, and stress-responsive elements associated with defense against pathogens. The expression of AsCHI2, AsCHI3, and AsCHI7 genes was constitutive in Fusarium-resistant and -susceptible garlic cultivars and was mostly induced at the early stage of F. proliferatum infection. In roots, AsCHI2 and AsCHI3 mRNA levels were increased in the susceptible and decreased in the resistant cultivar, whereas in cloves, AsCHI7 and AsCHI5 expression was decreased in the susceptible but increased in the resistant plants, suggesting that these genes are involved in the garlic response to Fusarium proliferatum attack. Our results provide insights into the role of chitinases in garlic and may be useful for breeding programs to increase the resistance of Allium crops to Fusarium infections.This cross-sectional study aimed to determine the use of neuroenhancers, the motivations and factors associated with their use in French and Romanian university students. Students from two universities in France (Rouen and Opal Coast University) and one in Romania (Cluj-Napoca) were asked to complete a self-administered anonymous questionnaire, either online or on paper, about the use of three different categories of substance Prescription drugs (methylphenidate, modafinil, and beta-blockers), drugs of abuse (alcohol, cannabis, cocaine, and amphetamines), and soft enhancers (coffee, vitamins, caffeine tablets, and energy drinks). In total, 1110 students were included The users were 2.2% for prescription drugs, 4.3% for drugs of abuse, and 55.0% for soft enhancers. Students used neuroenhancement to stay awake for study (69.3%), to improve concentration (55.5%), to decrease stress (40.9%), and to improve memory (39.6%). Neuroenhancement was considered to meet expectations by 74.4% of users. CMC-Na cell line The factors associated with the use of drugs of abuse were frequent binge drinking (Adjusted Odds Ratio-AOR 6.49 [95% CI 2.53-16.6]), smoking (AOR 5.50 [95% CI 2.98-10.14]), having a student job (AOR 2.42 [95% CI 1.13-5.17]), and being male (AOR 2.23 [95% CI1.21-4.11]). No significant associations with eating disorders were detected for any of the three categories of substances. University students reported neuroenhancement with prescription drugs, drugs of abuse, and mainly soft enhancers. These substances were used mainly to increase the waking hours. Educational programs in universities seem to be required in order to increase student awareness of the problems caused by neuroenhancements, and to decrease the associated risks by changing students’ attitudes and beliefs.