E-PVT: enhanced position-velocity-time scheduler for computer-controlled optical finishing with comprehensive considerations of dynamics constraints, continuity and efficiency.

Deterministic computer-controlled optical finishing is an essential approach for achieving high-quality optical surfaces. Its determinism and convergence rely heavily on precise and smooth motion control to guide the machine tool over an optical surface to correct residual errors. One widely supported and smooth motion control model is position-velocity-time (PVT), which employs piecewise cubic polynomials to describe positions. Our prior research introduced a PVT-based velocity scheduling method, demonstrating sub-nanometer level convergence in ion beam figuring (IBF) processes. However, three challenges remained. Firstly, this method relies on quadratic programming, resulting in computational intensiveness for dense tool paths. Secondly, the dynamics constraints and velocity and acceleration continuities are not comprehensively considered, limiting the full potential of PVT-based control. Thirdly, no compensation mechanism existed when dynamics constraints are exceeded. In this study, in response to these challenges, we proposed the Enhanced PVT (E-PVT) method, reducing the time complexity from O(n3) to O(n) while fully addressing dynamics constraints and continuities. A novel compensation method utilizing particle swarm optimization was proposed to address situations where dynamics constraints might be exceeded while maintaining the overall processing efficiency. Validation through simulation and experimentation confirmed the improved performance of E-PVT.

Automatic planning of maxillary anterior dental implant based on prosthetically guided and pose evaluation indicator.

PURPOSE: Preoperative planning of maxillary anterior dental implant is a prerequisite to ensuring that the implant achieves the proper three-dimensional (3D) pose, which is essential for its long-term stability. However, the current planning process is labor-intensive and subjective, relying heavily on the surgeon's experience. Consequently, this paper proposes an automatic method for computing the optimal pose of the dental implant. METHODS: The method adopts the principle of prosthetically guided dental implant placement. Initially, the prosthesis coordinate system is established to determine the implant candidate orientations. Subsequently, virtual slices of the maxilla in the buccal-palatal direction are generated according to the prosthesis position. By extracting feature points from the virtual slices, the implant candidate starting points are acquired. Then, a candidate pose set is obtained by combining these candidate starting points and orientations. Finally, a pose evaluation indicator is introduced to determine the optimal implant pose from this set. RESULTS: Twenty-two cases were utilized to validate the method. The results show that the method could determine an ideal pose for the dental implant, with the average minimum distance between the implant and the left tooth root, the right tooth root, the palatal side, and the buccal side being 2.57 ± 0.53 mm, 2.59 ± 0.65 mm, 0.74 ± 0.19 mm, 1.83 ± 0.16 mm, respectively. The planning time was less than 9 s. CONCLUSION: Unlike manual planning, the proposed method can efficiently and accurately complete maxillary anterior dental implant planning, providing a theoretical analysis of the success rate of the implant. Thus, it has great potential for future clinical application.

Risk assessment of deep-sea floating offshore wind power projects based on hesitant fuzzy linguistic term set considering trust relationship among experts.

The development of deep-sea floating offshore wind power (FOWP) is the key to fully utilizing water resources to enhance wind resources in the years ahead, and then the project is still in its initial stage, and identifying risks is a crucial step before promoting a significant undertaking. This paper proposes a framework for identifying risks in deep-sea FOWP projects. First, this paper identifies 16 risk criteria and divides them into 5 groups to establish a criteria system. Second, hesitant fuzzy linguistic term set (HFLTS) and triangular fuzzy number (TFN) are utilized to gather and describe the criterion data to ensure the robustness and completeness of the criterion data. Third, extending the method for removal effects of criteria (MEREC) to the HFLTS environment through the conversion of TFNs, under the influence of subjective preference and objective fairness, a weighting method combining analytic network process (ANP) and MEREC is utilized to calculate criteria weights, and the trust relationship and consistency between experts are used to calculate the expert weights to avoid the subjective weighting given by experts arbitrariness. Fourth, the study's findings indicated that the overall risk level of the deep-sea FOWP projects is "medium." Fifth, sensitivity and comparative analyses were conducted to test the reliability of the assessment outcomes. lastly, this research proposes risk management measures for the deep-sea FOWP project's establishment from economic, policy, technology, environment, and management aspects.

Effect of total flavonoids of Dracocephalum moldavica L. On neuroinflammation in Alzheimer's disease model amyloid-ß (Aß1-42)-peptide-induced astrocyte activation.

One of the main pathological features noted in Alzheimer's disease (AD) is the presence of plagues of aggregated ß-amyloid (Aß1-42)-peptides. Excess deposition of amyloid-ß oligomers (AßO) are known to promote neuroinflammation. Sequentially, following neuroinflammation astrocytes become activated with cellular characteristics to initiate activated astrocytes. The purpose of this study was to determine whether total flavonoids derived from Dracocephalum moldavica L. (TFDM) inhibited Aß1-42-induced damage attributed to activated C8-D1A astrocytes. Western blotting and ELISA were used to determine the expression of glial fibrillary acidic protein (GFAP), and complement C3 to establish the activation status of astrocytes following induction from exposure to Aß1-42. Data demonstrated that stimulation of C8-D1A astrocytes by treatment with 40 µM Aß1-42 for 24 hr produced significant elevation in protein expression and protein levels of acidic protein (GFAP) and complement C3 accompanied by increased expression and levels of inflammatory cytokines. Treatment with TFDM or the clinically employed drug donepezil in AD therapy reduced production of inflammatory cytokines, and toxicity initiated following activation of C8-D1A astrocytes following exposure to Aß1-42. Therefore, TFDM similar to donepezil inhibited inflammatory secretion in reactive astrocytes, suggesting that TFDM may be considered as a potential compound to be utilized in AD therapy.

A Spinal MRI Image Segmentation Method Based on Improved Swin-UNet.

As the number of patients increases, physicians are dealing with more and more cases of degenerative spine pathologies on a daily basis. To reduce the workload of healthcare professionals, we propose a modified Swin-UNet network model. Firstly, the Swin Transformer Blocks are improved using a residual post-normalization and scaling cosine attention mechanism, which makes the training process of the model more stable and improves the accuracy. Secondly, we use the log-space continuous position biasing method instead of the bicubic interpolation position biasing method. This method solves the problem of performance loss caused by the large difference between the resolution of the pretraining image and the resolution of the spine image. Finally, we introduce a segmentation smooth module (SSM) at the decoder stage. The SSM effectively reduces redundancy, and enhances the segmentation edge processing to improve the model's segmentation accuracy. To validate the proposed method, we conducted experiments on a real dataset provided by hospitals. The average segmentation accuracy is no less than 95%. The experimental results demonstrate the superiority of the proposed method over the original model and other models of the same type in segmenting the spinous processes of the vertebrae and the posterior arch of the spine.

The predictive value of the preoperative albumin-to-fibrinogen ratio for postoperative hospital length of stay in liver cancer patients.

BACKGROUND: Hepatocellular carcinoma (HCC) is a significant global health burden, with postoperative hospital length of stay (LOS) impacting patient outcomes and healthcare costs. Existing nutritional, inflammatory, and coagulation indices can predict LOS, with particular interest in albumin, fibrinogen, and D-dimer. This study investigates the predictive value of preoperative albumin-to-fibrinogen ratio (AFR) and albumin-to-D-dimer ratio (ADR) for postoperative LOS in HCC patients. METHODS: This retrospective study involved 462 adult HCC patients who underwent partial hepatic lesion excision between February 2016 and August 2022. We analyzed demographic and clinical data, including preoperative blood samples, surgical approach, and LOS. The primary outcome measure was LOS, calculated from the date of surgery to the date of hospital discharge. Preoperative AFR and ADR were calculated. The ROC curves determined optimal cutoff points. The Cox proportional hazards model, Kaplan-Meier method, and the log-rank test were used for statistical analysis. RESULTS: The study established an optimal AFR cutoff value of 15.474, with a higher AUC value than ADR, indicating superior predictive potential for postoperative LOS. Participants with high-AFR (AFR > 15.474) had a shorter median LOS (13 vs. 15 days, p < 0.001) compared to those with low-AFR (AFR ≤15.474). Multivariate analysis revealed high-AFR (HR: 1.99; p < 0.001) as a positive influence on LOS reduction, whereas Child-Pugh rated as B (HR: 0.49; p < 0.001), laparotomy (HR: 0.37; p < 0.001) and total bilirubin >20.5 µmol/L (HR: 0.58; p < 0.001) negatively impacted LOS reduction. Subgroup analysis confirmed AFR's predictive ability for patients experiencing reduced or prolonged LOS due to Child-Pugh score, surgical methods, and total bilirubin concentrations. Even within normal albumin and fibrinogen levels, patients with high-AFR exhibited a shorter LOS (all p < 0.001). CONCLUSIONS: Our findings underscore the value of the AFR as a reliable predictor of LOS in HCC patients. An AFR greater than 15.474 consistently correlated with a shorter LOS, suggesting its potential clinical utility in guiding perioperative management and resource allocation in HCC patients.

3D reconstruction for maxillary anterior tooth crown based on shape and pose estimation networks.

PURPOSE: The design of a maxillary anterior tooth crown is crucial to post-treatment aesthetic appearance. Currently, the design is performed manually or by semi-automatic methods, both of which are time-consuming. As such, automatic methods could improve efficiency, but existing automatic methods ignore the relationships among crowns and are primarily used for occlusal surface reconstruction. In this study, the authors propose a novel method for automatically reconstructing a three-dimensional model of the maxillary anterior tooth crown. METHOD: A pose estimation network (PEN) and a shape estimation network (SEN) are developed for jointly estimating the crown point cloud. PEN is a regression network used for estimating the crown pose, and SEN is based on an encoder-decoder architecture and used for estimating the initial crown point cloud. First, SEN adopts a transformer encoder to calculate the shape relationship among crowns to ensure that the shape of the reconstructed point cloud is precise. Second, the initial point cloud is subjected to pose transformation according to the estimated pose. Finally, the iterative method is used to form the crown mesh model based on the point cloud. RESULT: The proposed method is evaluated on a dataset with 600 cases. Both SEN and PEN are converged within 1000 epochs. The average deviation between the reconstructed point cloud and the ground truth of the point cloud is 0.22 mm. The average deviation between the reconstructed crown mesh model and the ground truth of the crown model is 0.13 mm. CONCLUSION: The results show that the proposed method can automatically and accurately reconstruct the three-dimensional model of the missing maxillary anterior tooth crown, which indicates the method has promising application prospects. Furthermore, the reconstruction time takes less than 11 s for one case, demonstrating improved work efficiency.

Knowledge and vaccination acceptance toward the human monkeypox among men who have sex with men in China.

Background: MSM individuals are at high risk of monkeypox infection, and judicious use of vaccines can control the outbreak. Therefore, we conducted a national cross-sectional survey to assess the vaccination willingness, associated factors, and related knowledges of monkeypox among MSM individuals in China. Methods: This anonymous cross-sectional study was conducted in China from July 1 to July 3, 2022, and electronic questionnaires were sent online to MSM individuals of specific institutions. Men, aged 18 or older, who had anal sex in the past year were recruited. Multivariable logistic regression models and univariable logistic regression models were performed in different groups of participants, including all eligible respondents, people with or without self-reported HIV infection, and people who had sex with at least one male sexual partner in last month. Results: A total of 2,618 male respondents, including 2,134 homosexuals and 484 bisexuals, were enrolled in our final analysis. Most of the respondents had a certain understanding of the source of infection, transmission route, and preventive measures, but lacked knowledge of the susceptible population, clinical manifestations, vaccination, and treatment. In total, 90.2% of all respondents were willing to receive the vaccines against monkeypox. Among people with self-reported HIV infection, the vaccination acceptance rate was 91.7%, while it was 89.7% in the rest. The main influencing factors were knowledge about monkeypox (moderate: aOR = 1.47, 95% CI: 1.04-2.08; high: aOR = 2.03, 95% CI: 1.23-3.34), knowledge about prevention measures (moderate: aOR = 3.52, 95% CI: 2.51-4.94; high: aOR = 5.32, 95% CI: 2.98-9.47), concerns about their susceptibility to monkeypox infection (aOR = 4.37, 95% CI: 3.29-5.80), and possible contact with people and animals in epidemic areas (aOR = 0.42, 95% CI: 0.25-0.70). For self-reported HIV-infected individuals, education (bachelor degree: aOR = 0.40, 95% CI: 0.18-0.89) and poor condom use (sometimes: aOR = 2.18, 95% CI: 1.06-4.47) may also affect the vaccination. Conclusions: There was still a lack of knowledge about the human monkeypox among MSM individuals in China. The vaccination acceptance rate of this high-risk population was high, and it was closely related to the knowledge factors, fear of infection, and possible contact with people or animals in affected areas. Targeted publicity and education of the high-risk groups, vaccination pre-arranged planning should be formulated to cope with the further development of this infectious disease.

Texture-less surface reconstruction using shape-based image augmentation.

The development of intelligent Robot-Assisted Minimally Invasive Surgery demands geometric reconstruction from endoscopic images. However, images of human tissue surfaces are commonly texture-less. Obtaining the dense depth map of a texture-less scene is very difficult because traditional feature-based 3D reconstruction methods cannot detect enough features to build dense correspondences for depth computation. Given this problem, this study proposes a novel reconstruction method based on our shape-based image augmentation method. The main contribution of this method is the provision of a novel means to resolve the texture-less problem mainly on the input data level. In our method, we first calculate two shape gradient maps using Shape-From-Shading (SFS) method and we build Fast Point Feature Histogram (FPFH) 3D descriptor map according to the shape. Second, a series of augmented images can be computed by combining shape gradient maps, FPFH map, and the original image with different weights. Finally, we detect features on the new augmented images. Based on feature calculated sparse depth information and SFS calculated dense shape information, we further integrate a rectified dense depth map. Experiments show that our method can reconstruct texture-less surfaces with good accuracy.

An image-guided hybrid robot system for dental implant surgery.

PURPOSE: Dental implant surgery is an effective method for remediating the loss of teeth. Robot is expected to increase the accuracy of dental implant surgery. However, most of them are industrial serial robot, with low stiffness and non-unique inverse kinematic solution, which may reduce the success rate and safety of robotic surgery. Compared to serial robot, parallel robot is more stiffness and has unique inverse kinematic. However, its workspace is small, which may not meet surgical requirements. Therefore, a novel hybrid robot dedicated to dental implant is proposed. METHODS: The hybrid robot is composed of three translation joints, two revolute joints, and Stewart parallel manipulator. Stewart is used for performing surgical operation, while the joints are used for enlarging the workspace of Stewart. In order to ensure the safety of robot motion, physical human-robot interaction based on a variable admittance controller is applied in the robotic system. In addition, considering the small workspace of Stewart, an optimal model is proposed to minimize the joint movement of Stewart in adjusting the orientation of drill bit. RESULTS: Phantom experiments were carried out based on the prototype robot. In the experiments, the optimal model could be solved after 20 iterations, finding an ideal joint configuration. The proposed variable admittance controller could enhance comfort level effectively. The accuracy of robot is evaluated by angle, entry and exit deviation, which are 0.74 ± 0.25°, 0.93 ± 0.28 mm, and 0.96 ± 0.23 mm, respectively. CONCLUSION: The phantom experiments validate the functionality of the proposed hybrid robot. The satisfactory performance makes it more widely used in the practical dental implant surgery in the future.

Multi-Dimension and Multi-Feature Hybrid Learning Network for Classifying the Sub Pathological Type of Lung Nodules through LDCT.

In order to develop appropriate treatment and rehabilitation plans with regard to different subpathological types (PILs and IAs) of lung nodules, it is important to diagnose them through low-dose spiral computed tomography (LDCT) during routine screening before surgery. Based on the characteristics of different subpathological lung nodules expressed from LDCT images, we propose a multi-dimension and multi-feature hybrid learning neural network in this paper. Our network consists of a 2D network part and a 3D network part. The feature vectors extracted from the 2D network and 3D network are further learned by XGBoost. Through this formation, the network can better integrate the feature information from the 2D and 3D networks. The main learning block of the network is a residual block combined with attention mechanism. This learning block enables the network to learn better from multiple features and pay more attention to the key feature map among all the feature maps in different channels. We conduct experiments on our dataset collected from a cooperating hospital. The results show that the accuracy, sensitivity and specificity of our network are 83%, 86%, 80%, respectively It is feasible to use this network to classify the subpathological type of lung nodule through routine screening.

Chlorine-Incorporation-Induced Formation of the Layered Phase for Antimony-Based Lead-Free Perovskite Solar Cells.

The environmental toxicity of Pb in organic-inorganic hybrid perovskite solar cells remains an issue, which has triggered intense research on seeking alternative Pb-free perovskites for solar applications. Halide perovskites based on group-VA cations of Bi3+ and Sb3+ with the same lone-pair ns2 state as Pb2+ are promising candidates. Herein, through a joint experimental and theoretical study, we demonstrate that Cl-incorporated methylammonium Sb halide perovskites (CH3NH3)3Sb2ClXI9-X show promise as efficient solar absorbers for Pb-free perovskite solar cells. Inclusion of methylammonium chloride into the precursor solutions suppresses the formation of the undesired zero-dimensional dimer phase and leads to the successful synthesis of high-quality perovskite films composed of the two-dimensional layered phase favored for photovoltaics. Solar cells based on the as-obtained (CH3NH3)3Sb2ClXI9-X films reach a record-high power conversion efficiency over 2%. This finding offers a new perspective for the development of nontoxic and low-cost Sb-based perovskite solar cells.

Enhanced Thermochemical Stability of CH3NH3PbI3 Perovskite Films on Zinc Oxides via New Precursors and Surface Engineering.

Hydroxyl groups on the surface of ZnO films lead to the chemical decomposition of CH3NH3PbI3 perovskite films during thermal annealing, which limits the application of ZnO as a facile electron-transporting layer (ETL) in perovskite solar cells. In this work, we report a new recipe that leads to substantially reduced hydroxyl groups on the surface of the resulting ZnO films by employing polyethylenimine (PEI) to replace generally used ethanolamine in the precursor solutions. Films derived from the PEI-containing precursors are denoted as P-ZnO and those from the ethanolamine-containing precursors as E-ZnO. Besides the fewer hydroxyl groups that alleviate the thermochemical decomposition of CH3NH3PbI3 perovskite films, P-ZnO also provides a template for the fixation of fullerene ([6,6]-phenyl-C61-butyric acid methyl ester, PCBM) owing to its nitrogen-rich surface that can interact with PCBM. The fullerene was used to block the direct contact between P-ZnO and CH3NH3PbI3 films and therefore further enhance the thermochemical stability of perovskite films. As a result, perovskite solar cells based on the P-ZnO/PCBM ETL yield an optimal power conversion efficiency (PCE) of 15.38%. We also adopt P-ZnO as the ETL for organic solar cells that yield a remarkable PCE of 10.5% based on the PBDB-T:ITIC photoactive layer.