Fault diagnosis of electro-mechanical actuator based on WPD-STFT time-frequency entropy and PNN

Electro-mechanical actuators (EMAs) are increasingly being used as critical actuation devices of the aircraft. It will cause serious accidents once the fault of EMAs occurs, thus the fault diagnosis of EMAs is essential to maintain the normal operation of aircraft. In this paper, a method based on WPD-STFT time-frequency entropy and PNN is proposed to achieve fault diagnosis of EMAs by processing the vibration signals collected by the accelerometer installed in the EMAs. Firstly, the vibration signals are decomposed by wavelet packet to obtain the signal components of different frequency bands, the signal components are subjected to STFT and spectrograms are obtained. Then, time-frequency entropy is calculated and combined with principal component analysis (PCA) for dimension reduction as the feature vector. Finally, the probabilistic neural network (PNN) classifier is introduced to classify the fault modes. The experimental result shows that this method can accomplish the accurate fault diagnosis of EMAs. Moreover, the performance of the proposed WPD-STFT time-frequency entropy method has an advantage over that of WPD-PCA method or STFT combined with mass-moment entropy method for feature extraction

Weekend admissions and outcomes in patients with pneumonia: a systematic review and meta-analysis

BackgroundTo document pooled evidence on the association between weekend hospital admissions and the potential risks of mortality, intensive care requirements, and readmission among patients with pneumonia.MethodsWe performed a systematic search across the PubMed, EMBASE, and Scopus databases. We collected observational studies exploring the association between weekend admissions and outcomes of interest in patients with pneumonia. To analyze the data, we used a random effects model and expressed the effect sizes as pooled odds ratios (ORs) accompanied by their respective 95% confidence intervals (CIs).ResultsThe analysis comprised data from 13 retrospective studies. Compared to patients admitted on weekdays, those admitted during the weekend had a non-statistically significant marginally higher risk of in-hospital mortality (OR, 1.02; 95% CI, 1.00, 1.04) but similar 30-day mortality after admission (OR, 1.03; 95% CI, 0.97, 1.10), and similar risks of admission to intensive care unit (OR, 1.04; 95% CI, 0.98, 1.11) and re-admission (OR, 0.85; 95% CI, 0.65–1.12).ConclusionOur findings do not support the presence of a “weekend effect” in patients with pneumonia.Systematic review registrationPROSPERO, identifier CRD42023425802, https://www.crd.york.ac.uk/prospero/

Mental health and substance use in urban left-behind children in China: A growing problem

Children left behind by their migrant parents in urban and rural areas represent two vulnerable but distinct populations that have emerged due to the large-scale population migrations that occur within China. In 2015, there were an estimated 28 million urban left-behind children and around 41 million rural left-behind children. The purpose of this study was to examine the mental health status and substance use behaviors of urban left-behind children and urban children still living with their parents in comparison to rural left-behind children. This study also sought to investigate how parent-adolescent communication and children's resilience may moderate or exacerbate mental health status and/or substance use across children experiencing different forms of parental migration and hukou status (household registration system), using cross-sectional data from a school-based questionnaire survey with a sample of 4565 children living in both urban and rural counties of Anhui province. Regression model results suggest that, compared to urban children who lived with both parents, urban children who were currently left-behind appeared to exhibit higher mental health difficulties (emotional symptoms and total difficulties) and more substance use (smoking and drinking). Urban left-behind children were also found to experience more mental health problems and substance use than rural left-behind children. Our results indicated that both parent-adolescent communication and resilience were strongly associated with children's mental health and substance use outcomes. These findings have significance for the creation and tailoring of interventions directed at urban left-behind children

A Wohlfahrtiimonas chitiniclastica with a novel type of blaVEB–1-carrying plasmid isolated from a zebra in China

BackgroundWohlfahrtiimonas chitiniclastica is an emerging fly-borne zoonotic pathogen, which causes infections in immunocompromised patients and some animals. Herein, we reported a W. chitiniclastica BM-Y from a dead zebra in China.MethodsThe complete genome sequencing of BM-Y showed that this isolate carried one chromosome and one novel type of blaVEB–1-carrying plasmid. Detailed genetic dissection was applied to this plasmid to display the genetic environment of blaVEB–1.ResultsThree novel insertion sequence (IS) elements, namely ISWoch1, ISWoch2, and ISWoch3, were found in this plasmid. aadB, aacA1, and gcuG were located downstream of blaVEB–1, composing a gene cassette array blaVEB–1–aadB–aacA1–gcuG bracketed by an intact ISWoch1 and a truncated one, which was named the blaVEB–1 region. The 5′-RACE experiments revealed that the transcription start site of the blaVEB–1 region was located in the intact ISWoch1 and this IS provided a strong promoter for the blaVEB–1 region.ConclusionThe spread of the blaVEB–1-carrying plasmid might enhance the ability of W. chitiniclastica to survive under drug selection pressure and aggravate the difficulty in treating infections caused by blaVEB–1-carrying W. chitiniclastica. To the best of our knowledge, this is the first report of the genetic characterization of a novel blaVEB–1-carrying plasmid with new ISs from W. chitiniclastica

Epigenetic regulation of programmed cell death in hypoxia-induced pulmonary arterial hypertension

Pulmonary arterial hypertension (PAH) is a severe progressive disease that may cause early right ventricular failure and eventual cardiac failure. The pathogenesis of PAH involves endothelial dysfunction, aberrant proliferation of pulmonary artery smooth muscle cells (PASMCs), and vascular fibrosis. Hypoxia has been shown to induce elevated secretion of vascular endothelial growth factor (VEGF), leading to the development of hypoxic PAH. However, the molecular mechanisms underlying hypoxic PAH remain incompletely understood. Programmed cell death (PCD) is a natural cell death and regulated by certain genes. Emerging evidence suggests that apoptotic resistance contributes to the development of PAH. Moreover, several novel types of PCD, such as autophagy, pyroptosis, and ferroptosis, have been reported to be involved in the development of PAH. Additionally, multiple diverse epigenetic mechanisms including RNA methylation, DNA methylation, histone modification, and the non-coding RNA molecule-mediated processes have been strongly linked to the development of PAH. These epigenetic modifications affect the expression of genes, which produce important changes in cellular biological processes, including PCD. Consequently, a better understanding of the PCD processes and epigenetic modification involved in PAH will provide novel, specific therapeutic strategies for diagnosis and treatment. In this review, we aim to discuss recent advances in epigenetic mechanisms and elucidate the role of epigenetic modifications in regulating PCD in hypoxia-induced PAH

Deep learning assisted diagnosis system: improving the diagnostic accuracy of distal radius fractures

ObjectivesTo explore an intelligent detection technology based on deep learning algorithms to assist the clinical diagnosis of distal radius fractures (DRFs), and further compare it with human performance to verify the feasibility of this method.MethodsA total of 3,240 patients (fracture: n = 1,620, normal: n = 1,620) were included in this study, with a total of 3,276 wrist joint anteroposterior (AP) X-ray films (1,639 fractured, 1,637 normal) and 3,260 wrist joint lateral X-ray films (1,623 fractured, 1,637 normal). We divided the patients into training set, validation set and test set in a ratio of 7:1.5:1.5. The deep learning models were developed using the data from the training and validation sets, and then their effectiveness were evaluated using the data from the test set. Evaluate the diagnostic performance of deep learning models using receiver operating characteristic (ROC) curves and area under the curve (AUC), accuracy, sensitivity, and specificity, and compare them with medical professionals.ResultsThe deep learning ensemble model had excellent accuracy (97.03%), sensitivity (95.70%), and specificity (98.37%) in detecting DRFs. Among them, the accuracy of the AP view was 97.75%, the sensitivity 97.13%, and the specificity 98.37%; the accuracy of the lateral view was 96.32%, the sensitivity 94.26%, and the specificity 98.37%. When the wrist joint is counted, the accuracy was 97.55%, the sensitivity 98.36%, and the specificity 96.73%. In terms of these variables, the performance of the ensemble model is superior to that of both the orthopedic attending physician group and the radiology attending physician group.ConclusionThis deep learning ensemble model has excellent performance in detecting DRFs on plain X-ray films. Using this artificial intelligence model as a second expert to assist clinical diagnosis is expected to improve the accuracy of diagnosing DRFs and enhance clinical work efficiency

A clinical Pseudomonas juntendi strain with blaIMP−1 carried by an integrative and conjugative element in China

ObjectiveTo precisely determine the species of a carbapenem-resistant Pseudomonas strain 1809276 isolated from the urine of a Chinese patient and analyze its integrative and conjugative element (ICE) 1276 formation mechanism.MethodsSingle-molecule real-time (SMRT) sequencing was carried out on strain 18091276 to obtain the complete chromosome and plasmid (pCN1276) sequences, and average nucleotide identity (ANI) was used for precise species identification. The ICEs in GenBank with the same integrase structure as ICE 1276 were aligned. At the same time, the transfer ability of blaIMP−1 and the antibiotic sensitivity of Pseudomonas juntendi 18091276 were tested.ResultsThis bacterium was P. juntendi, and its drug resistance mechanism is the capture of the accA4' gene cassette by the Tn402-like type 1 integron (IntI1-blaIMP−1) to form In1886 before its capture by the ΔTn4662a-carrying ICE 1276. The acquisition of blaIMP−1 confers carbapenem resistance to P. juntendi 18091276.ConclusionThe formation of blaIMP−1-carrying ICE 1276, its further integration into the chromosomes, and transposition and recombination of other elements promote bacterial gene accumulation and transmission

Inclusion/Exclusion Behaviors of Small Molecules during Crystallization of Polymers in Miscible PLLA/TAIC Blend

In this work, PLLA/TAIC has been taken as a model system to investigate the inclusion and exclusion of small molecules during the crystallization of polymers in their miscible blend. Our results indicate that it is the growth rate and diameter of PLLA spherulites that dominate the localization of TAIC. On the one hand, crystallization temperature plays an important role. Crystallization at higher temperature corresponds to higher growth rates and a greater diameter of PLLA spherulites. The former improves the ability of PLLA crystals to trap TAIC while the latter leads to a lower volume fraction of space among neighboring PLLA spherulites. The combination of the two contributes to the enhanced inclusion behaviors. On the other hand, when compared to melt crystallization, cold crystallization results in much smaller spherulites (from higher nucleation density) and sufficient space among spherulites, which accounts for the enrichment of TAIC in interspherulitic regions and for its enhanced exclusion. In the adopted polymer–small molecule blend, TAIC can enrich in interspherulitic regions even in its miscible blend with PLLA, which can be attributed to its stronger diffusion ability

Quantifying urban expansion and its driving forces in Chengdu, western China

Understanding urban sprawl and its drivers is crucial for sustainable urban development. Most studies on Chinese urbanization have focused on coastal areas, paying little attention to urban centers in western China. This study examines urban expansion based on the Google Earth Engine (GEE), remotely sensed image, urban expansion model, and analysis of buffer and quadrant location in the Geographic Information System (GIS). Additionally, driving forces of urban expansion are examined based on the principle component analysis (PCA). Results indicate that urban land area increased more than 5.60 times, reaching 124,723 ha, an increase of over 400 % during 1990–2020. The urban expansion rate and intensity significantly increased and exhibited spatio-temporal heterogeneity. We identified that urban spatial expansion patterns changed from patch filling to patch border expansion, and urban expansion direction was mainly in the southern, northeastern, southwestern, and northwestern regions, extending along the traffic corridor, ring road, and adjacent cities. We suggest that economic development, population, and urbanization have become the driving factors of urban expansion. The GEE provides a new geographic processing algorithm based on massive image datasets, facilitating remote sensing processing. The results revealed that Chengdu is following trends witnessed in coastal cities of China; however, the significance of various drivers of urban expansion in these cities differs from that of the eastern cities. This study will help formulate policies for better urban land management and sustainable land development