Learning Autonomous Ultrasound via Latent Task Representation and Robotic Skills Adaptation

As medical ultrasound is becoming a prevailing examination approach nowadays, robotic ultrasound systems can facilitate the scanning process and prevent professional sonographers from repetitive and tedious work. Despite the recent progress, it is still a challenge to enable robots to autonomously accomplish the ultrasound examination, which is largely due to the lack of a proper task representation method, and also an adaptation approach to generalize learned skills across different patients. To solve these problems, we propose the latent task representation and the robotic skills adaptation for autonomous ultrasound in this paper. During the offline stage, the multimodal ultrasound skills are merged and encapsulated into a low-dimensional probability model through a fully self-supervised framework, which takes clinically demonstrated ultrasound images, probe orientations, and contact forces into account. During the online stage, the probability model will select and evaluate the optimal prediction. For unstable singularities, the adaptive optimizer fine-tunes them to near and stable predictions in high-confidence regions. Experimental results show that the proposed approach can generate complex ultrasound strategies for diverse populations and achieve significantly better quantitative results than our previous method

PoseFusion: Robust Object-in-Hand Pose Estimation with SelectLSTM

Accurate estimation of the relative pose between an object and a robot hand is critical for many manipulation tasks. However, most of the existing object-in-hand pose datasets use two-finger grippers and also assume that the object remains fixed in the hand without any relative movements, which is not representative of real-world scenarios. To address this issue, a 6D object-in-hand pose dataset is proposed using a teleoperation method with an anthropomorphic Shadow Dexterous hand. Our dataset comprises RGB-D images, proprioception and tactile data, covering diverse grasping poses, finger contact states, and object occlusions. To overcome the significant hand occlusion and limited tactile sensor contact in real-world scenarios, we propose PoseFusion, a hybrid multi-modal fusion approach that integrates the information from visual and tactile perception channels. PoseFusion generates three candidate object poses from three estimators (tactile only, visual only, and visuo-tactile fusion), which are then filtered by a SelectLSTM network to select the optimal pose, avoiding inferior fusion poses resulting from modality collapse. Extensive experiments demonstrate the robustness and advantages of our framework. All data and codes are available on the project website: https://elevenjiang1.github.io/ObjectInHand-Dataset

Salesperson human capital investment and heterogeneous export enterprises performance

This paper aims to study the impact of salesperson human capital investment on the export performance of heterogeneous enterprises in China. To distinguish the different effects on the staff level and the management level, we define the human capital investment for the overall salespersons as human capital investment I and the human capital investment for the sales managers as human capital investment II, respectively measured by the salary of the ordinary salespersons and the ratio of expenses to sales. We find that human capital investment I has a significant positive effect on export performance, while human capital investment II shows a “positive U-shaped” relationship with export performance. Considering the heterogeneity of enterprise, the positive effect of human capital investment I is more significant than that of human capital investment II in enterprises with high R&D intensity. Moreover, with the improvement of technology intensity, both the promotion of human capital investment I and human capital investment II would generate greater influence on export performance

What contributes to medical debt? Evidence from patients in rural China.

BACKGROUND: Rural households in developing countries usually have severe medical debt due to high out-of-pocket (OOP) payments, which contributes to bankruptcy. China implemented the critical illness insurance (CII) in 2012 to decrease patients' medical expenditure. This paper aimed to explore the medical debt of rural Chinese patients and its influencing factors. METHODS: A questionnaire survey of health expenditures and medical debt was conducted in two counties of Central and Western China in 2017. Patients who received CII were used as the sample on the basis of multi-stage stratified cluster sampling. Descriptive statistics and multivariate analysis of variance were used in all data. A two-part model was used to evaluate the occurrence and extent of medical debt. RESULTS: A total of 826 rural patients with CII were surveyed. The percentages of patients incurring medical debt exceeded 50% and the median debt load was 20,000 Chinese yuan (CNY, 650 CNY = US$100). Financial assistance from kin (P < 0.001) decreased the likelihood of medical debt. High inpatient expenses (IEs, P < 0.01), CII reimbursement ratio (P < 0.001), and non-direct medical costs (P < 0.001) resulted in increased medical debt load. CONCLUSIONS: Medical debt is still one of the biggest problems in rural China. High IEs, CII reimbursement ratio, municipal or high-level hospitals were the risk determinants of medical debt load. Financial assistance from kin and household income were the protective factors. Increasing service capability of hospitals in counties could leave more patiemts in county-level and township hospitals. Improving CII with increased reimbursement rate may also be issues of concern

Effect of critical illness insurance on the medical expenditures of rural patients in China: an interrupted time series study for universal health insurance coverage.

OBJECTIVE: The objective of this study is to determine if critical illness insurance (CII) promotes the universal health coverage to reduce out-of-pocket (OOP) medical expenditures and improve the effective reimbursement rate (ERR) in rural China. STUDY DESIGN: The 5-year monthly hospitalisation data, starting 2 years before the CII (ie, the 'intervention') began, were collected. Interrupted time series analysis models were used to evaluate the immediate and gradual effects of CII on OOP payment and ERR. SETTING: The study was conducted in Xiantao County, Hubei Province, China. PARTICIPANTS: A total of 511 221 inpatients within 5 years were included in the analysis. RESULTS: In 2016, 100 288 patients received in-patient services, among which 4137 benefited from CII. After the implementation of CII, OOP expenses increased 32.2% (95% CI 24.8% to 39.5%, p<0.001). Compared with the preintervention periods, the trend changes decline at a rate of 0.7% per month after the implementation of CII. Similarly, a significant decrease was observed in log ERR after the intervention started. The rate of level change is 16% change (95% CI -20.0% to -12.1%, p<0.001). CONCLUSION: CII did not decrease the OOP payments of rural inpatients in 2011-2016 periods. The limited extents of population coverage and financing resources can be attributed to these results. Therefore, the Chinese government must urgently raise the funds of CII and improve the CII policy reimbursement rate

Identifying distinctive tissue and fecal microbial signatures and the tumor-promoting effects of deoxycholic acid on breast cancer

IntroductionA growing body of evidence indicates that the dysbiosis of both mammary and intestinal microbiota is associated with the initiation and progression of breast tumors. However, the microbial characteristics of patients with breast tumors vary widely across studies, and replicable biomarkers for early-stage breast tumor diagnosis remain elusive.MethodsWe demonstrate a machine learning-based method for the analysis of breast tissue and gut microbial differences among patients with benign breast disease, patients with breast cancer (BC), and healthy individuals using 16S rRNA sequence data retrieved from eight studies. QIIME 2.0 and R software (version 3.6.1) were used for consistent processing. A naive Bayes classifier was trained on the RDP v16 reference database to assign taxonomy using the Vsearch software.ResultsAfter re-analyzing with a total of 768 breast tissue samples and 1,311 fecal samples, we confirmed that Halomonas and Shewanella were the most representative genera of BC tissue. Bacteroides are frequently and significantly enriched in the intestines of patients with breast tumor. The areas under the curve (AUCs) of random forest models were 74.27% and 68.08% for breast carcinoma tissues and stool samples, respectively. The model was validated for effectiveness via cohort-to-cohort transfer (average AUC =0.65) and leave-one-cohort-out (average AUC = 0.66). The same BC-associated biomarker Clostridium_XlVa exists in the tissues and the gut. The results of the in-vitro experiments showed that the Clostridium-specific-related metabolite deoxycholic acid (DCA) promotes the proliferation of HER2-positive BC cells and stimulates G0/G1 phase cells to enter the S phase, which may be related to the activation of peptide-O-fucosyltransferase activity functions and the neuroactive ligand–receptor interaction pathway.DiscussionThe results of this study will improve our understanding of the microbial profile of breast tumors. Changes in the microbial population may be present in both the tissues and the gut of patients with BC, and specific markers could aid in the early diagnosis of BC. The findings from in-vitro experiments confirmed that Clostridium-specific metabolite DCA promotes the proliferation of BC cells. We propose the use of stool-based biomarkers in clinical application as a non-invasive and convenient diagnostic method

China Promotes Sanming’s Model: A National Template for Integrated Medicare Payment Methods

Introduction: China is promoting integrated care. However, incomplete payment methods led to medical insurance overspending and intensified service fragmentation. Sanming implemented Integrated Medicare Payment Methods (IMPM) in October 2017, which integrates multi-level payment policies. Sanming’s IMPM works well and has been promoted by the Chinese government. Therefore, in this paper, we aim to systematically analyze Sanming’s IMPM, and conduct preliminary evaluations of Sanming’s IMPM. Policy Description: IMPM integrates two levels of policy that are implemented simultaneously: (1) The payment policy for healthcare providers refers to how to calculate the global budget (GB) of the medical insurance fund paid to the healthcare providers and the policy guidance for the healthcare providers on how to use GB. (2) The payment policy for medical personnel refers to the adjustment of the evaluation index of the annual salary system (ASS) according to the IMPM’s purpose and the payment policy that adjust pay levels based on performance. Discussion and lessons learned: After the IMPM reform, county hospitals (CHs) may reduce over-providing dispensable healthcare, and cooperation between hospitals may increase. The policy guidance (Determining GB according to population; Medical insurance balance can be used for doctors’ salary, cooperation between hospitals, and promotion of residents’ health; Adjusting ASS assessment indicators according to IMPM purposes) increases CHs’ motivation to promote balances of medical insurance fund by cooperating with primary healthcare and increasing health promotion actions. Conclusion: As a model promoted by the Chinese government, the specific policies of Sanming’s IMPM are better matched with policy goals, which may be more conducive to promoting medical and health service providers to pay more attention to cooperation among medical institutions and population health

An examination of Alzheimer’s disease and white matter from 1981 to 2023: a Bibliometric and visual analysis

BackgroundAlzheimer’s disease (AD) is characterized by the presence of gray matter lesions and alterations in white matter. This study aims to investigate the research related to white matter in the context of AD from a Bibliometric standpoint.MethodsRegular and review articles focusing on the research pertaining to Alzheimer’s disease (AD) and white matter were extracted from the Web of Science Core Collection (WOSCC) database, covering the period from its inception to 10th July 2023. The “Bibliometrix” R package was employed to summarize key findings, to quantify the occurrence of top keywords, and to visualize the collaborative network among countries. Furthermore, VOSviewer software was utilized to conduct co-authorship and co-occurrence analyses. CiteSpace was employed to identify the most influential references and keywords based on their citation bursts. The retrieval of AD- and white matter-related publications was conducted by the Web of Science Core Collection. Bibliometric analysis and visualization, including the examination of annual publication distribution, prominent countries, active institutions and authors, core journals, co-cited references, and keywords, were carried out by using VOSviewer, CiteSpace, the Bibliometrix Package, and the ggplot2 Package. The quality and impact of publications were assessed using the total global citation score and total local citation score.ResultsA total of 5,714 publications addressing the intersection of Alzheimer’s disease (AD) and white matter were included in the analysis. The majority of publications originated from the United States, China, and the United Kingdom. Prominent journals were heavily featured in the publication output. In addition to “Alzheimer’s disease” and “white matter,” “mild cognitive impairment,” “MRI” and “atrophy” had been frequently utilized as “keywords.”ConclusionThis Bibliometric investigation delineated a foundational knowledge framework that encompasses countries, institutions, authors, journals, and articles within the AD and white matter research domain spanning from 1981 to 2023. The outcomes provide a comprehensive perspective on the broader landscape of this research field

Zn-doped chitosan/alginate multilayer coatings on porous hydroxyapatite scaffold with osteogenic and antibacterial properties

Porous hydroxyapatite (HA) scaffolds prepared by three-dimensional (3D) printing have wide application prospects owing to personalized structural design and excellent biocompatibility. However, the lack of antimicrobial properties limits its widespread use. In this study, a porous ceramic scaffold was fabricated by digital light processing (DLP) method. The multilayer chitosan/alginate composite coatings prepared by layer-by-layer method were applied to scaffolds and Zn2+ was doped into coatings in the form of ion crosslinking. The chemical composition and morphology of coatings were characterized by scanning electron microscope (SEM) and X-ray photoelectron spectroscopy (XPS). Energy dispersive spectroscopy (EDS) analysis demonstrated that Zn2+ was uniformly distributed in the coating. Besides, the compressive strength of coated scaffolds (11.52 ± 0.3 MPa) was slightly improved compared with that of bare scaffolds (10.42 ± 0.56 MPa). The result of soaking experiment indicated that coated scaffolds exhibited delayed degradation. In vitro experiments demonstrated that within the limits of concentration, a higher Zn content in the coating has a stronger capacity to promote cell adhesion, proliferation and differentiation. Although excessive release of Zn2+ led to cytotoxicity, it presented a stronger antibacterial effect against Escherichia coli (99.4%) and Staphylococcus aureus (93%)

Micro- and macro-mechanical testing of grain boundary sliding in a Sn-Bi alloy

This project explores the fundamental mechanisms of grain boundary sliding (GBS) with an emphasis on its role in superplasticity, using both micro- and macro-mechanical testing methods. GBS plays an important role in the deformation of polycrystalline materials, especially at high homologous temperatures (above half of the melting point). Classical models for GBS (Rachinger sliding and Lifshitz sliding) assume that all grains and grain boundaries undergo the same process, but recent research has shown this is not true. Individual grain boundaries differ in their ability to participate in sliding and diffusion. Therefore, it is important to investigate the response of individual grain boundaries to stress. This project uses microcantilevers, loaded using a nanoindenter, to investigate the response to stress of individual grain boundaries in Sn-1%Bi, which is expected to exhibit GBS at room temperature. The response of individual grain boundaries are correlated with grain boundary characters determined using electron backscattered diffraction (EBSD). On the macroscopic scale, both in-situ and ex-situ shear tests are conducted to investigate the superplastic behaviour of this material. The strain rate sensitivity index of the material with a grain size of 8.5 μm is found to be around 0.45. Surface marker lines have quantitatively revealed grain boundary sliding. The investigation from surface studies is expanded to the interior of bulk material in 3D by conducting an in-situ tensile test coupled with diffraction contrast tomography (DCT) at a synchrotron facility. The microcantilever tests enable grain boundary sliding and diffusion creep to be investigated separately by varying the normal and shear stresses on the grain boundary plane. GBS is dependent on grain boundary structure (misorientation angle, rotation axis and grain boundary plane orientation). The microcantilever size is similar to the grain size used in the macro-mechanical tests. It is demonstrated that the shear stress for steady-state GBS is comparable in micro- and macro-tests. Grain neighbour switching events have been identified in the interior of bulk material in 3D for the first time.</p