Variation of sugar compounds in Phoebe chekiangensis seeds during natural desiccation.

To investigate the role of sugar metabolism in desiccation-sensitive seeds, we performed a natural desiccation treatment on Phoebe chekiangensis seeds in a room and systematically analyzed the changes in seed germination, sugar compounds, malondialdehyde, and relative electrical conductivity during the seed desiccation. The results revealed that the initial moisture content of P. chekiangensis seed was very high (37.06%) and the seed was sensitive to desiccation, the germination percentage of the seed decreased to 5.33% when the seed was desiccated to 22.04% of moisture content, therefore, the seeds were considered recalcitrant. Based on the logistic model, we know that the moisture content of the seeds is 29.05% when the germination percentage drops to 50% and that it is desirable to keep the seed moisture content above 31.74% during ambient transportation. During seed desiccation, sucrose and trehalose contents exhibited increasing trends, and raffinose also increased during the late stage of desiccation, however, low levels of the non-reducing sugar accumulations may not prevent the loss of seed viability caused by desiccation. Glucose and fructose predominated among sugar compounds, and they showed a slight increase followed by a significant decrease. Their depletion may have contributed to the accumulation of sucrose and raffinose family oligosaccharides. Correlation analysis revealed a significant relationship between the accumulation of sucrose, trehalose, and soluble sugars, and the reduction in seed viability. Sucrose showed a significant negative correlation with glucose and fructose. Trehalose also exhibited the same pattern of correlation. These results provided additional data and theoretical support for understanding the mechanism of sugar metabolism in seed desiccation sensitivity.

Thrombotic events and prophylactic anticoagulation in pediatric patients with COVID-19: a systematic review and meta-analysis.

BACKGROUND: Venous thromboembolism (VTE) can occur in children with COVID-19, and the efficacy and safety of prophylactic anticoagulant therapy are uncertain. This study aimed to assess the incidence of VTE in pediatric patients with COVID-19, the association of D-dimer with thrombus formation, and the effectiveness and safety of prophylactic anticoagulation treatment. METHODS: We systematically searched databases from January 2020 to February 2023. A systematic review and meta-analysis were conducted to determine the incidence of VTE in children and evaluate the efficacy and safety of prophylactic anticoagulant therapy. RESULTS: Thirteen cohort studies and one clinical trial were included. The pooled incidence rate of VTE in affected children was 1.5% (95% CI 0.4-2.9%). Children with D-dimer levels five times higher than normal had a higher risk of VTE (OR 4.92, 95% CI 1.60-15.11). Prophylactic anticoagulant therapy did not significantly reduce the risk of VTE (OR 1.35, 95% CI 0.74-2.49). The safety of prophylactic anticoagulant therapy was relatively high, with major bleeding and all-cause mortality rates below 0.1% (95% CI 0.0-0.2%). CONCLUSIONS: The incidence of VTE in children with COVID-19 is low, and prophylaxis based on ISTH standards is reasonable. Low-molecular-weight heparin (LMWH) for VTE prevention has a high level of safety. However, more high-quality studies are needed to understand the impact of anticoagulant therapy on VTE incidence in pediatric patients with COVID-19.

Fault Diagnosis for Rolling Bearing of Combine Harvester Based on Composite-Scale-Variable Dispersion Entropy and Self-Optimization Variational Mode Decomposition Algorithm.

Because of the influence of harsh and variable working environments, the vibration signals of rolling bearings for combine harvesters usually show obvious characteristics of strong non-stationarity and nonlinearity. Accomplishing accurate fault diagnosis using these signals for rolling bearings is a challenging subject. In this paper, a novel fault diagnosis method based on composite-scale-variable dispersion entropy (CSvDE) and self-optimization variational mode decomposition (SoVMD) is proposed, systematically combining the nonstationary signal analysis approach and machine learning technology. Firstly, an improved SoVMD algorithm is developed to realize adaptive parameter optimization and to further extract multiscale frequency components from original signals. Subsequently, a CSvDE-based feature learning model is established to generate the multiscale fault feature space (MsFFS) of frequency components for the improvement of fault feature learning ability. Finally, the generated MsFFS can serve as the inputs of the Softmax classifier for fault category identification. Extensive experiments on the vibration datasets collected from rolling bearings of combine harvesters are conducted, and the experimental results demonstrate the more superior and robust fault diagnosis performance of the proposed method compared to other existing approaches.

Source Free Semi-Supervised Transfer Learning for Diagnosis of Mental Disorders on fMRI Scans.

The high prevalence of mental disorders gradually poses a huge pressure on the public healthcare services. Deep learning-based computer-aided diagnosis (CAD) has emerged to relieve the tension in healthcare institutions by detecting abnormal neuroimaging-derived phenotypes. However, training deep learning models relies on sufficient annotated datasets, which can be costly and laborious. Semi-supervised learning (SSL) and transfer learning (TL) can mitigate this challenge by leveraging unlabeled data within the same institution and advantageous information from source domain, respectively. This work is the first attempt to propose an effective semi-supervised transfer learning (SSTL) framework dubbed S3TL for CAD of mental disorders on fMRI data. Within S3TL, a secure cross-domain feature alignment method is developed to generate target-related source model in SSL. Subsequently, we propose an enhanced dual-stage pseudo-labeling approach to assign pseudo-labels for unlabeled samples in target domain. Finally, an advantageous knowledge transfer method is conducted to improve the generalization capability of the target model. Comprehensive experimental results demonstrate that S3TL achieves competitive accuracies of 69.14%, 69.65%, and 72.62% on ABIDE-I, ABIDE-II, and ADHD-200 datasets, respectively. Furthermore, the simulation experiments also demonstrate the application potential of S3TL through model interpretation analysis and federated learning extension.

Roles of autophagy-related genes in the therapeutic effects of Xuanfei Pingchuan capsules on chronic obstructive pulmonary disease based on transcriptome sequencing analysis.

Objective: Autophagy plays an important role in the occurrence and development of chronic obstructive pulmonary disease (COPD). We evaluated the effect of Xuanfei Pingchuan capsule (XFPC) on autophagy-related genes of COPD by a bioinformatics analysis and experimental verification. Methods: The best treatment duration was screened by CCK8 assays. HBE cells were divided into three groups: blank, CSE and XFPC. After intervened by XFPC, HBE cells were collected and sent to Shenzhen Huada Gene Company for transcriptome sequencing. Subsequently, differential expression analyses, target gene prediction, and function enrichment analyses were carried out. Expression changes were verified in HBE cells by real-time Quantitative PCR (RT-qPCR) and western blotting (WB). Results: The result of differential expression analysis displayed that 125 target genes of HBE cells were mainly related to mitogen-activated protein kinase (MKK) binding, interleukin 33 binding, 1-Pyrroline-5-carboxylate dehydrogenase activity, and the mitogen-activated protein kinase (MAPK) signal pathway. Among the target genes, the core genes related to autophagy obtained by maximum neighborhood component algorithm were CSF1, AREG, MAPK9, MAP3K7, and AKT3. RT-qPCR and WB methods were used to verify the result, it showed similar expression changes in CSF1, MAPK9, MAP3K7, and AKT3 in bronchial epithelial cells to those in the bioinformatics analysis. Conclusion: Through transcriptome sequencing and validation analysis, we predicted that CSF1, MAPK9, MAP3K7, and AKT3 may be the potential autophagy-related genes that play an important role in the pathogenesis of COPD. XFPC may regulate autophagy by down-regulating the expression of CSF1, MAPK9, MAP3K7, and AKT3, thus achieving the purpose of treating chronic obstructive pulmonary disease.

Safety and efficacy of glucocorticoids in the treatment of COVID-19: A meta-analysis of randomized control trials.

BACKGROUND: It is unclear the efficacy and safety of glucocorticoids compared with placebo or usual care for treatment of COVID-19. RESEARCH DESIGN AND METHODS: Randomized controlled trials (RCTs) of corticosteroids in COVID-19 patients from 1 December 2019, to 30 June 2022, were assessed using Cochrane bias risk assessment method and improved Jadad score scale. GRADEpro was used to rate the quality of evidence for outcomes. RESULTS: Fifteen RCTs were included, including 10,620 patients. Glucocorticoid treatment for severe and critical COVID-19 showed lesser all-cause mortality (OR = 0.85, 95% CI [0.76, 0.94], P = 0.002) than conventional treatment. However, for mildly ill patients, neither inhaled drugs nor intravenous drugs reduced mortality (OR = 0.64, 95% CI [0.24, 1.76], P = 0.39). Glucocorticoids had no significant effect on the adverse reactions of patients (OR = 1.18, 95% CI [0.77, 1.80], P = 0.44) compared with usual care/placebo. Subgroup analysis demonstrated that dexamethasone significantly reduced the mortality of COVID-19 patients. Low-dose glucocorticoids were also associated with lower all-cause mortality. CONCLUSION: Glucocorticoids (especially dexamethasone) reduce mortality of patients with severe and critical COVID-19 with no significant effect on the incidence of adverse reactions (moderate quality). In contrast, glucocorticoids do not benefit patients with mild symptoms (low quality).

Efficacy of statin therapy in chronic obstructive pulmonary disease: a systematic review and meta-analysis from 2008-2019.

INTRODUCTION: Statins produce significant hypolipidemic effects and reduce C-reactive protein (CRP) in patients with chronic obstructive pulmonary disease (COPD). It has been reported that statins did not prevent the acute exacerbation of COPD or improve clinical outcomes. Therefore, we analyzed the actual therapeutic effects of statins on COPD therapy during long-term clinical trials. EVIDENCE ACQUISITION: Relevant studies were retrieved from various databases from 2008 to 2019. For each study, Odds Ratios (ORs), mean difference (MD) and 95% confidence interval (95% CI) were assessed. EVIDENCE SYNTHESIS: Thirty-two studies were retrieved with 3137 patients receiving statin therapy and 3140 controls. Satins significantly increased exercise capacity (47.21, 95% CI: 20.79-73.63), lung FEV1 (4.02, 95% CI: 2.28-5.75), forced expiratory volume in 1 s/forced vital capacity (FEV1/FVC) (3.56, 95% CI: 2.01-5.10) and high-density lipoproteins (HDL) (5.573, 95% CI: 1.74-9.41). In addition, statins downregulated CRP function (W=-1.60, 95% CI: -2.45-0.76), IL-6 (-3.35, 95% CI: -4.94 to -1.76), St George's breath questionnaire (SGRQ) scores (-9.96, 95% CI: -12.83 to -7.10), COPD assessment test (CAT) (-3.49, 95% CI: -4.70 to 2.29) and systolic blood pressure (-4.992, 95% CI: -5.17 to -4.818). Total cholesterol (TC) (-37.84, 95% CI: -46.10 to 29.58) low-density lipoproteins (LDL) (-26.601, 95% CI: -26.688 to 26.514) and triglycerides (TG) (-42.914, 95% CI: -61.809 to 24.02) were also decreased. CONCLUSIONS: Clinical trials conducted over a 10-year period revealed beneficial advantages of statin therapy in COPD patients, permitting increased exercise capacity, FEV1/FVC and HDL. In addition, CRP, IL-6, systolic blood pressure, SGRQ scores and CAT were significantly decreased as well as lipid levels.

Federated Multi-Task Learning for Joint Diagnosis of Multiple Mental Disorders on MRI Scans.

OBJECTIVE: Deep learning (DL) techniques have been introduced to assist doctors in the interpretation of medical images by detecting image-derived phenotype abnormality. Yet the privacy-preserving policy of medical images disables the effective training of DL model using sufficiently large datasets. As a decentralized computing paradigm to address this issue, federated learning (FL) allows the training process to occur in individual institutions with local datasets, and then aggregates the resultant weights without risk of privacy leakage. METHODS: We propose an effective federated multi-task learning (MTL) framework to jointly identify multiple related mental disorders based on functional magnetic resonance imaging data. A federated contrastive learning-based feature extractor is developed to extract high-level features across client models. To ease the optimization conflicts of updating shared parameters in MTL, we present a federated multi-gate mixture of expert classifier for the joint classification. The proposed framework also provides practical modules, including personalized model learning, privacy protection, and federated biomarker interpretation. RESULTS: On real-world datasets, the proposed framework achieves robust diagnosis accuracies of 69.48 ± 1.6%, 71.44 ± 3.2%, and 83.29 ± 3.2% in autism spectrum disorder, attention deficit/hyperactivity disorder, and schizophrenia, respectively. CONCLUSION: The proposed framework can effectively ease the domain shift between clients via federated MTL. SIGNIFICANCE: The current work provides insights into exploiting the advantageous knowledge shared in related mental disorders for improving the generalization capability of computer-aided detection approaches.

Different Sedation Strategies in Older Patients Receiving Spinal Anesthesia for Hip Surgery on Postoperative Delirium: A Randomized Clinical Trial.

Background: Postoperative delirium (POD) is of great concern as a complication of surgery in older adult patients. Sedation strategies influence the development of POD. This study compared how sedation strategies administered during spinal anesthesia influenced POD in patients aged ≥65 years undergoing elective surgery for hip fracture repair. Patients and Methods: A randomized clinical trial was conducted from 1 August 2021 to 30 June 2022 at a single academic medical center. Two hundred and twenty-six patients were randomly divided into four groups: lighter sedation with propofol (LP), heavier sedation with propofol (HP), lighter sedation with dexmedetomidine (LD), and heavier sedation with dexmedetomidine (HD). The incidence of delirium was the primary outcome and was assessed daily by the blinded Confusion Assessment Method. Results: There was a significant association between dexmedetomidine (LD+HD group) and a lower incidence of delirium (11.9% [13/109] vs the propofol group (23.6% [26/110]; Risk ratio, 0.51; 95% CI, 0.274 to 0.929; p=0.024). In the propofol group, heavier sedation had a higher rate of POD (32.7% [18/55] vs the lighter sedation group (14.5% [8/55]; Risk ratio, 2.25; 95% CI, 1.069 to 4.736; p=0.025). Conclusion: Dexmedetomidine was associated with a lower incidence of delirium than that with propofol among older patients with hip fractures. In patients that received propofol, heavier sedation was associated with high incidence of POD.

Identification of Guiboutia species by NIR-HSI spectroscopy.

Near infrared hyperspectral imaging (NIR-HSI) spectroscopy can be a rapid, precise, low-cost and non-destructive way for wood identification. In this study, samples of five Guiboutia species were analyzed by means of NIR-HSI. Partial least squares discriminant analysis (PLS-DA) and support vector machine (SVM) were used after different data treatment in order to improve the performance of models. Transverse, radial, and tangential section were analyzed separately to select the best sample section for wood identification. The results obtained demonstrated that NIR-HSI combined with successive projections algorithm (SPA) and SVM can achieve high prediction accuracy and low computing cost. Pre-processing methods of SNV and Normalize can increase the prediction accuracy slightly, however, high modelling accuracy can still be achieved by raw pre-processing. Both models for the classification of G. conjugate, G. ehie and G. demeusei perform nearly 100% accuracy. Prediction for G. coleosperma and G. tessmannii were more difficult when using PLS-DA model. It is evidently clear from the findings that the transverse section of wood is more suitable for wood identification. NIR-HSI spectroscopy technique has great potential for Guiboutia species analysis.

Single-molecule magnet behaviour in a centrosymmetric dinuclear dysprosium(III) complex: sequential differentiation of triple relaxation pathways.

A dinuclear complex with the formula Dy2L2(H2L)Cl2(EtOH)2 (Dy2) has been synthesized by reacting DyCl3·H2O with a ligand H2L (H2L = N,N'-ethylenebis(salicylideneimine)) using ethanol as the solvent. Its crystal structure can be viewed as a dimer of two Dy(III) fragments, where each Dy(III) site shows a N2O6Cl coordination sphere with a pentagonal bipyramid geometry (D5h). Magnetic measurements reveal that Dy2 behaves as a single-ion magnet (SIM) under a zero field. When the field is applied, the ac magnetic susceptibilities show double and triple peaks under high (≥600 Oe) and low (<600 Oe) dc fields, respectively. In contrast to the common double relaxation pathways in SIMs, such multiple and intricate relaxation pathways have not been reported yet in the previous literature. In this work, by experimental analysis of the ac signals, we attribute the three slow relaxation pathways to quantum tunnelling of magnetization (QTM), intermolecular dipole-dipole interaction and spin reversal, respectively. In addition, ab initio calculations are used to elucidate the magnetic behaviours of Dy2. Overall, our work indicates that the interpretation of the relaxation process using double relaxation pathways is incomplete and difficult in previously reported literature.

Affine Transformation-Enhanced Multifactorial Optimization for Heterogeneous Problems.

Evolutionary multitasking (EMT) is a newly emerging research topic in the community of evolutionary computation, which aims to improve the convergence characteristic across multiple distinct optimization tasks simultaneously by triggering knowledge transfer among them. Unfortunately, most of the existing EMT algorithms are only capable of boosting the optimization performance for homogeneous problems which explicitly share the same (or similar) fitness landscapes. Seldom efforts have been devoted to generalize the EMT for solving heterogeneous problems. A few preliminary studies employ domain adaptation techniques to enhance the transferability between two distinct tasks. However, almost all of these methods encounter a severe issue which is the so-called degradation of intertask mapping. Keeping this in mind, a novel rank loss function for acquiring a superior intertask mapping is proposed in this article. In particular, with an evolutionary-path-based representation model for optimization instance, an analytical solution of affine transformation for bridging the gap between two distinct problems is mathematically derived from the proposed rank loss function. It is worth mentioning that the proposed mapping-based transferability enhancement technique can be seamlessly embedded into an EMT paradigm. Finally, the efficacy of our proposed method against several state-of-the-art EMTs is verified experimentally on a number of synthetic multitasking and many-tasking benchmark problems, as well as a practical case study.

Complete mitogenome of Treron sphenurus (Aves, Columbiformes): the first representative from the genus Treron, genomic comparisons and phylogenetic analysis of Columbidae.

The wedge-tailed green pigeon (Treron sphenurus) has a protective value in the evolution of the family Columbidae. In this study, the complete mitogenome of T. sphenurus from Baise City, China, which represents the first sequenced species of the genus Treron in Tribe Treronini, is reported. This was accomplished using PCR-based methods and a primer-walking sequencing strategy with genus-specific primers. The mitogenome was found to be 18,919 bp in length comprising 37 genes, including 13 protein-coding genes, two rRNA genes, 22 tRNA genes, and one control region. In terms of structure and composition, many similarities were found between the T. sphenurus and Hemiphaga novaeseelandiae (New Zealand pigeon) mitogenomes. This was further supported by phylogenetic analysis showing that T. sphenurus has a close evolutionary relationship with H. novaeseelandiae. The complete mitogenome of T. sphenurus reported here is expected to provide valuable molecular information for further studies on the phylogeny of the genus Treron and for analyses of the taxonomic status of the family Columbidae.

Xuanfei Pingchuan Capsules Ameliorate Autophagy in Human Bronchial Epithelial Cells by Inhibiting p38 Phosphorylation.

Background: This study aimed to investigate the protective effect of Xuanfei Pingchuan Capsules (XFPC) on autophagy and p38 phosphorylation in human bronchial epithelial (HBE) cells induced by cigarette smoke extract (CSE). Methods: HBE cells were divided into five groups: blank, CSE, low XFPC dose (XFPC-L), medium XFPC dose (XFPC-M), and high XFPC dose (XFPC-H). HBE cells were induced by CSE to establish a cell model for chronic obstructive pulmonary disease, and different doses of XFPC medicated serum were used to treat the cells. The Cell Counting Kit-8 was used to detect cell viability. Flow cytometry was used to detect cell apoptosis. Fluorescence microscopy and the expression level of microtubule-associated protein light chain 3 (LC3)-II in immunohistochemical method were used to observe autophagy in cells. Western blot was used to detect the protein expression level of p38, phospho-p38 (p-p38), LC3-I, LC3-II and Beclin 1. Real-time polymerase chain reaction was used to detect the expression of LC3-I, LC3-II and Beclin 1 on mRNA level. Results: Compared with the blank group, the cell viability of the CSE group was significantly decreased, and apoptosis and the level of autophagy in cells were significantly increased. The mRNA and protein expression of LC3-I, LC3-II, Beclin 1 and the protein level of p-p38 were significantly increased in the CSE-HBE cells. Compared to the CSE group, the different doses of XFPC medicated serum increased cell viability, decreased cell apoptosis, and inhibited mRNA and protein expression of LC3-I, LC3-II, Beclin 1 and protein level of p-p38. These results were especially observed in the group XFPC-H. After adding a p38 agonist, the therapeutic effect of XFPC on cell viability and autophagy was suppressed. Conclusion: XFPC significantly increased cell viability in a CSE-induced HBE cell model for chronic obstructive pulmonary disease through inhibiting the level of autophagy mediated by phosphorylation of p38.

The complete mitochondrial genome of Black Drongo Dicrurus macrocercus (Passeriformes, Dicruridae).

The Black Drongo (Dicrurus macrocercus) is an important beneficial bird widespread in China and other Asian countries. In this study, a complete mitochondrial genome of D. macrocercus has been obtained by polymerase chain reaction method for the first time. This circular molecule is 17,017 bp in length with A + T contents of 56.9% and contains 2 rRNA genes, 13 protein-coding genes, and 22 tRNA genes. Phylogenetic analysis shows that D. macrocercus is genetically closest to D. hottentottus.

Janus PtXO (X = S, Se) monolayers: the visible light driven water splitting photocatalysts with high carrier mobilities.

Triggered by the recent experimental synthesis of the Janus PtSSe monolayer, we use the first-principles calculations to predict two new Janus photocatalysts PtXO (X = S, Se), based on the systematic investigations of the structural stabilities, electronic structures, band alignments, catalytic activity and optical absorption. The two Janus structures are found to be mechanically, dynamically and thermodynamically stable, and have suitable band edge positions for the overall water splitting. Owing to the high electron mobility (up to 2164.95 cm2 V-1 s-1) and large disparity between the electron and hole mobilities, together with the indirect band gaps and the intrinsic dipole induced built-in electric fields, the photogenerated electrons/holes can be efficiently separated in PtXO. Moreover, the S/Se vacancy can effectively lower the free energy difference of the HER, making the catalytic reactions occur spontaneously under the potentials of photoexcited electrons and holes. Large optical absorption coefficients (105 cm-1) are also confirmed in the visible light range, and the biaxial tensile strain can further enhance the optical absorption while maintaining the capability of the overall water splitting. Our results not only propose two new Janus materials by demonstrating the possibility of experimental realization, but also indicate that PtXO are peculiar candidates for photocatalytic water splitting.

Reversible Switching of Single-Molecule Magnetic Behaviour by Desorption/Adsorption of Solvent Ligand in a New Dy(III)-Based Metal Organic Framework.

Two metal-organic frameworks (MOFs), [Dy(BDC)(NO3)(DMF)2] n (1, H2BDC = terephthalic acid) and [Dy(BDC)(NO3)] n (1a), were synthesized. The structures of MOFs 1 and 1a are easy to be reversibly transformed into each other by the desorption or adsorption of coordination solvent molecules. Accordingly, their magnetic properties can also be changed reversibly, which realizes our goals of manipulating on/off single-molecule magnet behaviour. MOF 1 behaves as a single-molecule magnet either with or without DC field. Contrarily, no slow magnetic relaxation was observed in 1a both under zero field and applied field.

Cylindrical Shell Vibration Gyroscope Excited and Detected by High-Temperature-Sintered Piezoelectric Ceramic Electrodes.

A cylindrical shell piezoelectric vibration gyroscope is a kind of Coriolis vibration gyroscope. Its core components are the cylindrical quartz resonator (CQR) and the piezoelectric ceramic electrodes (PCEs). In order to develop a high-precision Cylindrical shell piezoelectric vibration gyroscope, it is very important to reduce the influence of the PCEs and obtain a high-quality-factor CQR. To achieve this goal, a novel high-temperature sintering method is proposed to combine the CQR and the PCEs, and the corresponding sintered resonators are fabricated. After sintering, results of the acoustic excitation experiment and piezoelectric excitation experiment are tested, and the influence of the sintered PCEs on the CQR is determined. A complete gyroscope is obtained by vacuum packaging the sintered resonator. Through the open-loop and closed-loop tests, the performance parameters of gyroscope are obtained. The feasibility of the high-temperature sintering method is proved by experiments.

Study on the Magneto-Structural Correlation of a New Dinuclear Cobalt(II) Complex with Double µ-Phenoxo Bridges.

A new µ-phenoxo-bridged dinuclear cobalt(II) complex, [Co2(L)2(acac)2(H2O)] (1), has been synthesized by employing a new ligand, (4-methyl-2-formyl-6-(((2-trifluoromethyl)phenyl)methyliminomethyl) phenol) (HL). Structural analysis of complex 1 reveals that the geometry around cobalt centers is best described as a distorted octahedron and the distance of cobalt neighbors is 3.128(0) Å. The magnetic property studies indicate that complex 1 exhibits strong spin-orbit coupling effects and weak ferromagnetic coupling between two high-spin Co(II) centers linked by double µ-Ophenoxo bridges, with J = 1.87(2) cm-1. The studies show that not only the Co-O-Co angle affects the alignment of the cobalt spins but also the dihedral angle between the CoOCo plane and the phenyl plane plays an important role in the magnetic coupling in this [Co2O2] system. Thus, the small bridging angles (96.96(11) and 96.91(11)°) and the large dihedral angles between the CoOCo plane and the phenyl plane (63.0(1) and 30.6(1)°) induce intramolecular ferromagnetic exchange interaction in complex 1.

Fault Diagnosis of Rolling Element Bearings with a Two-Step Scheme Based on Permutation Entropy and Random Forests.

This study presents a two-step fault diagnosis scheme combined with statistical classification and random forests-based classification for rolling element bearings. Considering the inequality of features sensitivity in different diagnosis steps, the proposed method utilizes permutation entropy and variational mode decomposition to depict vibration signals under single scale and multiscale. In the first step, the permutation entropy features on the single scale of original signals are extracted and the statistical classification model based on Chebyshev's inequality is constructed to detect the faults with a preliminary acquaintance of the bearing condition. In the second step, vibration signals with fault conditions are firstly decomposed into a collection of intrinsic mode functions by using variational mode decomposition and then multiscale permutation entropy features derived from each mono-component are extracted to identify the specific fault types. In order to improve the classification ability of the characteristic data, the out-of-bag estimation of random forests is firstly employed to reelect and refine the original multiscale permutation entropy features. Then the refined features are considered as the input data to train the random forests-based classification model. Finally, the condition data of bearings with different fault conditions are employed to evaluate the performance of the proposed method. The results indicate that the proposed method can effectively identify the working conditions and fault types of rolling element bearings.