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As the micromanipulator of surgical robots works in a narrow space, it is difficult to install any position sensors at the end, so the position control and position detection cannot be accurately performed. A position estimator based on the parameter autonomous selection model is proposed to estimate the end position indirectly. Firstly, a single joint principle prototype and a position estimator model are established through the 4-Dof driving scheme of the micromanipulator and the cable-driven model. Secondly, the proposed parameter change model is combined with the parameter selection method to form a parameter autonomous selection model. Finally, a position estimator based on the parameter autonomous selection model is established. The experimental results show the maximum estimation error of the position estimator is 0.1928°. Compared with other position estimation methods, the position estimator proposed in this paper has higher accuracy and better robustness, which lays a foundation for the full closed-loop control of micromanipulator position.

Background: Ferroptosis, which is caused by an iron-dependent accumulation of lipid hydroperoxides, is a type of cell death linked to diabetic kidney disease (DKD). Previous research has shown that fatty acid binding protein 4 (FABP4) is involved in the regulation of ferroptosis in diabetic retinopathy. The present study was constructed to explore the role of FABP4 in the regulation of ferroptosis in DKD.Methods: We first detected the expression of FABP4 and proteins related to ferroptosis in renal biopsies of patients with DKD. Then, we used a FABP4 inhibitor and small interfering RNA to investigate the role of FABP4 in ferroptosis induced by high glucose in human renal proximal tubular epithelial (HG-HK2) cells.Results: In kidney biopsies of DKD patients, the expression of FABP4 was elevated, whereas carnitine palmitoyltransferase-1A (CP-T1A), glutathione peroxidase 4, ferritin heavy chain, and ferritin light chain showed reduced expression. In HG-HK2 cells, the induction of ferroptosis was accompanied by an increase in FABP4. Inhibition of FABP4 in HG-HK2 cells changed the redox state, sup-pressing the production of reactive oxygen species, ferrous iron (Fe2+), and malondialdehyde, increasing superoxide dismutase, and reversing ferroptosis-associated mitochondrial damage. The inhibition of FABP4 also increased the expression of CPT1A, reversed lipid deposition, and restored impaired fatty acid β-oxidation. In addition, the inhibition of CPT1A could induce ferroptosis in HK2 cells.Conclusion: Our results suggest that FABP4 mediates ferroptosis in HG-HK2 cells by inhibiting fatty acid β-oxidation.

Background: Pregnancy body mass index (BMI) influences fetal weight, yet no studies focused on the comparison of formulas’ predictive accuracy after considering it. Objective: This study aimed to find out the most accurate formula for predicting birth weight, especially in different BMI pregnant women. Methods: It is a prospective observational study. Using a convenient sampling, the participants who met the criteria for inclusion were recruited in a tertiary hospital from January to March 2019. BMI was calculated according to the pregnant woman’s weight and height at the first obstetric visit. The estimated birth weights were predicted by five formulas based on participants’ uterine height and abdominal circumference of the last obstetric examination. The actual birth weight was scaled in the delivery room. The root mean square error (RMSE), empirical cumulative distribution map (ECDP) and Bland–Altman plot were used to determine the accuracy of the formulas in predicting birth weight. Results: A total of 1197 pregnant women were recruited. The RMSE, median value and difference of Zhuo’s formula in predicting the actual birth weight were the smallest (348.7), the closest to 0 (20.0) g, and the smallest (-0.141 ± 11.511) g, respectively. In subgroup analysis, the RMSE of Zhuo’s formula was the smallest in the low and normal BMI groups, and the difference of Zhuo’s formula by Bland- Altman plot was the smallest (only 0.729±10.440) g in the overweight and obese group. Conclusion: Zhuo’s formula for predicting birth weight has the highest accuracy in different BMI groups. Thus, it is worth recommending for clinical use.

Laser-induced plasma deviates from LTE faster with the increase of radius r and slower with the increase of delay time Td in a higher-pressure environment.

As one of the important types of two-dimensional materials, layered double hydroxides (LDHs) have been widely used in the biomedical field as carriers for drug delivery.

Combining molecular transition-metal complexes and semiconductors is an effective way to create high-performance hybrid photocatalysts based on improvement of solar energy harvesting ability and photogenerated charge carrier separation efficiency.

This review aims to summarize existing approaches and their progress on the interpretation of gas-sensing mechanisms in semiconductor materials.

The improvement of methyl lactate yield was achieved by constructing water-tolerant Lewis acid sites, which were generated by reducing hydroxyl groups and increasing coordinatively unsaturated sites.

In this work, a general and convenient protocol for the blue light-promoted radical-mediated cascade spiro-cyclization/Michael addition of N-arylpropiolamides with thiophenols under metal-free conditions was developed.

In this paper, we have developed a metal-free protocol for the controllable synthesis of various 3-selenyl/sulfenyl/telluriumindoles from the regioselective intramolecular cyclization reactions of in situ generated RXCl with o-alkynyl arylamines.

Objective. To review the progress of research on photoplethysmography- (PPG-) based cuffless continuous blood pressure monitoring technologies and prospect the challenges that need to be addressed in the future. Methods. Using Web of Science and PubMed as search engines, the literature on cuffless continuous blood pressure studies using PPG signals in the recent five years were searched. Results. Based on the retrieved literature, this paper describes the available open datasets, commonly used signal preprocessing methods, and model evaluation criteria. Early researches employed multisite PPG signals to calculate pulse wave velocity or time and predicted blood pressure by a simple linear equation. Later, extensive researches were dedicated to mine the features of PPG signals related to blood pressure and regressed blood pressure by machine learning models. Most recently, many researches have emerged to experiment with complex deep learning models for blood pressure prediction with the raw PPG signal as input. Conclusion. This paper summarized the methods in the retrieved literature, provided insight into the artificial intelligence algorithms employed in the literature, and concluded with a discussion of the challenges and opportunities for the development of cuffless continuous blood pressure monitoring technologies.

A cell model is developed and validated to analyze the performance of polymer electrolyte membrane water electrolysis (PEMWE) stacks and systems. It is used to characterize the oxygen evolution reaction (OER) activity on a TiO2-supported IrO2 catalyst and an unsupported IrO2 powder catalyst. Electrochemical, stack, and system thermoneutral potentials are defined and determined for isothermal and non-isothermal stack operation. Conditions are determined under which the system thermoneutral potential or flammability of H2 in the O2 anode stream limits the stack turndown and operating temperature. Performance is analyzed of a complete PEMWE system with an electrolyzer stack containing an IrO2/TiO2 anode catalyst (2 mg/cm2 Ir loading) and N117-like membrane mitigated for H2 crossover, anode balance-of-plant (BOP) components, cathode BOP system with temperature swing adsorption for H2 purification, and electrical BOP system with transformer and rectifier. At the rated power condition, defined as 2 A/cm2 at 1.9 V, 80 °C, and 30 bar H2 pressure, the stack/system efficiency is 65.3%/60.3% at beginning of life (BOL), decreasing to 59.3%/53.9% at end of life (EOL). The peak stack/system efficiency is 76.3%/70.2% at BOL, decreasing to 71.2%/65.6% at EOL. Improvements in catalyst activity and membrane are identified for a 50% increase in current to 3 A/cm2 at 1.8 V.

Artificial intelligence (AI) and the Internet of Things (IoT) make it urgent to push the frontier of AI to the network edge and release the potential of edge big data. The model’s accuracy in data acquisition and music genre classification (MGC) is further improved based on theater music data acquisition. First, machine learning and AI algorithms are used to collect data on various devices and automatically identify music genres. The data collected by edge devices are safe and private, which shortens the time delay of data processing and response. In addition, the deep belief network (DBN)-based MGC algorithm has better overall recognition and classification effect on music genres. The MGC accuracy of the proposed improved DBN algorithm is nearly 80%, compared to 30%–40% of the traditional algorithms. The DBN algorithm is more accurate than the traditional classical algorithm in MGC. The research has an important reference value for developing Internet technology and establishing a music recognition model.

To conduct a Food Literacy Evaluation Questionnaire Chinese Version (FLEQ-Ch) through a cross-cultural validation of the original questionnaire.This was an observational, cross-sectional study undertaken in two phases: (1) translation and cross-culture adaptation, and (2) psychometric evaluation.A total of 509 residents in Yangzhou City, China were enrolled in this study.A translation and cross-cultural adaptation of the FLEQ in Chinese was developed. The psychometric characteristics of FLEQ-Ch were analyzed for internal consistency, content validity, construct validity and discriminant validity.The KMO value of the questionnaire was 0.901 and the approximate chi-square value of Bartlett's sphericity test was 8132.538. The ranges of the Cronbach's α coefficient and the test-retest coefficient of the total questionnaire and three dimensions were 0.869-0.955 and 0.941-0.952, respectively. The value of content validity index of the total questionnaire was 0.945. Construct validity: (1) Aggregation coefficient was between 0.828 and 0.955; (2) Discrimination coefficient was between 0.004 and 0.227; (3) Correlation coefficient between each factor was between 0.046 and 0.188; the correlation coefficient between each factor and the total questionnaire ranged from 0.419 to 0.788. Discriminant validity: the standardized factor loadings of all items on the corresponding factors were 0.75-0.96. The results of the model-fit indices showed RMSEA was 0.08 and GFI was 0.91.The FLEQ-Ch can effectively evaluate the food literacy of the general public in terms of foods planning and management, foods selection, and foods-making attitudes. It covers the four areas of food literacy, and shows good practicability and operability.

The design of metal material curved surface die is a common problem in engineering. From the perspective of intelligent manufacturing, this paper analyzes the mechanism and design key points of metal material curved surface die, establishes the mathematical model of die design by using the matrix equation method, and puts forward a general engineering mathematical calculation method of segmented die design. Based on the look-up table calculation, this scheme can simplify the calculation method and reduce the calculation error, which is suitable for general engineering die processing calculation.

The recognition method based on deep learning has a large amount of calculation for the changes of different traffic densities in the actual traffic environment. In this paper, an integrated recognition method YOLOv4-L is proposed for reducing computational complexity based on the YOLOv4. The characteristics of multi-lane traffic flow with different flow densities were analyzed for statistical data sets, and k-means++ clustering algorithm was used to optimize the prior frame parameters to improve the matching degree between the prior frame. GhostNet was used to replace CSPDarknet53 of original network structure of YOLOv4 as the feature extraction network. The depthwise separable convolution module was introduced to replace the original 3×3 common convolution in feature extraction network, reduce model parameters and improve detection speed. The network model is further improved both with accuracy and robustness with the help of comprehensive method of Mosaic data enhancement, learning rate cosine annealing and label smoothing. Experimental results show that, Recognition speed is greatly improved at the expense of minimal recognition accuracy reduction: the recognition speed improvement value is 47.81%, 49.15% , 56.06% in detection speed (FPS), respectively in free flow, synchronous flow and blocked flow, the reduction value of accuracy is 2.21%, 0.67%,, 0.05% mAP, respectively.

In order to study the role of generative adversarial network (GAN) in music generation, this article creates a convolutional GAN-based Midinet as a baseline model through the music generation process and creative psychological education and GAN principle. Additionally, it proposes a music generation model based on music theory rules and a chord-constrained GAN dual-track music generation model. Based on this model, a deep chord gated recurrent neural generative adversarial network (DCG_GAN) is proposed. The generated melodies are evaluated in both subjective and objective directions. The results show that the three evaluation indicators of DCG_GAN have the highest scores in the subjective evaluation. The average score given by ordinary listeners reaches 3.76 points, and the professional score reaches 3.58 points, which are 0.69 and 1.31 points higher than the baseline model, respectively. In the objective evaluation, DCG_GAN is improved by 8.075% in empty bars rate (EBR). The UPC (num_chroma_used) evaluation index value of the DCG_GAN model is improved by 0.52 compared with the baseline model. The qualified note ratio (QNR) evaluation index value is improved by up to 4.46% among the five audio tracks. The proposed overall style-based music generation model has superior performance in music generation. Both subjective and objective evaluations show that the generated music is more favored by the audience, indicating that the combination of deep learning and GAN has a great effect on music generation.

In order to promote the circulation of Internet entrepreneurial information, based on information theory and general security theory, this paper explains how to construct the attack channel and defense channel of the k-anonymity model, so as to provide a reliable network foundation for the transmission of related information. In order to fully solve the problems existing in multiuser requests, this paper proposes two modules, single-request sharing mode and multirequest sharing mode, to process query requests in the request queue to maximize the reuse of request results. Moreover, the model constructed in this paper needs to be processed through deep learning first and then shared through the intelligent model. Therefore, the data learning and data sharing of the model are mainly analyzed during model validation. The experimental simulation results show that the intelligent sharing model of Internet entrepreneurial information resources based on deep learning proposed in this paper has good data learning and data transmission effects.

In order to solve the problems of highly redundant spatial information and motion noise in the heart rate (HR) estimation from facial videos based on remote Photoplethysmography(rPPG), this paper proposes a novel HR estimation method based on spatial-temporal attention model. Firstly, to reduce the redundant information and strengthen the association relationships of long-range videos, the spatial-temporal facial features are extracted by the 2D convolutional neural network (2DCNN) and 3D convolutional neural network (3DCNN), respectively. The aggregation function is adopted to incorporate feature maps into short segment spatial-temporal feature maps. Secondly, the spatial-temporal strip pooling is designed in the spatial-temporal attention module to reduce head movement noises. Then, via the two-part loss function, the model can focus more on the rPPG signal rather than the interference. We conduct extensive experiments on two public datasets to verify the effectiveness of our model. The experimental results show that the proposed method achieves significantly better performances than the state-of-the-art baselines: The mean absolute error could be reduced by 11% on the PURE dataset, and by 25% on the COHFACE dataset.

Background: Dexterity is an important index for evaluating the motion performance of a robot. The size of the robot connecting rods directly affects the performance of flexibility. Objective: The purpose of this study is to provide an overview of optimal design methods from many pieces of literature and patents, and propose a new optimal design method for ensuring the robot completes its tasks flexibly and efficiently under workspace constraints. Methods: The kinematics and working space of the robot are analyzed to determine the range of motion of each joint. Then, a dexterity index is established based on the mean value of the global spatial condition number. Finally, an improved cuckoo algorithm is proposed, which changes the step size control factor with the number of iterations. Taking the dexterity index as the objective optimization function and the working radius as the constraint condition, the improved cuckoo search algorithm is used to optimize the size of the robot rod. Results: The improved cuckoo algorithm and proposed rod size optimized method are fully evaluated by experiments and comparative studies. The optimization design process shows that the proposed method has better solution accuracy and faster convergence speed. The optimized design results show that the robot's dexterity index has increased by 26.1%. Conclusion: The proposed method has better solution accuracy and faster convergence speed. The method was suitable for optimizing the rod parameters of the robot, and it was very meaningful to improve the motion performance of the robot.

BACKGROUND: Anlotinib is a new multi-target tyrosine kinase inhibitor (TKI) and has been shown to have antitumor effects and synergistic antitumor effects with immunotherapy only in animal studies and in the 2nd-line treatment in small clinical trials. A real-world study with large sample to compare the efficacy and safety of anlotinib plus immune checkpoint inhibitors (ICIs) with ICIs alone in the multiline treatment of advanced non-small cell lung cancer (NSCLC) was urgently needed. METHODS: The data of 535 advanced NSCLC patients were collected from January 1, 2018, to December 31, 2021. The patients were divided into 2 groups: (I) ICI monotherapy (230 patients); (II) ICI + anlotinib (305 patients). After propensity-score matching (PSM) to reduce the effects of biases and confounding variables, the progression-free survival time (PFS), occurrence of adverse events, disease control rate (DCR), and objective response rate (ORR) of the 2 groups were compared. The effects of clinical factors, including age, gender, gene mutations, tumor proportion score, metastases, and combined radiotherapy, were also analyzed. RESULTS: After PSM, the baseline clinical characteristics were well balanced and the 2 group had a good comparability. Patients in the ICI + anlotinib group had significantly longer median PFS in both the 2nd-line treatment (7.73 vs. 4.70 months; P=0.003) and 3rd-line treatment (5.90 vs. 3.37 months; P=0.020), but the difference lacked statistical significance in the 1st-line treatment (8.40 vs. 5.20 months; P=0.229). The overall median PFS of patients in the ICI + anlotinib group was also much longer than that of patients in the ICI monotherapy group (6.37 vs. 3.90 months; P

Background The aim of this study was to investigate the clinical efficacy of reaming and cement spacer implantation for the treatment of bone infection after intramedullary nailing. Methods Retrospective analysis the patients with lower extremities infection after intramedullary nailing admitted to our hospital between February 2013 and April 2020. In the first stage, reaming and cement spacer implantation were performed and the defects were filled with antibiotic cement spacer. In the second stage, the patients were divided into repaired group and non-repaired group according to whether the bone defects were repaired or not. The infection control rate and complications of the two groups were compared. Results A total of 69 patients were admitted to this study, there were 37 tibias and 32 femurs. The average follow-up time was 38.82 months. After the first stage debridement surgery. There were 6 patients in repaired group, and 8 patients in non-repaired group recurrence of infection which need debridement again, the infection rate of repaired group was lower than that of non-repaired group, P = 0.038. Finally, the overall infection control rate was 97.1%, which was 100% in repaired group and 91.30% in non-repaired group, P = 0.108. The overall complication rate was 17.39%, and there was no significant difference between the two groups. Conclusion The efficacy of reaming and cement spacer implantation for the treatment of bone infection after intramedullary nailing is satisfactory, but repeated debridement may be required to improve the infection control rate. The recurrence rate of infection was higher in patients who had not undergone bone defects repaired for a long time.

The empirical formula is one of the traditional methods used for predicting ground deformation settlement caused by tunnel excavation. Due to its rationality and simplicity, the Peck formula is widely used for predicting surface subsidence. However, due to its limitations, it is necessary to modify it when predicting surface settlement caused by tunnel excavation in different strata. In this paper, a correction formula for the width coefficient of a tunnel surface settlement slot is derived from the Peck formula by taking into account the theory of strata slip cracks. Values are calculated using the correction formula and compared with measured data to verify the effectiveness of the correction formula. The main conclusions are: (1) The position corresponding to the width of the settlement in the Peck curve is the point where the formation is most prone to slip cracking. (2) In the general shallow buried case, the settlement groove width coefficient K and the internal friction angle φ of the ground satisfy the formula K = 1/tan(45° + φ/2 + a) + b, and the values of parameters a and b reflect the average values of the geometric properties of the tunnel based on the measured data. (3) The prediction of the correction formula is consistent with the measured data, and thus the correction formula can be applied to problems related to the stability of shallow buried tunnels.

Plasmodesmata (PD) are plasma membrane (PM)-lined cytoplasmic nanochannels that mediate in cell-to-cell communication across the cell wall. A range of proteins are embedded in the PD PM and endoplasmic reticulum (ER) and function in regulating PD-mediated symplasmic trafficking. However, knowledge of the nature and function of the ER-embedded proteins, in the intercellular movement of non-cell-autonomous proteins, is limited. Here, we report the functional characterization of two ER luminal proteins, AtBiP1/2, and two ER integral membrane proteins, AtERdj2A/B, which are located within the PD. These PD proteins were identified as interacting proteins with Cucumber mosaic virus (CMV) movement protein (MP) in coimmunoprecipitation studies, using an Arabidopsis-derived plasmodesmal-enriched cell wall protein preparation (PECP). The AtBiP1/2 PD location was confirmed by transmission electron microscopy-based immunolocalization, and their AtBiP1/2 signal peptides (SPs) function in PD targeting. In vitro/in vivo pull-down assays revealed the association between AtBiP1/2 and CMV MP, mediated by AtERdj2A, through the formation of an AtBiP1/2-AtERdj2-CMV MP complex within PD. The role of this complex in CMV infection was established, as systemic infection was retarded in bip1/bip2w and erdj2b mutants. Our findings provide a model for a mechanism by which the CMV MP mediates in cell-to-cell trafficking of its viral ribonucleoprotein complex.

Background Glioma is the most common malignancy of the central nervous system. Fos-like antigen 1 (FOSL1) is overexpressed and acts as a tumor-promoting factor in glioma. However, the regulation of FOSL1 remains unknown. KLF14, a member of Kruppel-like factors that are involved gene transcription, plays an important role in the regulation of cell proliferation, differentiation and apoptosis. Loss of KLF14 triggers spontaneous tumorigenesis of lung, spleen and lymph node, suggesting its potential as biomarker for cancer. However, its role in glioma still needs to be deciphered. Therefore, we explore the interactions between FOSL1 and KLF14, as well as their role in glioma. Methods We first determined that FOSL1 can be transcriptional inhibited by KLF14 using dual-luciferase reporter gene assays and qPCR assays. Then, through immunohistochemistry (IHC)assay and western blotting (WB) assay in glioma tissues, we demonstrated a negative correlation between FOSL1 and KLF14. Next, KLF14 knockdown cells and double knockdown of KLF14 and FOSL1 cells were generated, and cell growth were detected by different experimental methods (MTT assay, crystal violet staining, cell migration assay). We then used qPCR and WB assay to search for and validate how KLF14 affects tumor cell migration through FOSL1. Finally, we confirmed the inhibition of tumor growth by KLF14 using xenograft tumor model. Results In this study, we showed that KLF14 inhibited the transcription of FOSL1.There is a negative correlation between KLF14 and FOSL1 in glioma tissues. Overexpression of KLF14 reversed the effect of FOSL1 in cell invasion, migration and epithelial-mesenchymal transition in glioma cells, and this was accompanied by the down-regulation of Snail2 and CD44. Moreover, KLF14 overexpression inhibits tumor progression in vivo. Conclusions The present results suggest that KLF14 is a new tumor molecular marker and a potential target for the treatment of glioma, providing a new target for anti-tumor drug research.

This study was designed to evaluate the impact of methicillin resistance on the outcomes among patients with S. aureus osteomyelitis. We reviewed all extremity osteomyelitis patients treated in our clinic center between 2013 and 2020. All adult patients with S. aureus pathogen infection were included. Clinical outcome in terms of infection control, length of hospital stay, and complications were observed at the end of a 24‐month follow‐up and retrospectively analyzed between populations with/without methicillin resistance. In total, 482 osteomyelitis patients due to S. aureus were enrolled. The proportion of methicillin-resistant S. aureus (MRSA) was 17% (82) and 83% (400) of patients had Methicillin-sensitive S. aureus (MSSA). Of 482 patients, 13.7% (66) presented with infection persistence after initial debridement and antibiotic treatment (6 weeks), needed repeated debridement, 8.5% (41) had recurrence after all treatment end and a period infection cure, complications were observed in 17 (3.5%) patients (pathologic fracture; 4, nonunion; 5, amputation; 8) at final follow-up. Following multivariate analysis, we found patients with S. aureus osteomyelitis due to MRSA are more likely to develop a persistent infection (OR: 2.26; 95% CI 1.24–4.13) compared to patients with MSSA. Patients infected with MRSA also suffered more complications (8.5% vs. 2.5%, p = 0.015) and longer hospital stays (median: 32 vs. 23 days, p S. aureus osteomyelitis. These results will help for patients counsel and preparation for treatment.