Search

Dextransucrases play a crucial role in the production of dextran from economical sucrose; therefore, there is a pressing demand to explore novel dextransucrases with better performance. This study characterized a dextransucrase enzyme, LmDexA, which was identified from the Leuconostoc mesenteroides NN710. This bacterium was isolated from the soil of growing dragon fruit in Guangxi province, China. We successfully constructed six different N-terminal truncated variants through sequential analysis. Additionally, a truncated variant, ΔN190LmDexA, was constructed by removing the 190 amino acids fragment from the N-terminal. This truncated variant was then successfully expressed heterologously in Escherichia coli and purified. The purified ΔN190LmDexA demonstrated optimal hydrolysis activity at a pH of 5.6 and a temperature of 30 °C. Its maximum specific activity was measured to be 126.13 U/mg, with a Km of 13.7 mM. Results demonstrated a significant improvement in the heterologous expression level and total enzyme activity of ΔN190LmDexA. ΔN190LmDexA exhibited both hydrolytic and transsaccharolytic enzymatic activities. When sucrose was used as the substrate, it primarily produced high-molecular-weight dextran (>400 kDa). However, upon the addition of maltose as a receptor, it resulted in the production of a significant amount of oligosaccharides. Our results can provide valuable information for enhancing the characteristics of recombinant dextransucrase and potentially converting sucrose into high-value-added dextran and oligosaccharides. [ABSTRACT FROM AUTHOR]

Lysosomes are degradation centers of cells and intracellular hubs of signal transduction, nutrient sensing, and autophagy regulation. Dysfunction of lysosomes contributes to a variety of diseases, such as lysosomal storage diseases (LSDs) and neurodegeneration, but the mechanisms are not well understood. Altering lysosomal activity and examining its impact on the occurrence and development of disease is an important strategy for studying lysosome-related diseases. However, methods to dynamically regulate lysosomal function in living cells or animals are still lacking. Here, we constructed lysosome-localized optogenetic actuators, named lyso-NpHR3.0, lyso-ArchT, and lyso-ChR2, to achieve optogenetic manipulation of lysosomes. These new actuators enable light-dependent control of lysosomal membrane potential, pH, hydrolase activity, degradation, and Ca2+ dynamics in living cells. Notably, lyso-ChR2 activation induces autophagy through the mTOR pathway, promotes Aβ clearance in an autophagy-dependent manner in cellular models, and alleviates Aβ-induced paralysis in the Caenorhabditis elegans model of Alzheimer's disease. Our lysosomal optogenetic actuators supplement the optogenetic toolbox and provide a method to dynamically regulate lysosomal physiology and function in living cells and animals. Lysosomes are cellular degradation centers, critical for maintaining homeostasis. Selective modulation of lysosomal activity has remained a challenge to date; this study reports the development of lysosome-targeted optogenetic tools for the light-inducible manipulation of lysosomal physiology in cells and in C. elegans. [ABSTRACT FROM AUTHOR]

Rice yield is essential to global food security under increasingly frequent and severe climate change events. Spatial analysis of rice yields becomes more critical for regional action to ensure yields and reduce climate impacts. However, the understanding of the spatially varied geographical, climate, soil, and environmental factors of rice yields needs to be improved, leading to potentially biased local rice yield prediction and responses to climate change. This study develops a spatial machine learning-based approach that integrates machine learning and spatial stratified heterogeneity models to identify the determinants and spatial interactions of rice yields in the main rice-producing areas of China, the world's largest rice-producing nation. A series of satellite remote sensing-derived variables are collected to characterize varied geographical, climate, soil, and environmental conditions and explain the spatial disparities of rice yields. The first step is to explore the spatial clustering patterns of the rice yield distributions using spatially global and local autocorrelation models. Next, a Geographically Optimal Zones-based Heterogeneity (GOZH) model, which integrates spatial stratified heterogeneity models and machine learning, is employed to explore the power of determinants (PD) of individual spatial variables in influencing the spatial disparities of rice yields. Third, geographically optimal zones are identified with the machine learning-derived optimal spatial overlay of multiple geographical variables. Finally, the overall PD of various variables affecting rice yield distributions is calculated using the multiple variables-determined geographically optimal zones and the GOZH model. The comparison between the developed spatial machine learning-based approach and previous related models demonstrates that the GOZH model is an effective and robust approach for identifying the spatial determinants and their spatial interactions with rice yields. The identified spatial determinants and their interactions are essential for enhancing regional agricultural management practices and optimizing resource allocation within diverse main rice-producing regions. The comprehensive understanding of the spatial determinants and heterogeneity of rice yields of this study has a broad impact on agricultural strategies and food security. [ABSTRACT FROM AUTHOR]

In the face of complex scenarios, the information insufficiency of classification tasks dominated by a single modality has led to a bottleneck in classification performance. The joint application of multimodal remote sensing data for surface observation tasks has garnered widespread attention. However, issues such as sample differences between modalities and the lack of correlation in physical features have limited the performance of classification tasks. Establishing effective interaction between multimodal data has become another significant challenge. To fully integrate heterogeneous information from multiple modalities and enhance classification performance, this paper proposes a dual-branch cross-Transformer feature fusion network aimed at joint land cover classification of hyperspectral imagery (HSI) and Light Detection and Ranging (LiDAR) data. The core idea is to leverage the potential of convolutional operators to represent spatial features, combined with the advantages of the Transformer architecture in learning remote dependencies. The framework employs an improved self-attention mechanism to aggregate features within each modality, highlighting the spectral information of HSI and the spatial (elevation) information of LiDAR. The feature fusion module based on cross-attention integrates deep features from two modalities, achieving complementary information through cross-modal attention. The classification task is performed using jointly obtained spectral and spatial features. Experiments were conducted on three multi-source remote sensing classification datasets, demonstrating the effectiveness of the proposed model compared to existing methods. [ABSTRACT FROM AUTHOR]

Aim: To describe the lived experiences of family caregivers of individuals with dementia during the coronavirus disease (COVID‐19) outbreak in China. Design: This study used a descriptive phenomenological research method. Methods: Between May and September 2021, semi‐structured interviews were conducted with 22 family caregivers of people with dementia. Colaizzi's method was used for manual analysis. Results: Qualitative data revealed an overarching experience of finding 'There is always good fortune in misfortune to encourage us in coping with difficulties'. Three themes emerged: family reactions to the COVID‐19 outbreak, feeling supported by multiple resources performing respective functions and resilient adaptation to new situations. Conclusion: During the COVID‐19 outbreak, family caregivers of people living with dementia in China looked for positive aspects among difficulties and experienced corresponding reactions, social support resources and resilient adapted coping styles. Implications for the Profession and/or Patient Care: Nurses in China and other countries facing similar pandemic characteristics, cultures or economic development levels, can guide family caregivers to look at family hardships from a positive perspective, develop interventions to rapidly respond to families' reactions after a disaster and help them identify social support resources and form adapted coping styles. Impact: We identified the resilience and the positive experiences of Chinese family caregivers of individuals with dementia during the COVID‐19 outbreak. The results can inform countries with similar cultures and economic levels, offering measures to support their adaptation to pandemics. Reporting Method: This study followed the COREQ guidelines. Patient or Public Contribution: Family caregivers of people with dementia who met the inclusion criteria and who were interested in sharing their understanding of their experiences, participated in the study. [ABSTRACT FROM AUTHOR]

Aiming to address the issues of parameter complexity and high computational load in existing fault detection algorithms for transmission lines, which hinder their deployment on devices like drones, this study proposes a novel lightweight model called Leaner YOLOv7-Tiny. The primary goal is to swiftly and accurately detect typical faults in transmission lines from aerial images. This algorithm inherits the ELAN structure from YOLOv7-Tiny network and replaces its backbone with depthwise separable convolutions to reduce model parameters. By integrating the SP attention mechanism, it fuses multi-scale information, capturing features across various scales to enhance small target recognition. Finally, an improved FCIoU Loss function is introduced to balance the contribution of high-quality and low-quality samples to the loss function, expediting model convergence and boosting detection accuracy. Experimental results demonstrate a 20% reduction in model size compared to the original YOLOv7-Tiny algorithm. Detection accuracy for small targets surpasses that of current mainstream lightweight object detection algorithms. This approach holds practical significance for transmission line fault detection. [ABSTRACT FROM AUTHOR]

Sugarcane bagasse (SCB) is an abundant agricultural waste, rich in cellulose and hemicellulose, that could be used as an ideal raw material for succinic acid (SA) production. A two-step chemical pretreatment, involving alkali extraction and alkaline hydrogen peroxide treatment, was utilized to treat SCB, followed by multi-enzyme hydrolysis to obtain a reducing sugar hydrolysate mainly composed of glucose and xylose. Optimization of the multi-enzyme hydrolysis of pretreated SCB resulted in a final reducing sugar concentration of 78.34 g/L. In order to enhance the bioconversion of SCB to SA and to reduce the production costs, the initial reducing sugar concentration, nitrogen source, and MgCO3 content were further optimized. The results demonstrated that the inexpensive corn steep liquor powder (CSLP) could be utilized as an alternative nitrogen source to yeast extract for the production of SA; and the optimal concentrations of initial reducing sugar, CSLP, and MgCO3 were 70 g/L, 18 g/L, and 60 g/L, respectively. When fed-batch fermentation was conducted in a 2 L stirred bioreactor, approximately 72.9 g/L of SA was produced, with a yield of 83.2% and a productivity of 1.40 g/L/h. The high SA concentration, yield, and productivity achieved in this study demonstrate the potential of SCB, an agricultural waste, as a viable alternative substrate for Actinobacillus succinogenes GXAS137 to produce SA. This lays a solid foundation for the resource utilization of agricultural waste and cost-effective industrial-scale production of SA in the future. [ABSTRACT FROM AUTHOR]

Pseudorabies virus (PRV) is an immunosuppressive virus that causes significant damage to the pig industry. This study aimed to investigate the effects of PRV on oxidative stress and apoptotic related in the spleen of mice to provide basis knowledge for further research on the pathogenesis of PRV in mice model. 36 mice were randomly two groups, the control group which only received 200 μL PBS and infection group which was subcutaneously infected with 200 μL of 1 × 103 TCID50/100 μL PRV, respectively. Spleen tissues in each group were collected for further experiments at 48, 72, and 96 h post-infection (hpi). Pathological observation was performed by hematoxylin and eosin Y staining. Biochemical and Flow cytometry methods were used to determine the reactive oxygen species profile and apoptosis of the spleen post-infection and apoptosis detection. In addition, q-PCR and Western blot were adopted to measure the apoptotic conditions of the spleen infected with PRV. The results indicated that the reactive oxygen species (ROS) level in the PRV infection group was remarkedly increased (p < 0.01) at a time-dependent pattern. Furthermore, the Malondialdehyde levels in the spleen of mice in the infection group increased (p < 0.01) in a time-dependent mode. However, the activity of Catalase, Superoxide dismutase, and glutathione peroxidase and the content of Glutathione in the infection group were decreased with the control group (p < 0.01) at a time-dependent manner. In addition, the ratio of splenocyte apoptosis in the infection group significantly increased (p < 0.01) in a time-dependent manner. In conclusion, PRV infection causes apoptosis of the spleen via oxidative stress in mice. [ABSTRACT FROM AUTHOR]

Purpose: The Radiofrequency (RF)‐induced heating for an active implantable medical device (AIMD) with dual parallel leads is evaluated in this paper. The coupling effects between dual parallel leads are studied via simulations and experiments methods. The global transfer function technique is used to assess the RF‐induced heating for dual‐lead AIMDs inside four human body models. Methods: RF‐induced heating for spinal cord stimulator systems with 60 and 90 cm length leads are studied at three parallel dual‐lead configurations (closely spaced, 8 mm spaced, and 40 mm spaced) and a single‐lead configuration. The global transfer function method is used to develop the AIMD models of different configurations and is used for lead‐tip heating assessments inside human body models. Results: In simulation studies, the peak 1g specific absorption rate/temperatrue rises of dual parallel leads systems is lower than those from the single‐lead system. In experimental American Society for Testing and Materials phantom studies, the temperature rises for the single‐lead AIMD system can be 2.4 times higher than that from dual‐lead AIMD systems. For the spinal cord stimulator systems used in the study, the statistical analysis shows the RF‐induced heating of dual‐lead configurations are also lower than those from the single‐lead configuration inside all four human body models. Conclusion: For the AIMD system in this study, it shows that the coupling effects between the dual parallel leads of AIMD systems can reduce RF‐induced heating. The global transfer function for different spatial distance dual‐lead configurations can potentially provide a method for the RF‐induced heating evaluation for dual‐lead AIMD systems. [ABSTRACT FROM AUTHOR]

Aim: To investigate the prevalence of SUI and explore the factors that could influence the severity of SUI in adult females. Design: A cross‐sectional study. Methods: A total of 1178 subjects were assessed using a risk‐factor questionnaires and International Consultation on Incontinence Questionnaire Short Form (ICIQ‐SF) and then divided into no SUI group, mild SUI group and moderate‐to‐severe SUI group according to the ICIQ‐SF score. Univariate analysis between adjacent groups and ordered logistic regression models in three groups were then performed to analysis the possible associated factor with the progressive of SUI. Results: The prevalence of SUI among adult women was 22.2% of them; 16.2% and 6% had mild SUI and moderate‐to‐severe SUI, respectively. Moreover, logistic analysis revealed that age, BMI, smoking, position preference for urination, urinary tract infections, urinary leaks during pregnancy, gynaecological inflammation and poor sleep quality were independent risk for the severity of SUI. Conclusion: SUI symptoms were mostly mild among Chinese females, specific risk factors such as unhealthy living habits and urination behaviours increased the risk of SUI and the aggravation of symptoms. Therefore, targeted interventions should be formulated for women to delay disease progression. [ABSTRACT FROM AUTHOR]

To develop quick‐charge sodium‐ion battery, it is significant to optimize insertion‐type anode to afford fast Na+ diffusion rate and excellent electron conductivity. First‐principles calculations reveal the TiO subcompound superiority for Na+ diffusion following Ti(II)O > Ti(III)O > Ti(IV)O. Hence, in situ growth of amorphous TiO subcompounds with rich oxygen defects based on Ti3C2Tx‐MXene is developed. Meanwhile, the composite presents expanded MXene interlayer spacing and much enhanced conductivity. The synergistic effect of enhanced electron/ion conduction gives a high capacity of 107 mAh g−1 at 50 A g−1, which gives 50% and 150% increasements compared with one counterpart without valence adjustment and another one without MXene expansion. It only needs 20 s (at 30 A g−1) to complete the discharge/charge process and obtains a capacity of 144.5 mAh g−1, which also shows a long‐term cycling stability at quick‐charge mode (121 mAh g−1 after 10000 cycles at 10 A g−1). The enhanced performance comes from fast electron transfer among TiO subcompounds contributed by rich‐defect amorphous TiO2–x, and a reversible change of elastic MXene with interlayer spacing between 1.4 and 1.9 nm during Na+ insertion/extraction process. This study provides a feasible route to boost the kinetics and develop quick‐charge sodium‐ion battery. [ABSTRACT FROM AUTHOR]

This study evaluated the potential of duckweed as a human food, ethanol feedstock, and anticancer drug. First, the nutritional value of wild duckweed was reported for the first time. Its main composition was similar to that of artificially cultivated duckweed, and thus, wild duckweed can serve as a great human food source. In addition, high-starch duckweed induced by nutrient starvation was fermented into bioethanol. A yield of 0.262 g/g, the highest duckweed-ethanol yield reported thus far, was achieved, indicating that duckweed is an excellent feedstock for ethanol production. Finally, the anticancer effects of duckweed flavonoids (DFs) were assessed for the first time using acute myeloid leukaemia (AML) cells as models in vitro and in vivo. The results revealed that DFs possessed antileukaemia activity and were safe and effective for AML therapy. In conclusion, duckweed was demonstrated to be helpful for humans for food security, energy crisis remediation, and tumour treatment. [ABSTRACT FROM AUTHOR]

Background: Resveratrol is a commercially available stilbenoid widely used as dietary supplements, functional food ingredients, and cosmetic ingredients due to its diverse physiological activities. The production of resveratrol in microorganisms provides an ideal source that reduces the cost of resveratrol, but the titer in Saccharomyces cerevisiae was still much lower than that in other hosts. Results: To achieve enhanced production of resveratrol in S. cerevisiae, we constructed a biosynthetic pathway via combining phenylalanine and tyrosine pathways by introducing a bi-functional phenylalanine/tyrosine ammonia lyase from Rhodotorula toruloides. The combination of phenylalanine pathway with tyrosine pathway led to a 462% improvement of resveratrol production in yeast extract peptone dextrose (YPD) medium with 4% glucose, suggesting an alternative strategy for producing p-coumaric acid-derived compounds. Then the strains were further modified by integrating multi-copy biosynthetic pathway genes, improving metabolic flux to aromatic amino acids and malonyl-CoA, and deleting by-pathway genes, which resulted in 1155.0 mg/L resveratrol in shake flasks when cultured in YPD medium. Finally, a non-auxotrophic strain was tailored for resveratrol production in minimal medium without exogenous amino acid addition, and the highest resveratrol titer (4.1 g/L) ever reported was achieved in S. cerevisiae to our knowledge. Conclusions: This study demonstrates the advantage of employing a bi-functional phenylalanine/tyrosine ammonia lyase in the biosynthetic pathway of resveratrol, suggesting an effective alternative in the production of p-coumaric acid-derived compounds. Moreover, the enhanced production of resveratrol in S. cerevisiae lays a foundation for constructing cell factories for various stilbenoids. [ABSTRACT FROM AUTHOR]

Seed vigor is one of the essential contents of agricultural research. The decline of seed vigor is described as an inevitable process. Recent studies have shown that the oxidative damage caused by reactive oxygen species (ROS) is the main reason for the destruction of various chemicals in seeds and eventually evolves into seed death. The traditional vigor tests, such as the seed germination test and TTC staining, are commonly used to assess seed vigor. However, these methods often need a large number of experimental samples, which will bring a waste of seed resources. At present, many new methods that are fast and nondestructive to seeds, such as vibrational spectroscopic techniques, have been used to test seed vigor and have achieved convincing results. This paper is aimed at analyzing the microchanges of seed-vigor decline, summarizing the performance of current seed-vigor test methods, and hoping to provide a new idea for the nondestructive testing of a single seed vigor by combining the physiological alterations of seeds with chemometrics algorithms. [ABSTRACT FROM AUTHOR]

Hydrogen energy, a green renewable energy, has shown great potential in developing new energy and alleviating environmental problems. Water electrolysis is an effective method to achieve large-scale clean hydrogen production, but this process needs to consume a huge amount of electric energy. It is urgent to develop high-activity, high-stability and low-cost catalysts to reduce the consumption of electric energy. At present, the noble metal catalyst is the star material in the hydrogen evolution reaction (HER), but its stability and high cost restrict its large-scale application. In this review, we comprehensively discussed the research progress on noble metal-based heterogeneous electrocatalysts used in water electrolysis for hydrogen production. Firstly, we analyzed the influence factors for hydrogen production performance, including the mass transfer process, the adsorption–desorption process, the catalytic process, and the influence of the working electrode and electrolyte. Then, we discussed the relationship between catalytic activity and electronic structure and chemical composition in view of theoretical calculations and summarized the strategies for developing efficient catalysts (alloying and interface engineering). Finally, we highlighted the challenges for the practical application of noble metal-based hydrogen evolution electrocatalysts. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to investigate the associations between loneliness and its components and cognitive function among older Chinese adults living in nursing homes and to test whether depressive symptoms, anxiety symptoms, and sleep disturbances mediate these associations. Methods: The sample comprised 228 Chinese individuals aged ≥ 65 years living in nursing homes who were free of dementia and psychiatric or serious somatic diseases. Loneliness was evaluated using the UCLA Loneliness Scale. Global cognitive function was assessed using the Beijing version of the Montreal Cognitive Assessment. Multivariable linear regression analyses were performed to examine the associations between loneliness and its components and global cognitive function. A mediation analysis was used to test the potential mediating effects of depressive symptoms, anxiety symptoms, and sleep disturbances. Results: The mean (SD) age of the participants was 80.8 (6.3) years, and 58.3% were women. Compared with the lowest quartile of loneliness degree, the multivariable-adjusted beta coefficient (95% confidence interval [95% CI]) for the highest quartile was -1.32 (-2.61 to -0.02) (P for trend = 0.03). Loneliness components, personal feelings of isolation and the lack of relational connectedness but not the lack of collective connectedness, were also inversely associated with cognitive function. Significant indirect effects on cognitive function were observed for loneliness and its two components (personal feelings of isolation and the lack of relational connectedness) in mediating pathways via depressive symptoms, anxiety symptoms, and sleep disturbances (all p < 0.05). Conclusions: A higher degree of loneliness and its two components, personal feelings of isolation and the lack of relational connectedness, are associated with worse cognitive function among Chinese residents in nursing homes. Depressive symptoms, anxiety symptoms, and sleep disturbances may at least partially mediate these associations. [ABSTRACT FROM AUTHOR]

Mildewed maize kernels were common in nature and they were harmful to humans and livestocks. Therefore, it is essential to screen the mildewed maize kernels and improve food security. In this study, Raman hyperspectral imaging technique was used to screen the mildewed maize kernels. Hyperspectral imaging of both embryo‐up and embryo‐down side were taken into consideration and the effect of their weight ratio on the screening accuracy was compared. Pixel‐wise approach and object‐wise approach were both analyzed and different variables selection methods were applied to optimize the input variables. Six machine learning classifiers including random forest (RF), support vector machine (SVM), linear discriminant analysis (LDA), extreme learning machine (ELM), partial least squares discriminant analysis (PLSDA), and naive Bayes classifier (NBC) were used to establish the screening models. The results exhibited 19 variables selected by competitive adaptive reweighted sampling (CARS) method from the weight ratio of 3:7 based on object‐wise approach were the most suitable for establishment of screening model with accuracy of 90.63% in the testing set. The microscopic mechanism of mildewed maize kernels was illustrated by micro‐fluorescence imaging. The study showed that Raman hyperspectral imaging combined with both embryo‐up and embryo‐down sides of maize kernels could be used as effective methods to improve the accuracy of screening mildewed maize kernels. Practical Applications: This study provides a comprehensive analysis about the pixels and both sides of maize kernels and gives a nondestructive screening method based on both sides of maize kernels for the mildewed detection. According the mildew of maize kernels, enterprises can effectively improve the storage efficiency of maize kernels to reduce economic losses. [ABSTRACT FROM AUTHOR]

Background: Little is known about family members' and patients' expression of negative emotions among high‐risk preoperative conversations. Objectives: This study aimed to identify the occurrence and patterns of the negative emotions of family members and patients in preoperative conversations, to investigate the conversation themes and to explore the correlation between the negative emotions and the conversation themes. Methods: A retrospective study was conducted using the Chinese version of Verona Coding Definitions of Emotional Sequences (VR‐CoDES‐C) to code 297 conversations on high‐risk procedures. Inductive content analysis was used to analyse the topics in which negative emotions nested. The χ2 Test was used to test the association between the cues and the conversation themes. Results: The occurrence rate of family members' and patients' negative emotions was very high (85.9%), much higher when compared to most conversations under other medical settings. The negative emotions were mainly expressed by cues (96.4%), and cue‐b (67.4%) was the most frequent category. Cues and concerns were mostly elicited by family members and patients (71.6%). Negative emotions were observed among seven themes, in which 'Psychological stress relating to illness severity, family's care and financial burden' (30.3%) ranked the top. Cue‐b, cue‐c and cue‐d had a significant correlation (p <.001) with certain themes. Conclusions: Family members and patients conveyed significantly more negative emotions in the high‐risk preoperative conversations than in other medical communications. Certain categories of cues were induced by specific emotional conversation contents. Patient Contribution: Family members and patients contributed to data. [ABSTRACT FROM AUTHOR]

This article presents a cascaded heterogeneous equivalent network for the evaluation of radiofrequency (RF) induced safety hazards on electrically long active implantable medical devices (AIMDs) exposed to magnetic resonance imaging systems. AIMDs in a highly heterogeneous human body are represented by cascaded transmission line models consisting of segments with different values of effective wavenumbers and characteristic impedances. Two terminations, implantable pulse generator (IPG), and lead-tip are modeled as lumped elements. Methods to extract values for lead-tip impedance, IPG impedance, wavenumber, and characteristic impedance of the AIMDs are proposed and validated through numerical simulations and experimental investigations. Based on these values, one can build up a unique AIMD model along each implanted trajectory inside human body models. The developed models can be used to accurately evaluate the RF-induced voltage and heating for each implantation scenario. [ABSTRACT FROM AUTHOR]

Hot compression behaviors of CrCoNi medium entropy alloy are were performed on the Gleeble-3800 thermal simulator in the strain rate range from 0.01 to 10 s−1 and the temperature range from 800 to 1100 °C. According to the true stress-true strain curves, the true stress decreases with the decreasing of strain rate and the increasing of deformation temperature. The experimental parameters were fitted, and a modified model based on Arrhenius hyperbolic sine was established. Among them, material constants such as, n, A, and Q are functions of strain. Meanwhile, the processing map of CrCoNi medium entropy alloy under different strain conditions are established. Importantly, the optimal domain of apparent flow stability can be determined as the deformation temperature from 900 to 1100 °C and the strain rate from 0.01 to 10 s−1. The results indicate that the stability domain of the CrCoN medium entropy alloy has a wider range, and the strain has little effect on its processing performance. [ABSTRACT FROM AUTHOR]

The Kagome superconductors AV3Sb5 (A = K, Rb, Cs) have received enormous attention due to their nontrivial topological electronic structure, anomalous physical properties and superconductivity. Unconventional charge density wave (CDW) has been detected in AV3Sb5. High-precision electronic structure determination is essential to understand its origin. Here we unveil electronic nature of the CDW phase in our high-resolution angle-resolved photoemission measurements on KV3Sb5. We have observed CDW-induced Fermi surface reconstruction and the associated band folding. The CDW-induced band splitting and the associated gap opening have been revealed at the boundary of the pristine and reconstructed Brillouin zones. The Fermi surface- and momentum-dependent CDW gap is measured and the strongly anisotropic CDW gap is observed for all the V-derived Fermi surface. In particular, we have observed signatures of the electron-phonon coupling in KV3Sb5. These results provide key insights in understanding the nature of the CDW state and its interplay with superconductivity in AV3Sb5 superconductors. The impact of the charge density wave (CDW) state to the electronic structure in the Kagome superconductors AV3Sb5 remains unclear. Here, the authors observe CDW-induced Fermi surface reconstruction with a strongly anisotropic CDW gap and signatures of the electron-phonon coupling for all V-derived bands. [ABSTRACT FROM AUTHOR]

Purpose: During MR scans, abandoned leads from active implantable medical devices (AIMDs) can experience excessive heating at the lead tip, depending on the type of termination applied to the proximal contacts (proximal end treatment). The influence of different proximal end treatments (ie, [1] freely exposed in the tissue, [2] terminated with metal in contact with the tissue, or [3] capped with plastic, and thereby fully insulated, on the RF‐induced lead‐tip heating) are studied. A technique to ensure that MR Conditional AIMD leads remain MR Conditional even when abandoned is recommended. Methods: Abandoned leads from three MR Conditional AIMDs ([1] a sacral neuromodulation system, [2] a cardiac rhythm management pacemaker system, and [3] a deep brain stimulator system) were investigated in this study. The computational lead models (ie, the transfer functions) for different proximal end treatments were measured and used to assess the in vivo lead‐tip heating for four virtual human models (FATS, Duke, Ella, and Billie) and compared with the lead‐tip heating of the complete MR Conditional AIMD system. Result: The average and maximum lead‐tip heating for abandoned leads proximally capped with metal is always lower than that from the complete AIMD system. Abandoned leads proximally insulated could lead to an average in vivo temperature rise up to 3.5 times higher than that from the complete AIMD system. Conclusion: For the three investigated AIMDs under 1.5T MR scanning, our results indicate that RF‐induced lead‐tip heating of abandoned leads strongly depends on the proximal lead termination. A metallic cap applied to the proximal termination of the tested leads could significantly reduce the RF‐induced lead‐tip heating. [ABSTRACT FROM AUTHOR]

Purpose: The paper presents a novel method to reduce the RF‐induced heating of active implantable medical devices during MRI. Methods: With the addition of an energy decoying and dissipating structure, RF energy can be redirected toward the dissipating rings through the decoying conductor. Three lead groups (45 cm‐50 cm) and 4 (50 cm‐100 cm) were studied in 1.5 Tesla MR systems by simulation and measurement, respectively. In vivo modeling was performed using human models to estimate the RF‐induced heating of an active implantable medical device for spinal cord treatment. Result: In the simulation study, it was shown that the peak 1g‐averaged specific absorption rate near the lead‐tips can be reduced by 70% to 80% compared to those from the control leads. In the experimental measurements during a 2‐min exposure test in a 1.5 Telsa MR system, the temperature rises dropped from the original 18.3℃, 25.8℃, 8.1℃, and 16.1℃ (control leads 1‐4) to 5.4℃, 6.9℃, 1.6℃, and 3.3℃ (leads 1‐4 with the energy decoying and dissipation structure). The in vivo calculation results show that the maximum induced temperature rise among all cases can be substantially reduced (up to 80%) when the energy decoying and dissipating structures were used. Conclusion: Our studies confirm the effectiveness of the novel technique for a variety of scanning scenarios. The results also indicate that the decoying conductor length, number of rings, and ring area must be carefully chosen and validated. [ABSTRACT FROM AUTHOR]

Sepsis-induced acute kidney injury (AKI) continues to be associated with poor outcomes in critical care patients. Previous research has revealed that tetrahydrocurcumin (THC) exerts renoprotective effects in multiple nephritic disorders by modulating inflammation and oxidative stress. However, the effects of THC on sepsis-induced AKI and the underlying mechanisms remain unclear. In this study, a mouse model of sepsis-induced AKI, generated by cecal ligation and puncture operation, was used to investigate the protective effects of THC and the role of SIRT1. Histological manifestation and TUNEL analysis were observed to determine the severity of kidney damage. Levels of BUN, SCr, KIM-1, and UAlb/Cr were calculated to assess the renal function. Expressions of IL-1β, IL-6, and TNF-α were measured to evaluate the inflammatory response. MDA content, SOD, GSH, CAT, and GPx activities and DHE staining were analyzed to estimate the degree of oxidative stress. Protein expressions of SIRT1, Ac-p65, and Ac-foxo1 were detected to explore the underlying mechanisms. We observed that THC not only increased the survival rate, improved the kidney function and ameliorated the renal histological damage of septic mice, but also inhibited inflammatory response, prohibited oxidative stress, and prevented cell apoptosis in renal tissues in septic mice. Mechanistically, THC remarkably increased the expression of SIRT1, accompanied by decreased expressions of downstream molecules Ac-p65 and Ac-foxo1. Meanwhile, the beneficial effects of THC were clearly abolished by the SIRT1-specific inhibitor EX527. These results delineate that THC prevents sepsis-induced AKI by suppressing inflammation and oxidative stress through activating the SIRT1 signaling. Abbreviation: Ac-p65: acetylated p65; Ac-foxo 1: acetylated forkhead box O1; AKI: acute kidney injury; BUN: blood urea nitrogen; CAT: catalase; DHE: dihydroethidium; GPx: glutathione peroxidase; GSH: reduced glutathione; IL-1β: Interleukin-1 beta; IL-6: Interleukin-6; KIM-1: kidney injury molecule 1; MDA: malondialdehyde; SCr: serum creatinine; SIRT1: silent information regulator 1; SOD: superoxide dismutase; THC: tetrahydrocurcumin; TNF-α: tumor necrosis factor-alpha; TUNEL: TdT-mediated dUTP Nick-End Labeling; UAlb/Cr: urine micro albumin/creatinine. [ABSTRACT FROM AUTHOR]

High resolution angle resolved photoemission measurements and band structure calculations are carried out to study the electronic structure of BaMnSb2. All the observed bands are nearly linear that extend to a wide energy range. The measured Fermi surface mainly consists of one hole pocket around Γ and a strong spot at Y which are formed from the crossing points of the linear bands. The measured electronic structure of BaMnSb2 is unusual and deviates strongly from the band structure calculations. These results will stimulate further efforts to theoretically understand the electronic structure of BaMnSb2 and search for novel properties in this Dirac material. [ABSTRACT FROM AUTHOR]

Single-layer FeSe films grown on the SrTiO3 substrate (FeSe/STO) have attracted much attention because of their possible record-high superconducting critical temperature (Tc) and distinct electronic structures. However, it has been under debate on how high its Tc can really reach due to the inconsistency of the results from different measurements. Here we report spectroscopic evidence of superconductivity pairing at 83 K in single-layer FeSe/STO films. By preparing high-quality single-layer FeSe/STO films, we observe strong superconductivity-induced Bogoliubov back-bending bands that extend to rather high binding energy ~ 100 meV by high-resolution angle-resolved photoemission measurements. They provide a new definitive benchmark of superconductivity pairing that is directly observed up to 83 K. Moreover, we find that the pairing state can be further divided into two temperature regions. These results indicate that either Tc as high as 83 K is achievable, or there is a pseudogap formation from superconductivity fluctuation in single-layer FeSe/STO films. How high the superconducting transition temperature can reach in single layer FeSe/SrTiO3 films has been under debate. Here, the authors use Bogoliubov back-bending bands as a benchmark and demonstrate that superconductivity pairing can be realized up to 83 K in this system. [ABSTRACT FROM AUTHOR]

Harmonics produced by residential loads have become an increasing concern in recent years due to the extensive adoption of power-electronic-based home appliances. Harmonic modeling of aggregate residential loads (ARLs) is of great significance since it is the prerequisite for harmonic evaluation and necessary mitigation measures in the residential areas. In this paper, a piecewise probabilistic harmonic model is proposed to analyze the aggregate harmonics of residential loads. Based on the field measurement data, a unified dominant harmonic coupled matrix model (UD-HCMM) is established. This model directly exhibits the coupled relationship between the harmonic voltages and currents of residential loads. In view of the random and fluctuating harmonic characteristics of home appliances, the multi-Gaussian curve fitting method is used to fit the UD-HCMM parameters. Thereafter, the probabilistic UD-HCMMs are reconstructed using the Newton-Raphson method. Finally, a piecewise UD-HCMM is derived to characterize the time-varying harmonics of ARLs. The accuracy and validity of the proposed method are verified through simulations and field measurements. In addition, the proposed method is applied to evaluate the harmonics of a medium voltage distribution system with massive residential loads. [ABSTRACT FROM AUTHOR]

In this article, an electric (E) field generator is developed to generate uniform and high-strength E-fields at multiple frequencies. The system can be used to assess the radio frequency (RF) hazards of implantable medical devices (IMDs) in magnetic resonance imaging (MRI) environments. The novel system consists of three parts: 1) a signal generating and amplifying block; 2) a four-channel feeding network; and 3) a rectangular resonator box. Mixed modes are utilized to generate locally uniform E-fields inside the rectangular resonator at both 64 and 128 MHz. RF-induced heating for two passive IMD families are evaluated using both numerical and experimental methods inside the E-field generator. These results are compared with those obtained from standard American Society of Testing and Materials (ASTM) phantom testing. The results show that the novel E-field generator is capable of evaluating RF-induced heating for passive IMDs similar to that of the ASTM phantom. Furthermore, it integrates both 1.5- and 3-T RF-induced heating tests in a single system. It is much simpler compared to the ASTM test method which needs the RF coil as a source. Consequently, this small and efficient E-field generator can be used as an alternative system for RF-induced heating tests of passive IMDs in the MRI environment. [ABSTRACT FROM AUTHOR]

We propose a network combining broad learning with transfer learning for problems with large divergences in data distribution between source and target domains associated with rolling bearings under varying loads, scarce vibration data with labeled information, unbalanced distributions of multiple-state data, and low efficiency from model training. This is proposed alongside an intelligent method in rolling bearing diagnosis based on the network. This broad learning system is used to extract data features enabling the construction of feature sample sets. An unsupervised balanced distribution adaptation method in transfer learning is adopted to reduce this divergence in data distribution. Moreover, the chicken swarm optimization method is introduced to optimize the parameters of the network, and a network model is established. Finally, a network combining broad learning with transfer learning is applied to the intelligent fault diagnosis of rolling bearings under varying loads. The experimental results verify the high effectiveness and accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

Rolling bearing vibration data and their labels are difficult or impossible to obtain under varying working conditions. Thus, multistats identification of different fault positions and degradation degrees has relatively low accuracy. This paper proposes a fault diagnosis method based on deep feature transfer. Sparse denoising autoencoder extracts deep features of the frequency-domain amplitude sequences of rolling bearing vibration signals, and the features are used to compose feature sample sets of the source and target domains. Joint geometrical and statistical alignment adaptively processes feature samples of the source and target domains, and this way reduces the distribution divergence and subspace transform shift of the inter-domain feature samples. The classification is achieved using softmax. Experimental results show that the feature visualization effect by visualization algorithm t-SNE using the proposed method is better than those of other methods in this paper. A higher accuracy can also be achieved for rolling bearing fault diagnosis under varying working conditions. [ABSTRACT FROM AUTHOR]

This article presents a novel test instrument and strategy for active implantable medical device (AIMD) model validation under a radiofrequency (RF) field generated by a magnetic resonance imaging (MRI) system. A high electric field generator is developed as an alternative instrument for standard MRI RF coils. This system is both compact and power efficient. In addition, a set of validation pathways are proposed based on the Hadamard matrix. These pathways provide low correlations among incident electric fields and yet generate relatively high temperature rises. Two generic AIMDs with different lengths are used to validate the strategy experimentally. It is demonstrated that this method provides an efficient and effective alternative for future AIMD model validation under MRI RF emissions. [ABSTRACT FROM AUTHOR]

Super-high resolution laser-based angle-resolved photoemission measurements are carried out on LiFeAs superconductor to investigate its electron dynamics. Three energy scales at ∼ 20 meV, ∼ 34 meV, and ∼ 55 meV are revealed for the first time in the electron self-energy both in the superconducting state and normal state. The ∼ 20 meV and ∼ 34 meV scales can be attributed to the coupling of electrons with sharp bosonic modes which are most likely phonons. These observations provide definitive evidence on the existence of mode coupling in iron-based superconductors. [ABSTRACT FROM AUTHOR]

This paper presents a generic method to reduce the radiofrequency (RF) induced heating of external fixation devices during the magnetic resonance imaging (MRI) procedure. A simplified equivalent circuit model was developed to illustrate the interaction between the external fixation device and the MRI RF field. Carefully designed mechanical structures, which utilize capacitive reactance from the circuit model, were applied to the external fixation device to mitigate the coupling between the external fixation device and the MRI RF field for RF-induced heating reduction. Both numerical and experimental studies were performed to demonstrate the validity of the circuit model and the effectiveness of the proposed method. By adding capacitive structures in both the clamp-pin and rod-clamp joints, the peak specific absorption rate averaged in 1 gram (SAR1g) near the pin tips were reduced from 760.4 W kg−1 to 12.0 W kg−1 at 1.5 T and 391.5 W kg−1 to 25.2 W kg−1 at 3 T from numerical simulations. Experimental results showed that RF-induced heating was reduced from 7.85 °C to 1.01 °C at 1.5 T and from 16.70 °C to 0.32 °C at 3 T for the external fixation device studied here. The carefully designed capacitive structures can be used to detune the coupling between the external fixation device and the MRI fields to reduce the RF-induced heating in the human body for both 1.5 T and 3 T MRI systems. However, as RF-induced heating is very device and design specific all devices must be thoroughly tested based on its final design. [ABSTRACT FROM AUTHOR]

There are several issues with existing chaotic encryption schemes for images. These include singularity, unidirectionality, and the complexity of the algorithm. The result is that the encrypted image has low security and acquiring discrete chaotic sequences is time-consuming. In order to solve these problems, a multi-channel chaotic encryption algorithm for color images based on DNA (Deoxyribonucleic acid) coding is proposed. Firstly, a six-dimensional discrete hyperchaotic system is used to generate six sets of chaotic key sequences. Secondly, RGB color components of the color image are extracted. DNA matrices are obtained by DNA coding for each component and merged to construct a combined DNA matrix. After scrambling the DNA matrix, it is split into three same size matrices. The other three matrices are obtained by XOR of the chaotic key matrices. DNA coding is performed for the other three matrices to obtain the corresponding DNA matrices. DNA calculation is performed on two groups of DNA matrices in one-to-one correspondence. The result of DNA calculation is performed by DNA decoding. Finally, multiple round diffusion encryptions are performed on the decoding matrices. Experimental results show that, compared with other methods, the proposed encryption algorithm provides better encryption, can resist different types of attacks, and has higher security. In addition, chaotic sequences can be generated directly by the discrete chaotic system, and the algorithm execution efficiency could be improved. [ABSTRACT FROM AUTHOR]

High temperature superconductivity in cuprates is realized by doping the Mott insulator with charge carriers. A central issue is how such an insulating state can evolve into a conducting or superconducting state when charge carriers are introduced. Here, by in situ vacuum annealing and Rb deposition on the Bi2Sr2Ca0.6Dy0.4Cu2O8 + δ (Bi2212) sample surface to push its doping level continuously from deeply underdoped (Tc = 25 K, doping level p ∼ 0.066) to the near-zero doping parent Mott insulator, angle-resolved photoemission spectroscopy measurements are carried out to observe the detailed electronic structure evolution in the lightly hole-doped region for the first time. Our results indicate that the chemical potential lies at about l eV above the charge transfer band for the parent state at zero doping, which is quite close to the upper Hubbard band. With increasing hole doping, the chemical potential moves continuously towards the charge transfer band and the band structure evolution exhibits a rigid band shift-like behavior. When the chemical potential approaches the charge transfer band at a doping level of ∼0.05, the nodal spectral weight near the Fermi level increases, followed by the emergence of the coherent quasiparticle peak and the insulator–superconductor transition. Our observations provide key insights in understanding the insulator–superconductor transition in doping the parent cuprate compound and for establishing related theories. [ABSTRACT FROM AUTHOR]

Large amounts of labelled vibration data of rolling bearings are difficult to acquire in full during operating conditions under varying loads. Moreover, a large divergence in data distribution exists between source and target domains for the same state. A multiple‐state identification method for rolling bearings under varying loads is proposed. The deep domain adaptation method integrates the convolutional and pooling theory with the deep belief network (DBN) that enables the construction of a convolutional Gaussian–Bernoulli DBN, which is used to extract the deep generalised features from the frequency‐domain amplitudes of the rolling bearings. The weighted mixed kernel is then used instead of the single kernel to improve the joint distribution adaptation, which is used to process the features of both the labelled source domain and the unlabelled target domain for domain adaptation, and reduce the distribution divergence. Finally, the k‐nearest neighbour algorithm is used for identification. Experimental results show that the proposed method can make full use of unlabelled data, mine the deep features of vibration signals, and reduce the divergence between data of the same state. In resolving the multiple‐state identification of rolling bearings under varying loads, a higher accuracy is attained in the identification. [ABSTRACT FROM AUTHOR]

Owing to the uneven distribution of key features in Chinese texts, key features play different roles in text recognition in Chinese text classification tasks. We propose a feature-enhanced fusion model based on attention mechanism for Chinese text classification, a long short-term memory (LSTM) network, a convolutional neural network (CNN), and a feature-difference enhancement attention algorithm model. The Chinese text is digitized into a vector form containing certain semantic context information into the embedding layer to train and test the neural network by preprocessing. The feature-enhanced fusion model is implemented by double-layer LSTM and CNN modules to enhance the fusion of text features extracted from the attention mechanism for classifying the classifiers. The feature-difference enhancement attention algorithm model not only adds more weight to important text features but also strengthens the differences between them and other text features. This operation can further improves the effect of important features on Chinese text recognition. The two models are classified by the softmax function. The text classification experiments are conducted based on the Chinese text corpus. The experimental results show that compared with the contrast model, the proposed algorithm can significantly improve the recognition ability of Chinese text features. [ABSTRACT FROM AUTHOR]

Radio frequency (RF) shimming is a widely used method to improve the MRI quality by adjusting the magnitude and phase of the transmit elements in the RF coil and eliminating the field inhomogeneity in 3T MRI system. This process alters the field distribution inside the MRI borehole and changes both the level and location of the absorbed RF energy in patients. It is necessary to assess the impact of RF shimming on the risk of RF-induced heating for patients especially those who have implantable longitude medical electrodes in place during the MRI procedure. This paper investigates the impacts of RF shimming on the RF-induced heating of a generic pacemaker electrode using a transfer function method. Two different shimming schemes were studied. The first excitation scheme was designed to obtain a homogeneous ${B_{1 + }}$ field in the image region-chest region. The second condition maximized the temperature rise around the generic pacemaker electrode with different implant trajectories. All the results were normalized to 2 W/kg average whole-body specific absorption rate (SAR) and a Q-matrices method was used to improve the SAR calculation efficiency. The average temperature rise at the electrode tip under quadrature excitation was 3.7 °C while under optimized excitation was 2.3 °C. The worst-case temperature rise for a selected trajectory was found to be 33.17 °C, which was almost 6 times of the temperature rise under quadrature excitation. Therefore, the RF-shimming condition can significantly change the RF-induced heating of electrodes. To ensure patient safety under MRI, RF-shimming condition should be considered and thoroughly integrated into the RF heating assessment. [ABSTRACT FROM AUTHOR]

The monolayer WSe2 is interesting and important for future application in nanoelectronics, spintronics and valleytronics devices, because it has the largest spin splitting and longest valley coherence time among all the known monolayer transition-metal dichalcogenides (TMDs). To obtain the large-area monolayer TMDs crystal is the first step to manufacture scalable and high-performance electronic devices. In this letter, we have successfully fabricated millimeter-sized monolayer WSe2 single crystals with very high quality, based on our improved mechanical exfoliation method. With such superior samples, using standard high resolution angle-resolved photoemission spectroscopy, we did comprehensive electronic band structure measurements on our monolayer WSe2. The overall band features point it to be a 1.2 eV direct band gap semiconductor. Its spin splitting of the valence band at K point is found as 460 meV, which is 30 meV less than the corresponding band splitting in its bulk counterpart. The effective hole masses of valence bands are determined as 2.344 me at Γ, and 0.529 me as well as 0.532 me at K for the upper and lower branch of splitting bands, respectively. And screening effect from substrate is shown to substantially impact on the electronic properties. Our results provide important insights into band structure engineering in monolayer TMDs. Our monolayer WSe2 crystals may constitute a valuable device platform. [ABSTRACT FROM AUTHOR]

Copyright of China Quarterly is the property of Cambridge University Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: This paper investigates the RF‐induced heating for multiple adjacent orthopedic implants under MRI at 1.5T and 3T exposure. When multiple implants are closely spaced to each other, the interactions between the implants may affect the RF‐induced heating. Traditional RF‐induced heating labeling is often only applicable to configurations of an individual implant, and is not applicable for multi‐implant configurations. Therefore, the aim of this study is to evaluate the effects of multiple orthopedic implants on RF‐induced heating and to propose potential appropriate instructions for safe scanning of multi‐implantable orthopedic implants. Methods: Typical plate and nail implants were used as examples. The effects of implant configuration, relative positions, and number of implants were investigated. Numerical simulations were conducted using full‐wave electromagnetic simulation software. Experimental measurements at 1.5 T were performed to validate the numerical results. Results: Numerical results indicate that, due to device interaction, the RF‐induced heating of multiple medical implants can be significantly different from that of a single implant. The measured temperature rise for multiple devices could be 2.7 times larger than that of a single implant. Conclusion: Our results confirm that RF‐induced heating of multiple implants can be quite different, and do not follow simple superposition of the results from single devices. Instructions for safe scanning of individual orthopedic devices would not be applicable to multi‐implant configurations. [ABSTRACT FROM AUTHOR]

This paper presents a novel, efficient, and simple method to characterize the transfer function (TF) of leads for active implantable medical devices. The method characterizes the TF using a set of base functions and can be obtained using a few voltage measurements. This procedure requires a few direct measurements of the radiofrequency (RF)-induced voltages on the leads during magnetic resonance imaging (MRI) exposure, and the simulated, or measured, electric field generated by MRI RF coil inside the American Society for Testing and Materials (ASTM) phantom. Consequently, the measurement time of the TF can be reduced and the overall process significantly simplified compared to existing TF measurement methods. The theory of the new method is presented and two examples are given to demonstrate the accuracy and efficiency. [ABSTRACT FROM AUTHOR]

Purpose: To examine the support from different sources of Chinese families of patients with moderate-to-severe dementia that most heavily influences the family adaptation and the influence pathway. Method: Two hundred and three families participated in this study. Chinese versions of instruments were used. Structural equation modeling was applied to confirm the effect pathway. Results: More family support, kin support, community support, and social support (narrow sense) were related to greater levels of family adaptation. Family support was the most heavy influence factor (total effect = 0.374), followed by kin support (0.334), social support (0.137), and community support (0.121). Family support and kin support were direct influence factors, while the other 2 were not. Conclusion: All support will promote family adaptation, especially family support and kin support. Interventions improving support from different sources, especially family support and kin support, will promote adaptation in Chinese families of patients with moderate-to-severe dementia. [ABSTRACT FROM AUTHOR]

With the increase in drilling depth, a slight conical pendulum movement of drilling strings causes the external drilling load becoming a non-negligible excitation source. The phenomenon of unique load sharing would be generated by irregular external load, which has complex influence on cyclic and axial symmetry of a power integrated gearbox. Bearing wear, which brings high frequency unpredictable vibration into the transmission system, is likely to occur because of the specific drive mode of the hydraulic top-drive system applied in well drilling. A systematic model combining the finite element method and the multi-body dynamics of a power-integrated gearbox simulation system is developed in this study with the characteristics of the power system, external load, driving forces, gear mesh stiffness, and bearing support stiffness taken into consideration. The load sharing characteristics of the power-integrated gearbox in a hydraulic top-drive system are numerically investigated. Moreover, the effects of gear mesh stiffness, bearing support stiffness, lateral load, and bearing clearance on the load sharing characteristics are systematically examined. Analysis results show that the dynamic process must be considered to achieve a comprehensive evaluation of the load sharing characteristics of a power-integrated gearbox. Evaluation results indicate that lateral load is the factor that influence the load sharing factor of the power-integrated gearbox most significantly, based on which, predictions can be safely made so that some additional mechanisms might be a practical option to diminish that effect. [ABSTRACT FROM AUTHOR]