Aims
To perform an updated systematic review and meta‐analysis of postoperative delirium (POD) after transcatheter aortic valve replacement (TAVR).
Methods
We conducted a systematic literature search ...of PubMed, Embase, and Cochrane Library databases from the time of the first human TAVR procedure in 2002 until December 24, 2021, which was supplemented by manual searches of bibliographies. Data were collected on incidence rates, risk factors, and/or associated mortality of POD after TAVR. Pooled analyses were conducted using random effects models to yield mean differences, odds ratios, hazard ratios, and risk ratios, with 95% confidence intervals.
Results
A total of 70 articles (69 studies) comprising 413,389 patients were included. The study heterogeneity was substantial. The pooled mean incidence of POD after TAVR in all included studies was 9.8% (95% CI: 8.7%–11.0%), whereas that in studies using validated tools to assess for delirium at least once a day for at least 2 consecutive days after TAVR was 20.7% (95% CI: 17.8%–23.7%). According to the level of evidence and results of meta‐analysis, independent preoperative risk factors with a high level of evidence included increased age, male sex, prior stroke or transient ischemic attack, atrial fibrillation/flutter, weight loss, electrolyte abnormality, and impaired Instrumental Activities of Daily Living; intraoperative risk factors included non‐transfemoral access and general anesthesia; and acute kidney injury was a postoperative risk factor. POD after TAVR was associated with significantly increased mortality (pooled unadjusted RR: 2.20, 95% CI: 1.79–2.71; pooled adjusted RR: 1.62, 95% CI: 1.25–2.10), particularly long‐term mortality (pooled unadjusted HR: 2.84, 95% CI: 1.91–4.23; pooled adjusted HR: 1.88, 95% CI: 1.30–2.73).
Conclusions
POD after TAVR is common and is associated with an increased risk of mortality. Accurate identification of risk factors for POD after TAVR and implementation of preventive measures are critical to improve prognosis.
The effects of nitrogen ion implantation on the microstructures and the vibration fatigue properties of the 7075-T651 aluminum alloy were investigated. Nitrogen ions were implanted into 7075-T651 ...aluminum alloy by metal vapor vacuum arc (MEVVA) at the dose of 3 × 1017 ions/cm2 at room temperature. The trajectory distribution range and the introduced defects of nitrogen ion-implanted 7075-T651 aluminum alloy were simulated using the Stopping and Range of Ions in Matter software. The phase composition was tested by X-ray diffraction (XRD), the microstructures were characterized using a transmission electron microscope (TEM), and the fracture morphologies of vibration samples were observed using a scanning electron microscope (SEM). Experimental results indicate that the fatigue life of the ion-implanted vibration samples increased by 75% compared with the untreated samples. The ion implantation caused the microscopic strain，which increased the density of dislocation structure and reduced the grain size. The gradient microstructure and fracture properties of the sample were analyzed. The results show that the high-density dislocation and fine grains induced by ion implantation are beneficial to prolong the vibration fatigue life.
•Ion implantation enhances anti-vibration fatigue properties of 7075-T651 aluminum alloy.•The damage induced by ion implantation leads to high-density dislocations.•High-density dislocations and grain refinement are the main factors to prolong the vibration fatigue life.
Aiming at the problem that the composite fault signal of the gearbox is weak and the fault characteristics are difficult to extract under strong noise environment, an improved singular spectrum ...decomposition (ISSD) method is proposed to extract the composite fault characteristics of the gearbox. Singular spectrum decomposition (SSD) has been proved to have higher decomposition accuracy and can better suppress modal mixing and pseudo component. However, noise has a great influence on it, and it is difficult to extract weak impact components. In order to improve the limitations of SSD, we chose the minimum entropy deconvolution adjustment (MEDA) as the pre-filter of the SSD to preprocess the signal. The main function of the minimum entropy deconvolution adjustment is to reduce noise and enhance the impact component, which can make up for the limitations of SSD. However, the ability of MEDA to reduce noise and enhance the impact signal is greatly affected by its parameter, the filter length. Therefore, to improve the shortcomings of MEDA, a parameter adaptive method based on Cuckoo Search (CS) is proposed. First, construct the objective function as the adaptive function of CS to optimize the MEDA algorithm. Then, the pre-processed signal is decomposed into singular spectral components (SSC) by SSD, and the meaningful components are selected by Correlation coefficient. For the existing modal mixing phenomenon, the SSC component is reconstructed to eliminate the misjudgment of the result. Then, the frequency spectrum analysis is performed to obtain the frequency information for fault diagnosis. Finally, the effectiveness and superiority of ISSD are validated by simulation signals and applying to compound faults of a Gear box test rig.
In the era of big data, data-driven methods mainly based on deep learning have been widely used in the field of intelligent fault diagnosis. Traditional neural networks tend to be more subjective ...when classifying fault time-frequency graphs, such as pooling layer, and ignore the location relationship of features. The newly proposed neural network named capsules network takes into account the size and location of the image. Inspired by this, capsules network combined with the Xception module (XCN) is applied in intelligent fault diagnosis, so as to improve the classification accuracy of intelligent fault diagnosis. Firstly, the fault time-frequency graphs are obtained by wavelet time-frequency analysis. Then the time-frequency graphs data which are adjusted the pixel size are input into XCN for training. In order to accelerate the learning rate, the parameters which have bigger change are punished by cost function in the process of training. After the operation of dynamic routing, the length of the capsule is used to classify the types of faults and get the classification of loss. Then the longest capsule is used to reconstruct fault time-frequency graphs which are used to measure the reconstruction of loss. In order to determine the convergence condition, the three losses are combined through the weight coefficient. Finally, the proposed model and the traditional methods are, respectively, trained and tested under laboratory conditions and actual wind turbine gearbox conditions to verify the classification ability and reliable ability.
As a relatively novel density-based clustering algorithm, Density peak clustering (DPC) has been widely studied in recent years. DPC sorts all points in descending order of local density and finds ...neighbors for each point in turn to assign all points to the appropriate clusters. The algorithm is simple and effective but has some limitations in applicable scenarios. If the density difference between clusters is large or the data distribution is in a nested structure, the clustering effect of this algorithm is poor. This study incorporates the idea of connectivity into the original algorithm and proposes an improved density peak clustering algorithm ConDPC. ConDPC modifies the strategy of obtaining clustering center points and assigning neighbors and improves the clustering accuracy of the original density peak clustering algorithm. In this study, clustering comparison experiments were conducted on synthetic data sets and real-world data sets. The compared algorithms include original DPC, DBSCAN, K-means and two improved algorithms over DPC. The comparison results prove the effectiveness of ConDPC.
This study aimed to investigate the correlation between vaginal microbiota and pregnancy outcomes of women who achieved pregnancy
fertilization (IVF) in Northern China, and to determine a biomarker ...for evaluation of the risk of preterm births in these women.
In total, 19 women from Northern China women who conceived after IVF and 6 women who conceived naturally were recruited in this study. The vaginal samples of the healthy participants were collected throughout pregnancy, that is, during the first, second, and third trimesters. The V3-V4 region of 16S rRNA was used to analyze the vaginal microbiome, and the bioinformatic analysis was performed using QIIME Alpha and Beta diversity analysis.
Either IVF group or Natural conception group, bacterial community diversities and total species number of vagnal samples from who delivered at term were significantly higher than those who delivered before term. Low abundance of vaginal bacteria indicates an increased risk of preterm delivery. Further, more abundant vaginal bacteria was found in first trimesters instead of the next two trimesters. Vignal samples collected during first trimester showed richer differences and more predictive value for pregnancy outcoes. In addition, the diversity of the vaginal bacterial community decreased as the gestational age increased, in all samples.
was only found in participants who conceived after IVF, and the percentage of
in viginal samples of normal delivery group is much higher than the samples from preterm delivery group.
specifically colonized in vagina of pregnant woman in AFT group (those who conceived after IVF (A), first trimester (F), and delivered at term (T)) and
was detected only in women with AFT and AST (those who conceived after IVF (A), second trimester (S), and delivered at term (T)). These data indicates that
and
have great potential in predicting pregnancy outcomes who pregnanted by vitro fertilization.
Vaginal microbiota were more stable in women who conceived naturally and those who carried pregnancy to term.
might act as a positive biomarker, whereas
and
may act as negative biomarkers for the risk of preterm birth.
In industrial production, it is highly essential to extract faults in gearbox accurately. Specifically, in a strong noise environment, it is difficult to extract the fault features accurately. LMD ...(local mean decomposition) is widely used as an adaptive decomposition method in fault diagnosis. In order to improve the mode mixing of LMD, ELMD (ensemble Local Mean Decomposition) is proposed as local mode mixing exists in noisy environment, but white noise added in ELMD cannot be completely neutralized leading to the influence of increased white noise on PF (product function) component. This further leads to the increase in reconstruction errors. Therefore, this paper proposes a composite fault diagnosis method for gearboxes based on an improved ensemble local mean decomposition. The idea is to add white noise in pairs to optimize ELMD, defined as CELMD (Complementary Ensemble Local Mean Decomposition) then remove the decomposed high noise component by PE (Permutation Entropy) while applying the SG (Savitzky-Golay) filter to smooth out the low noise in PFs. The method is applied to both simulated signal and experimental signal, which overcomes mode mixing phenomenon and reduces reconstruction error. At the same time, this method avoids the occurrence of pseudocomponents and reduces the amount of calculation. Compared with LMD, ELMD, CELMD, and CELMDAN, it shows that improved ensemble local mean decomposition method is an effective method for extracting composite fault features.
In perovskite solar cells, the interfacial transfer of photogenerated electrons from the photoactive layers to TiO2 mesoporous layers is the key step that determines the power conversion efficiency ...and stability of the devices and is influenced by the contact condition. Although foreign element doping can facilitate the extraction of electrons from the perovskite layers, the increase in the number of electronic states on the surface of semiconductor scaffolds will undesirably aggravate the charge recombination. In this work, we manage to dedope the foreign element from the surface of Nb-doped TiO2 nanostructures via moderate temperature treatment. By doing this, the remaining lattice expansion of the dedoped surface can reduce the lattice mismatching between the anatase and the perovskite, therefore not only facilitating the electronic interaction but also alleviating the interfacial strain on temperature changes. Besides, the surface dedoping can also protect the cells from UV degradation by suppressing the survival of holes generated in the TiO2 skeleton.
To evaluate the safety and efficacy of low-intensity focused ultrasound (LIFU) therapy in facilitating fundus descent and relieving postpartum breast pain compared with sham treatment. A multicentre, ...randomised, sham-controlled, blinded trial was conducted. A cohort of 176 eligible participants, who had normal prenatal check-ups and met the inclusion and exclusion criteria, were recruited from three medical centres and subsequently randomized into either the LIFU or sham group. All participants received three treatment sessions, wherein LIFU signal was applied to the uterus and breast sites using coupling gel, with the absence of ultrasound signal output in the sham group. Fundal height measurement and breast pain score were performed after each treatment. The primary outcome, uterine involution, was presented by measuring the fundal height of the uterus. The visual analogue scale (VAS) score, as a secondary outcome, was used to assess breast pain and determine the correlation between breast pain and fundal height as the outcome simultaneously. All participants were randomly assigned to either the LIFU group (n = 88) or sham group (n = 88), with seven individuals not completing the treatment. Overall, a statistically significant difference was noted in the rate and index of fundus descent after each treatment. The rate and index of fundus descent showed greater significance following the second treatment (rate: 1.5 (1.0, 2.0) cm/d; index: 0.15 (0.1, 0.18), P < 0.001) and third treatment (rate: 1.67 (1.33, 2.0) cm/d; index: 0.26 (0.23, 0.3), P < 0.001) in the LIFU group. VAS scores, which were based on the continuous variables for the baseline, first, second, and third treatments in the LIFU group (2.0 (2.0, 3.0), 1.0 (0.0, 2.0), 0.0 (0.0, 1.0), and 0.0 (0.0, 0.0) points, respectively), and the sham group (2.0 (2.0, 2.0), 2.0 (1.0, 2.0), 2.0 (1.0, 3.0), and 3.0 (1.0, 3.0) points, respectively), showed a statistically significant difference between the two groups. Meanwhile, the discrepancies in VAS score classification variables between the two groups were statistically significant. After the third treatment, a notable correlation was observed between the VAS score decrease and fundus descent rate; the more the VAS score decreased, the faster was the fundal decline rate in the LIFU group. LIFU therapy is safe and effective, contributing to the acceleration of uterine involution and the relief of postpartum breast pain.Trial ID The study has registered in the Chinese Clinical Trial Registry (ChiCTR2100049586) at 05/08/2021.
Haptic actuators generate touch sensations and provide realism and depth in human–machine interactions. A new generation of soft haptic interfaces is desired to produce the distributed signals over ...large areas that are required to mimic natural touch interactions. One promising approach is to combine the advantages of organic actuator materials and additive printing technologies. This powerful combination can lead to devices that are ergonomic, readily customizable, and economical for researchers to explore potential benefits and create new haptic applications. Here, an overview of emerging organic actuator materials and digital printing technologies for fabricating haptic actuators is provided. In particular, the focus is on the challenges and potential solutions associated with integration of multi‐material actuators, with an eye toward improving the fidelity and robustness of the printing process. Then the progress in achieving compact, lightweight haptic actuators by using an open‐source extrusion printer to integrate different polymers and composites in freeform designs is reported. Two haptic interfaces—a tactile surface and a kinesthetic glove—are demonstrated to show that printing with organic materials is a versatile approach for rapid prototyping of various types of haptic devices.
An overview of emerging organic actuator materials and digital printing technologies for fabricating soft organic haptic actuators to emulate touch sensations is provided. In particular, the focus is on the challenges and potential solutions associated with integration of multi‐material actuators. The progress in achieving compact, lightweight haptic actuators by combining different polymers and composites in freeform designs is reported.
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