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The violent swinging motion of a payload imposes significant safety problems for the operation of offshore ship-mounted cranes (offshore cranes). We therefore propose a stable experimental hoisting platform for an offshore crane payload positioning system with a parallel cable-driven method (PP-PCDM), and an adaptive cable-drive anti-swing tension (ACAT) control method based on the PP-PCDM is developed to resolve the problem of swinging of the payload by limiting its spatial position. The PP-PCDM enables synchronous tracking of the movement of the payload when the crane is working. When the payload deviates from a stable state due to an external disturbance, the anti-swing cables are immediately retracted or released based on the feedback signal. The spatial position of the payload is then limited by adjusting the length and tension of the parallel cables until the payload appears stationary from the perspective of the ship’s deck. Operational safety and efficiency is substantially improved, and the proposed PP-PCDM structure and ACAT control method can be applied to a variety of different types of cranes. The results of simulations and physical experiments show that the anti-swing effect exceeds 89.86%. The PP-PCDM enables excellent performance of synchronous tracking and hoisting assistance, and ensures that the rated lifting weight of the offshore crane is not affected.

Lung cancer is the malignant tumor with the highest incidence and mortality rate in China, and surgical resection is a crucial approach for its treatment. In 2023, significant advancements were made in the field of lung cancer surgery. Firstly, CALGB140503 showed that for peripheral ≤2 cm nodular lung cancer, sublobar resection demonstrated no significant difference in survival rates compared to lobectomy, establishing the foundation for its role in early lung cancer treatment. Secondly, JCOG1211 found that segmentectomy could be used to treat 2-3 cm ground-glass opacity-predominant adenocarcinoma, however, patient in this study may undergo overtreatment, which could potentially be mitigated through intraoperative rapid frozen section pathological examination. Furthermore, the ECTOP-1003 study proposed a selective lymph node dissection strategy based on tumor location and intraoperative rapid frozen section pathological examination, achieving a 100% accuracy rate and providing a more precise approach to lymph node dissection. Additionally, the exploration of the cure time window for lung adenocarcinoma was remarkable, emphasizing the importance of timing in surgical intervention to avoid overtreatment in early lung cancer treatment. Finally, the ECTOP-1008 study demonstrated that high-resolution chest computed tomography (CT) scans assisted in determining the pathological invasion degree of lung cancer, aiding in the precise judgment of curative time window. This review summarized the important research progress in the field of lung cancer surgery in 2023, aiming to provide insights for clinical practice and future trials in lung cancer surgery.

PURPOSE: Although NRG1 fusions are oncogenic drivers across multiple tumor types including lung cancers, these are difficult to study because of their rarity. The global eNRGy1 registry was thus established to characterize NRG1 fusion-positive lung cancers in the largest and most diverse series to date. METHODS: From June 2018 to February 2020, a consortium of 22 centers from nine countries in Europe, Asia, and the United States contributed data from patients with pathologically confirmed NRG1 fusion-positive lung cancers. Profiling included DNA-based and/or RNA-based next-generation sequencing and fluorescence in situ hybridization. Anonymized clinical, pathologic, molecular, and response (RECIST v1.1) data were centrally curated and analyzed. RESULTS: Although the typified never smoking (57%), mucinous adenocarcinoma (57%), and nonmetastatic (71%) phenotype predominated in 110 patients with NRG1 fusion-positive lung cancer, further diversity, including in smoking history (43%) and histology (43% nonmucinous and 6% nonadenocarcinoma), was elucidated. RNA-based testing identified most fusions (74%). Molecularly, six (of 18) novel 5 partners, 20 unique epidermal growth factor domain-inclusive chimeric events, and heterogeneous 5/3 breakpoints were found. Platinum-doublet and taxane-based (post-platinum-doublet) chemotherapy achieved low objective response rates (ORRs 13% and 14%, respectively) and modest progression-free survival medians (PFS 5.8 and 4.0 months, respectively). Consistent with a low programmed death ligand-1 expressing (28%) and low tumor mutational burden (median: 0.9 mutations/megabase) immunophenotype, the activity of chemoimmunotherapy and single-agent immunotherapy was poor (ORR 0%/PFS 3.3 months and ORR 20%/PFS 3.6 months, respectively). Afatinib achieved an ORR of 25%, not contingent on fusion type, and a 2.8-month median PFS. CONCLUSION: NRG1 fusion-positive lung cancers were molecularly, pathologically, and clinically more heterogeneous than previously recognized. The activity of cytotoxic, immune, and targeted therapies was disappointing. Further research examining NRG1-rearranged tumor biology is needed to develop new therapeutic strategies.

This paper proposes a three degrees of freedom parallel anti-swing method by the main and auxiliary cables to address the problems related to underactuated double-pendulum anti-swing for a ship-mounted jib crane. By analysing the dynamic coupling relationship between the swing of the hook and the payload, it seeks to establish an accurate dynamic model of the anti-swing device under the ship’s rolling and pitching conditions, and discusses the influence of ship excitation, the crane state, load posture and anti-swing parameters on the in-plane and out-of-plane swing angles. The analysis shows that the primary pendulum reduces the in-plane angle by 90% and the out-of-plane angle by 80%, the in-plane angle of the secondary pendulum is reduced by 90%, and the out-of-plane angle is reduced by 80%. The reliability of the simulation data is verified through experiments.

Electrochromic materials have good development prospect under the development concept of promoting low carbon and energy saving. In order to explore the efficient, simple and excellent preparation process, the polymer electrochromic film was prepared by the electrostatic spray method combined with the in-situ elution method. According to the color adaptability and solubility of the electrolyte salt, tetrabutylammonium perchlorate (TBAP) was selected as the template, and different proportions of electrolyte salt were added to the easy-to-process TPA-OMe-PA solution, then film was deposited on the surface of the ITO glass by electrostatic spray technology. After that, the electrolyte salt was precipitated by in-situ washing method. The morphology of the film was analyzed using scanning electron microscope, and the electrochromic properties of the film were studied using the electrochemical workstation combined with ultraviolet/visible/infrared spectrometer. The research results show that the polymer film prepared by electrostatic spray technology and in-situ elution method have multi-level pore structure and excellent electrochromic properties. Especially when the electrolyte content is 33.3%(mass fraction), the multi-layer porosity is the highest, and the electrochromic performance is the best. The bleaching time/coloration time is reduced to 0.6 s/1 s, and the coloration efficiency reaches 608.2 cm2·C-1, which is the best record for the polyamide based electrochromic film.

Background and purpose: We analyzed the distribution of metastatic sites and survival of lung cancer patients with metastases based on hospital registration to provide real-world data support for the treatment and survival management of lung cancer patients. Methods: A total of 1 490 lung cancer patients who developed metastasis during the follow-up in Fudan University Shanghai Cancer Center from 2008 to 2017 were enrolled in this study. Medical records review, telephone visits and death registry data linkage were applied in collecting endpoint data. The effects of age at diagnosis, gender and histological subtype on the distribution of metastases were studied. The Kaplan-Meier method was used to evaluate the overall survival (OS) rates of different metastatic sites. Results: The median follow-up time was 40.8 months. During the follow-up period, 937 cases died from all causes. 67.7% of patients only had single-site metastasis, while 32.3% of patients had multiple-site metastases. The common metastatic sites were bone (33.8%), brain (33.6%), lung (22.8%), liver (12.0%) and adrenal gland (3.7%). Female patients had more metastases to brain (37.8% vs 31.4%). Younger patients were more likely to develop multiple-site metastases, and small cell carcinomas patients had more brain metastases (47.2%) and liver metastases (20.9%). Lung metastasis featured relatively best survival (1-year OS rate: 78.3%, 3-year OS rate: 47.1%, 5-year OS rate: 29.5%), whereas liver metastasis had relatively the worst prognosis (1-year OS rate: 46.4%, 3-year OS rate: 15.2%, 5-year OS rate: 3.6%). Conclusion: The proportions of bone and brain metastases in lung cancer patients with metastasis are high. The distribution of metastatic sites is associated with gender, age at diagnosis and histological type. The prognosis of patient with different metastatic sites is different. Mechanisms or clinical treatment plans can be studied for different metastatic sites to improve the prognosis of late-stage lung cancer patients in future research.

Functional connectivity (FC) obtained from resting-state functional magnetic resonance imaging has been integrated with machine learning algorithms to deliver consistent and reliable brain disease classification outcomes. However, in classical learning procedures, custom-built specialized feature selection techniques are typically used to filter out uninformative features from FC patterns to generalize efficiently on the datasets. The ability of convolutional neural networks (CNN) and other deep learning models to extract informative features from data with grid structure (such as images) has led to the surge in popularity of these techniques. However, the designs of many existing CNN models still fail to exploit the relationships between entities of graph-structure data (such as networks). Therefore, graph convolution network (GCN) has been suggested as a means for uncovering the intricate structure of brain network data, which has the potential to substantially improve classification accuracy. Furthermore, overfitting in classifiers can be largely attributed to the limited number of available training samples. Recently, the generative adversarial network (GAN) has been widely used in the medical field for its generative aspect that can generate synthesis images to cope with the problems of data scarcity and patient privacy. In our previous work, GCN and GAN have been designed to investigate FC patterns to perform diagnosis tasks, and their effectiveness has been tested on the ABIDE-I dataset. In this paper, the models will be further applied to FC data derived from more public datasets (ADHD, ABIDE-II, and ADNI) and our in-house dataset (PTSD) to justify their generalization on all types of data. The results of a number of experiments show the powerful characteristic of GAN to mimic FC data to achieve high performance in disease prediction. When employing GAN for data augmentation, the diagnostic accuracy across ADHD-200, ABIDE-II, and ADNI datasets surpasses that of other machine learning models, including results achieved with BrainNetCNN. Specifically, in ADHD, the accuracy increased from 67.74% to 73.96% with GAN, in ABIDE-II from 70.36% to 77.40%, and in ADNI, reaching 52.84% and 88.56% for multiclass and binary classification, respectively. GCN also obtains decent results, with the best accuracy in ADHD datasets at 71.38% for multinomial and 75% for binary classification, respectively, and the second-best accuracy in the ABIDE-II dataset (72.28% and 75.16%, respectively). Both GAN and GCN achieved the highest accuracy for the PTSD dataset, reaching 97.76%. However, there are still some limitations that can be improved. Both methods have many opportunities for the prediction and diagnosis of diseases. [ABSTRACT FROM AUTHOR]