The improving strategies and applications of nanotechnology-based drugs in hepatocellular carcinoma treatment.

Hepatocellular carcinoma (HCC) is one of the leading causes of tumor-related death worldwide. Conventional treatments for HCC include drugs, radiation, and surgery. Despite the unremitting efforts of researchers, the curative effect of HCC has been greatly improved, but because HCC is often found in the middle and late stages, the curative effect is still not satisfactory, and the 5-year survival rate is still low. Nanomedicine is a potential subject, which has been applied to the treatment of HCC and has achieved promising results. Here, we summarized the factors affecting the efficacy of drugs in HCC treatment and the strategies for improving the efficacy of nanotechnology-based drugs in HCC, reviewed the recent applications' progress on nanotechnology-based drugs in HCC treatment, and discussed the future perspectives and challenges of nanotechnology-based drugs in HCC treatment.

Optimization of regional emergency supplies distribution vehicle route with dynamic real-time demand.

Given the particular characteristics of a sudden outbreak of an epidemic on a regional scale and considering the possible existence of a latent period process, this paper takes the distribution of regional emergency supplies as the research object. Form the proposes a dynamic vehicle path problem from the perspective of real-time demand changes. First, when there is a sudden outbreak of a small-scale epidemic, there is uncertainty about demand in the epidemic area. The objective functions of minimizing the vehicle travel route cost of emergency vehicles, the late arrival penalty cost of emergency vehicles, and the fixed cost of emergency vehicles, as well as the objective function of minimizing the total distance traveled by vehicles, are established. Second, a mathematical model of the dynamic real-time demand vehicle route problem is built using the actual vehicle routing problem as a basis. The model is then solved using the SFSSA method. Finally, the computational results demonstrate that the SFSSA algorithm can effectively reduce transportation cost and distance when solving the constructed mathematical model problem, providing a solution to the problem of optimizing the route of emergency material distribution vehicles for a regional scale.

A multi-center joint distribution optimization model considering carbon emissions and customer satisfaction.

Logistics enterprises are searching for a sustainable solution between the economy and the environment under the concept of green logistics development. Given that, this study integrates carbon emission as one of the costs into the vehicle routing problem with time window (VRPTW) and establishes a multi-center joint distribution optimization model taking into account distribution cost, carbon emission, and customer satisfaction. In the study of carbon emissions, this paper selected the vehicle load rate and vehicle distance as the main indicators. An improved ant colony algorithm is designed to solve the model by introducing the elite strategy, the saving strategy, vehicle service rules, and customer selection rules. Simulation results show that compared with the traditional ant colony optimization and genetic algorithm, the improved ant colony algorithm can effectively reduce the distribution cost and carbon emission and, improve customer satisfaction.

3D printed strontium-doped calcium phosphate ceramic scaffold enhances early angiogenesis and promotes bone repair through the regulation of macrophage polarization.

The vascularization of bone repair materials is one of the key issues that urgently need to be addressed in the process of bone repair. The changes in macrophage phenotype and function play an important role in the process of vascularization, and endowing bone repair materials with immune regulatory characteristics to enhance angiogenesis is undoubtedly a new strategy to improve the effectiveness of bone repair. In order to improve the effect of tricalcium phosphate (TCP) on vascularization and bone repair, we doped strontium ions (Sr) into TCP (SrTCP) and prepared porous 3D printed SrTCP scaffolds using 3D printing technology, and studied the scaffold mediated macrophage polarization and subsequent vascularization and bone regeneration. The results of the interaction between the scaffold and macrophages showed that the SrTCP scaffold can promote the polarization of macrophages from M1 to M2 and secrete high concentrations of VEGF and PDGF-bb cytokines, which shows excellent angiogenic potential. When human umbilical vein endothelial cells (HUVECs) were co-cultured with macrophage-conditioned medium of SrTCP scaffold, HUVECs exhibited excellent early angiogenesis-promoting effects in terms of scratch healing, angiogenic gene expression, and in vitro tube formation performance. The results of in vivo bone repair experiments showed that the SrTCP scaffold formed a vascular network with high density and quantity in the bone defect area, which could increase the rate of new bone formation and advance the period of bone formation, and finally achieved a better bone repair effect. We observed a cascade effect in which Sr-doped SrTCP scaffold regulate macrophage polarization to enhance angiogenesis and promote bone repair, which may provide a new strategy for the repair of clinical bone defects.

Design and application of improved sparrow search algorithm based on sine cosine and firefly perturbation.

Swarm intelligence algorithms are relatively simple and highly applicable algorithms, especially for solving optimization problems with high reentrancy, high stochasticity, large scale, multi-objective and multi-constraint characteristics. The sparrow search algorithm (SSA) is a kind of swarm intelligence algorithm with strong search capability, but SSA has the drawback of easily falling into local optimum in the iterative process. Therefore, a sine cosine and firefly perturbed sparrow search algorithm (SFSSA) is proposed for addressing this deficiency. Firstly, the Tent chaos mapping is invoked in the initialization population stage to improve the population diversity; secondly, the positive cosine algorithm incorporating random inertia weights is introduced in the discoverer position update, so as to improve the probability of the algorithm jumping out of the local optimum and speed up the convergence; finally, the firefly perturbation is used to firefly perturb the sparrows, and all sparrows are updated with the optimal sparrows using the firefly perturbation method to improve their search-ability. Thirteen benchmark test functions were chosen to evaluate SFSSA, and the results were compared to those computed by existing swarm intelligence algorithms, as well as the proposed method was submitted to the Wilcoxon rank sum test. Furthermore, the aforesaid methods were evaluated in the CEC 2017 test functions to further validate the optimization efficiency of the algorithm when the optimal solution is not zero. The findings show that SFSSA is more favorable in terms of algorithm performance, and the method's searchability is boosted. Finally, the suggested algorithm is used to the locating problem of emergency material distribution centers to further validate the feasibility and efficacy of SFSSA.

Deep-learning image reconstruction for image quality evaluation and accurate bone mineral density measurement on quantitative CT: A phantom-patient study.

Background and purpose: To investigate the image quality and accurate bone mineral density (BMD) on quantitative CT (QCT) for osteoporosis screening by deep-learning image reconstruction (DLIR) based on a multi-phantom and patient study. Materials and methods: High-contrast spatial resolution, low-contrast detectability, modulation function test (MTF), noise power spectrum (NPS), and image noise were evaluated for physical image quality on Caphan 500 phantom. Three calcium hydroxyapatite (HA) inserts were used for accurate BMD measurement on European Spine Phantom (ESP). CT images were reconstructed with filtered back projection (FBP), adaptive statistical iterative reconstruction-veo 50% (ASiR-V50%), and three levels of DLIR(L/M/H). Subjective evaluation of the image high-contrast spatial resolution and low-contrast detectability were compared visually by qualified radiologists, whilst the statistical difference in the objective evaluation of the image high-contrast spatial resolution and low-contrast detectability, image noise, and relative measurement error were compared using one-way analysis of variance (ANOVA). Cohen's kappa coefficient (k) was performed to determine the interobserver agreement in qualitative evaluation between two radiologists. Results: Overall, for three levels of DLIR, 50% MTF was about 4.50 (lp/cm), better than FBP (4.12 lp/cm) and ASiR-V50% (4.00 lp/cm); the 2 mm low-contrast object was clearly resolved at a 0.5% contrast level, while 3mm at FBP and ASiR-V50%. As the strength level decreased and radiation dose increased, DLIR at three levels showed a higher NPS peak frequency and lower noise level, leading to leftward and rightward shifts, respectively. Measured L1, L2, and L3 were slightly lower than that of nominal HA inserts (44.8, 95.9, 194.9 versus 50.2, 100.6, 199.2mg/cm3) with a relative measurement error of 9.84%, 4.08%, and 2.60%. Coefficients of variance for the L1, L2, and L3 HA inserts were 1.51%, 1.41%, and 1.18%. DLIR-M and DLIR-H scored significantly better than ASiR-V50% in image noise (4.83 ± 0.34, 4.50 ± 0.50 versus 4.17 ± 0.37), image contrast (4.67 ± 0.73, 4.50 ± 0.70 versus 3.80 ± 0.99), small structure visibility (4.83 ± 0.70, 4.17 ± 0.73 versus 3.83 ± 1.05), image sharpness (3.83 ± 1.12, 3.53 ± 0.90 versus 3.27 ± 1.16), and artifacts (3.83 ± 0.90, 3.42 ± 0.37 versus 3.10 ± 0.83). The CT value, image noise, contrast noise ratio, and image artifacts in DLIR-M and DLIR-H outperformed ASiR-V50% and FBP (P<0.001), whilst it showed no statistically significant between DLIR-L and ASiR-V50% (P>0.05). The prevalence of osteoporosis was 74 (24.67%) in women and 49 (11.79%) in men, whilst the osteoporotic vertebral fracture rate was 26 (8.67%) in women and (5.29%) in men. Conclusion: Image quality with DLIR was high-qualified without affecting the accuracy of BMD measurement. It has a potential clinical utility in osteoporosis screening.

Demand forecast and influential factors of cold chain logistics based on a grey model.

Due to high requirements of storage, operation and delivery conditions, it is more difficult for cold chain logistics to meet the demand with supply in the course of disruption. And, accurate demand forecasting promotes supply efficiency for cold chain logistics in a changeable environment. This paper aims to find the main influential factors of cold chain demand and presents a prediction to support the resilience operation of cold chain logistics. After analyzing the internal relevance between potential factors and regional agricultural cold chain logistics demand, the grey model GM (1, N) with fractional order accumulation is established to forecast future agricultural cold chain logistics demand in Beijing, Tianjin, and Hebei. The following outcomes have been obtained. (1) The proportion of tertiary industry, per capita disposable income indices for urban households and general price index for farm products are the first three factors influencing the cold chain logistics demand for agricultural products in both Beijing and Tianjin. The GDP, fixed asset investment in transportation and storage, and the proportion of tertiary industry are three major influential factors in Hebei. (2) Agricultural cold chain demand in Beijing and Hebei will grow sustainably in 2021-2025, while the trend in Tianjin remains stable. In conclusion, regional developmental differences should be considered when planning policies for the Beijing-Tianjin-Hebei cold chain logistics system.

Infrared small target energy distribution model for subpixel motion.

Dim small target detection is an important application of infrared (IR) searching and tracking systems. IR small target detection methods based on target energy information can accomplish a high detection rate and low false alarm rate. However, the general inaccuracy of target energy distribution models makes most detection algorithms ineffective. In this paper, considering the effect of a target's subpixel motion on energy distribution, a new, to the best of our knowledge, IR small target energy distribution (NSTED) model for subpixel motion is proposed. The NSTED model can well describe energy distribution variation of a subpixel moving target. The simulation results demonstrate that NSTED has a better output signal-to-noise ratio (SNR) than state-of-the-art Gaussian and hyperbolic secant models. Compared with the two models, NSTED improves the output SNR by at least 17.9% and 20.7%, respectively.

Attention-Based Temporal Encoding Network with Background-Independent Motion Mask for Action Recognition.

Convolutional neural network (CNN) has been leaping forward in recent years. However, the high dimensionality, rich human dynamic characteristics, and various kinds of background interference increase difficulty for traditional CNNs in capturing complicated motion data in videos. A novel framework named the attention-based temporal encoding network (ATEN) with background-independent motion mask (BIMM) is proposed to achieve video action recognition here. Initially, we introduce one motion segmenting approach on the basis of boundary prior by associating with the minimal geodesic distance inside a weighted graph that is not directed. Then, we propose one dynamic contrast segmenting strategic procedure for segmenting the object that moves within complicated environments. Subsequently, we build the BIMM for enhancing the object that moves based on the suppression of the not relevant background inside the respective frame. Furthermore, we design one long-range attention system inside ATEN, capable of effectively remedying the dependency of sophisticated actions that are not periodic in a long term based on the more automatic focus on the semantical vital frames other than the equal process for overall sampled frames. For this reason, the attention mechanism is capable of suppressing the temporal redundancy and highlighting the discriminative frames. Lastly, the framework is assessed by using HMDB51 and UCF101 datasets. As revealed from the experimentally achieved results, our ATEN with BIMM gains 94.5% and 70.6% accuracy, respectively, which outperforms a number of existing methods on both datasets.

Clinical efficacy of atorvastatin calcium combined with aspirin in patients with acute ischemic stroke and effect on neutrophils, lymphocytes and IL-33.

Clinical efficacy of atorvastatin calcium combined with aspirin in patients with acute ischemic stroke (AIS) and its effect on neutrophils to lymphocytes ratio (NLR) and interleukin-33 (IL-33) were investigated. In total, 108 patients with AIS in Luoyang Central Hospital Affiliated to Zhengzhou University from April 2016 to October 2017 were selected. There were 56 cases treated with atorvastatin calcium combined with aspirin as the observation group, and 52 cases were treated with aspirin alone as the control group. The clinical effect was observed. The NLR and IL-33 levels were measured by routine blood test and enzyme linked immunosorbent assay (ELISA) before and after treatment. The scores of the National Institutes of Health Stroke scale (NIHSS) and the occurrence of complications were collected before and after treatment in the two groups. Modified Rankin Scale (MRS) was used to evaluate the curative effect. Score ≤2 points is effective in the treatment. Pearson's analysis was used to analyze the correlation between NLR, IL-33 and NIHSS score. The total hospitalization time and 1 year survival rate were compared. The total effective rate of treatment in the observation group was higher than that in the control group (P<0.05). There was no difference in NLR and IL-33 levels between the two groups before treatment (P>0.05). After treatment, the NLR in the observation group was significantly lower than that in the control group (P<0.05). After treatment, the NIHSS score, the total number of complications and the total hospitalization time in the observation group were significantly lower than those in the control group (P<0.05). Pearson's analysis showed a positive correlation between NLR and NIHSS score (r=0.681, P<0.001), and a negative correlation between IL-33 and NIHSS score (r=-0.708, P<0.001). In conclusion, atorvastatin calcium combined with aspirin has a better effective rate in the treatment of acute ischemic stroke than aspirin alone. The combination can better reduce the NLR, increase the expression level of IL-33 in serum, reduce the occurrence of complications and hospitalization time, and increase the survival rate of patients.

Down-regulation of DJ-1 Augments Neuroinflammation via Nrf2/Trx1/NLRP3 Axis in MPTP-induced Parkinson's Disease Mouse Model.

Microglia-mediated neuroinflammation plays a significant role in the pathogenesis of Parkinson's disease (PD). Down-regulation of DJ-1, a PD-associated protein, has been recently found to increase microglial sensitivity to lipopolysaccharides (LPS). However, the role of DJ-1 in microglia-mediated neuroinflammation in PD remains unclear. 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) was used to establish a PD model with mice and tyrosine hydroxylase (TH) staining was performed to validate the model. Adenovirus strategy and shRNA was employed to knockdown the expression of DJ-1 in mice and BV2 microglia, respectively. Western Blot and quantitative PCR were carried out to determine the expression of cytokines, DJ-1, Nrf2, Trx1 and NRLP3. Immunoprecipitation was used to examine the potential interaction between DJ-1 and Nrf2 or Trx1. Flow cytometry-based Annexin V/7-AAD assay were performed to evaluate cell apoptosis. We found that down-regulation of DJ-1 exacerbated neuroinflammation in PD mice. DJ-1 and Nrf2 knockdown promoted inflammation and cell apoptosis in BV2 microglia, while NLRP3 knockdown had opposite effects. Furthermore, DJ-1 regulated the expression of NLRP3 by upregulating Nrf2/Trx1 axis. Taken together, these data suggested that down-regulation of DJ-1 accelerated microglia-mediated neuroinflammation and cell apoptosis via Nrf2/Trx1/NLRP3 axis. Thus, our results demonstrated the important role of DJ-1 in PD pathogenesis and warranted further investigation of DJ-1 as a therapeutic target for PD.

Tianzhi granule improves cognition and BPSD of vascular dementia: a randomized controlled trial.

BACKGROUND AND PURPOSE: Tianzhi granule (TZ) is usually used for patients with vascular dementia (VaD) in China. The aim was to assess the effect of TZ by a randomized clinical trial (RCT). METHODS: A 24-week RCT was conducted in 16 centres. Participants were grouped into TZ, donepezil or placebo. The co-primary outcomes were the Vascular Dementia Assessment Scale-cognitive subscale (VADAS-cog) and Clinician's Interview-based Impression of Change-plus caregiver information (CIBIC-plus). RESULTS: A total of 543 patients with mild to moderate VaD were enrolled, of whom 242 took TZ granules, 241 took donepezil, and 60 took placebo. The least-squares mean changes from baseline and 95% CI were 6.20 (5.31, 7.09) (TZ group), 6.53 (5.63, 7.42) (donepezil group) and 3.47 (1.76, 5.19) (placebo group), both TZ and donepezil showed small but significantly improvement compared with placebo group. The percent of improvement on the global impression which was measured by CIBIC-plus was 73.71% in TZ and 58.18% in placebo, there was significant different between TZ and placebo group (P = 0.004). No significant differences were observed between TZ and donepezil. No significant differences of adverse events were found. CONCLUSIONS: TZ and donepezil could bring symptomatic benefit for mild to moderate VaD. Trial registration The protocol had retrospectively registered at clinical trial.gov, Unique identifier: NCT02453932, date of registration: May 27, 2015; https://www.clinicaltrials.gov/ct2/show/NCT02453932?term=NCT02453932&rank=1.

Lack of association between serum homocysteine level and middle cerebral artery stenosis.

OBJECTIVES: Lowering homocysteine (HCY) has beneficial effects on vascular events in primary prevention but not in secondary prevention. Research on serum HCY level and middle cerebral artery (MCA) stenosis is lacking. The purpose of the study was to determine the association between these factors and provide more evidence for the prevention of ischemic stroke. METHODS: A total of 412 patients (35-93 years old) in the Neurology Department were recruited. Data of clinical and biochemical vascular risk factors were collected. MCA stenosis, including M1, M2, and M3, was determined by brain magnetic resonance angiography (MRA) and classified into stenosis or no stenosis. The differences and associations were analyzed by relevant statistical methods. RESULTS: There was no significant difference (p = 0.325) in HCY levels between the MCA stenosis and no stenosis groups at baseline. Logistic regression analysis demonstrated that there was no significant association between HCY levels and MCA stenosis (p = 0.447). After the two groups were matched for age and sex, there was still no difference (p = 0.540 for males and 0.061 for females) or association (p = 0.709 for males and 0.098 for females). In addition, we found that ischemic stroke was more prevalent in the MCA stenosis group and uric acid was higher in males with MCA stenosis. CONCLUSIONS: The study indicates a lack of association between serum HCY level and MCA stenosis, which may partially explain the negative results of secondary prevention clinical trials focused on lowering serum HCY level. Future studies on HCY reduction should focus more on primary prevention of ischemic stroke.

Non-phase-separated 2D B-C-N alloys via molecule-like carbon doping in 2D BN: atomic structures and optoelectronic properties.

Two-dimensional (2D) B-C-N alloys have recently attracted much attention but unfortunately, Chemical Vapor Deposition (CVD) B-C-N alloys typically phase separate. In spite of that, our analysis of the B-C-N alloy fabricated by electron-beam irradiation suggests that non-phase-separated B-C-N may in fact exist with a carbon concentration up to 14 at%. While this analysis points to a new way to overcome the phase-separation in 2D B-C-N, by first-principles calculations, we show that these B-C-N alloys are made of motifs with even numbers of carbon atoms, in particular, dimers or six-fold rings (in a molecule-like form), embedded in a 2D BN network. Moreover, by tuning the carbon concentration, the band gap of the B-C-N alloys can be reduced by 35% from that of BN. Due to a strong overlap of the wavefunctions at the conduction band and valance band edges, the non-phase-separated B-C-N alloys maintain the strong optical absorption of BN.

Effect of Berberine on Angiogenesis and HIF-1α / VEGF Signal Transduction Pathway in Rats with Cerebral Ischemia - Reperfusion Injury.

OBJECTIVE: To investigate the effect of berberine on angiogenesis and signal transduction pathway of hypoxia-inducible growth factor-1α (HIF-1α) / vascular endothelial growth factor (VEGF) in rats with cerebral ischemia-reperfusion injury. STUDY DESIGN: An experimental study. PLACE AND DURATION OF STUDY: Luoyang Central Hospital Affiliated with Zhengzhou University, China, from 2016 to 2017. METHODOLOGY: Forty-five rats were randomly divided into control group, model group and berberine group, 15 rats in each group. The model of rat with cerebral ischemia-reperfusion injury was duplicated by suture method. Neurological score was evaluated before, after operation, and 7 days after administration. Microvessel density (MVD) of cerebral ischemia- reperfusion cortex was detected by immunohistochemistry. HIF-1α mRNA and VEGF mRNA of cerebral ischemia- reperfusion cortex were detected by RT-PCR. HIF-1α, and VEGF protein expression of cerebral ischemia-reperfusion cortex was detected by Western Blotting. RESULTS: After operation and 7 days of administration, the neurological scores of the control group, model group, and berberine group were different (all p<0.001). After 7 days of administration, neurological score of berberine group was lower than that of model group (p <0.001), MVD, HIF-1α mRNA and VEGF mRNA expression. HIF-1α and VEGF protein expression levels were lower in model group than berberine group (all p <0.001). CONCLUSION: Berberine can promote angiogenesis in the rat with cerebral ischemia-reperfusion injury. Its mechanism may be activation of HIF-1α / VEGF signal transduction pathway.

Morphological parameters and anatomical locations associated with rupture status of small intracranial aneurysms.

Characterization of the rupture risk factors for small intracranial aneurysms (SIAs, ≤5 mm) is clinically valuable. The present study aims to identify image-based morphological parameters and anatomical locations associated with the rupture status of SIAs. Two hundred and sixty-three patients with single SIAs (128 ruptured, 135 unruptured) were included, and six morphological parameters, including size, aspect ratio (AR), size ratio (SR), height-width ratio (H/W), flow angle (FA) and aneurysm width-parent artery diameter ratio, and the aneurysm locations were evaluated using three-dimensional geometry, and were used to identify a correlation with aneurysm rupture. Statistically significant differences were observed between ruptured and unruptured groups for AR, SR, H/W, FA, and aneurysm locations, from univariate analyses. Logistic regression analysis further revealed that AR (p = 0.034), SR (p = 0.004), H/W (p = 0.003), and FA (p < 0.001) had the strongest independent correlation with ruptured SIAs after adjustment for age, gender and other clinical risk factors. A future study on a larger SIA cohort need to establish to what extent the AR, SR, H/W and FA increase the risk of rupture in patients with unruptured SIAs in terms of absolute risks.

Inhibition of JAK1 by microRNA-708 promotes SH-SY5Y neuronal cell survival after oxygen and glucose deprivation and reoxygenation.

MicroRNAs mediates gene expression in various diseases. Studies have shown that aberrant expression of miRNAs affected cerebral protection. In this study, we have investigated the effects of microRNA-708 (miR-708) on cell survival of oxygen and glucose-deprived reoxygenation (OGD/R) human neuroblastoma cells (SH-SY5Y) and explored whether miR-708 inhibited neuronal death by targeting JAK1. In vitro model of ischemia was used to investigate the neuroprotective functions of miR-708. MiR-708 mimics/siJAK1 transfected SH-SY5Y cells were treated with OGD. After 48h of reoxygenation, cell viability and cell survival were determined by EdU and FITC/PI double staining flow cytometry, respectively. Luciferase activity assay was performed to validate the role of JAK1 as a direct target of miR-708. qRT-PCR and Immunofluorescence assays were used to determine the expression of JAK1, MAP2 and NEUN in miR-708 mimics transfected SH-SY5Y cells. To explore the mechanisms involved in cell growth promotion by JAK1, morphological changes in cells were detected upon knockdown of JAK1, and the expression levels of JAK1, Bax, Bcl-2, cleaved-caspase-3, STAT3 and Mcl-1 were determined by Western blotting. The expression of miR-708 significantly decreased in cells treated with OGD/R. MiR-708 directly targeted JAK1 3'UTR to down-regulate JAK1 mRNA expression, whereas the expression of MAP2 and NEUN was upregulated. Previous studies have demonstrated that the suppression of JAK1 inhibited apoptosis phenocopied function of the miR-708 overexpression in OGD/R SH-SY5Y cells. miR-708 decreased the rate of apoptosis of OGD/R SH-SY5Y cells by suppressing the expression of JAK1.

A Novel Fault Diagnosis Method of Rolling Bearings Based on AFEWT-KDEMI.

According to the dynamic characteristics of the rolling bearing vibration signal and the distribution characteristics of its noise, a fault identification method based on the adaptive filtering empirical wavelet transform (AFEWT) and kernel density estimation mutual information (KDEMI) classifier is proposed. First, we use AFEWT to extract the feature of the rolling bearing vibration signal. The hypothesis test of the Gaussian distribution is carried out for the sub-modes that are obtained by the twice decomposition of EWT, and Gaussian noise is filtered out according to the test results. In this way, we can overcome the noise interference and avoid the mode selection problem when we extract the feature of the signal. Then we combine the advantages of kernel density estimation (KDE) and mutual information (MI) and put forward a KDEMI classifier. The mutual information of the probability density combining the unknown signal feature vector and the probability density of the known type signal is calculated. The type of the unknown signal is determined via the value of the mutual information, so as to achieve the purpose of fault identification of the rolling bearing. In order to verify the effectiveness of AFEWT in feature extraction, we extract signal features using three methods, AFEWT, EWT, and EMD, and then use the same classifier to identify fault signals. Experimental results show that the fault signal has the highest recognition rate by using AFEWT for feature extraction. At the same time, in order to verify the performance of the AFEWT-KDEMI method, we compare two classical fault signal identification methods, SVM and BP neural network, with the AFEWT-KDEMI method. Through experimental analysis, we found that the AFEWT-KDEMI method is more stable and effective.

Electronic excitation induced hydrogen-bond adjustment and lattice control in organic-inorganic hybrid cubic perovskites: a fixed occupation molecular dynamics study.

The organic-inorganic hybrid perovskite has become a new type of semiconductor for low cost and highly efficient solar cells. However, the mechanism of interactions between the organic cation and the inorganic framework is still not completely clear under optical electronic excitation. In this work, we employ first-principles molecular dynamics with electronic excitation effects to prove that the hydrogen-bond interaction between the molecular cation and the inorganic lattice can be readily adjusted by several-percentage-valence-electron excitations in cubic CH3NH3PbI3. While the hydrogen-bond interaction causes serious lattice distortions, the electronic excitation can recover the lattice symmetry largely by weakening hydrogen bonding. The study offers atomic dynamics to understand the excitation process in the organic-inorganic hybrid perovskite semiconductor.