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Graphene, hexagonal boron nitride (h-BN), and their heterostructures are promising thermal interface materials due to the outstanding thermal properties of graphene and h-BN. For the heterostructures, extensive work has mainly focused on the thermal transport of two-dimensional (2D) graphene/h-BN (GBN) in-plane heterostructures in which graphene and h-BN are bonded at the interface. In this study, we investigate the thermal conductivity of three-dimensional (3D) GBN van der Waals (vdW) heterostructures by means of nonequilibrium molecular dynamics (NEMD) simulations. Unlike the 2D GBN in-plane heterostructure, the 3D GBN vdW heterostructure consists of three layers where graphene is sandwiched by two h-BN sheets via vdW forces. Various techniques, including hydrogen-functionalization, vacancy defects, tensile strain, interlayer coupling strength, layer numbers of h-BN, size effect, and temperature, are extensively explored to find an effective route for the modulation of the thermal conductivity. It is found that the thermal conductivity of the triple-layer GBN vdW heterostructure is very sensitive to these extrinsic factors. Of these, hydrogen-functionalization is the most effective method. A low hydrogen coverage of 1% in the sandwiched graphene can lead to 55% reduction in the thermal conductivity of the vdW heterostructure. Vacancy defects on graphene exert a more significant effect on the thermal conductivity reduction for the vdW heterostructure than B or N vacancies in the outer h-BN layers. This work reveals the physical mechanism for manipulating the thermal transport along the GBN vdW heterostructures via structural modification and provides a useful guideline for designing novel thermal management devices based on the GBN vdW heterostructures. Refereed/Peer-reviewed

Studies have shown that most patients after PCI cannot adhere to the cardiac rehabilitation program. The survey found that due to the lack of secondary prevention of cardiac rehabilitation, the phenomenon of drug reduction and withdrawal after PCI is very common after discharge, leading to recurrence of the patient’s disease or worsen and repeated hospitalizations, so continuity of care is very important. In this paper, in addition to proposing a network care continuum with artificial intelligence handler in order to improve the healthcare system and provide new ideas for improving the postoperative recovery of CHD patients, we analyze the impact of PCI on the coronary heart disease patients’ PCI postoperative quality of life. In the method part, this article introduces the concepts of continuation care and PCI after surgery, introduces the marker delivery algorithm in the field of artificial intelligence, and introduces the SF-36 scale for patient quality of life analysis. This article designs an experiment combining artificial intelligence processors to carry out network continuity care for patients and divides 100 eligible patients into an experimental group and a control group. In the analysis part, the two groups of patients were analyzed in terms of general data comparison, physical function, biochemical indicators, quality of life, and dependence. It can be seen from the experimental analysis that the anxiety and depression of the two groups of subjects have different degrees of decline. The HAMA value of the experimental group is 9.06 ± 0.77 , and the HAMD value is 9.18 ± 1.20 , which is significantly lower than that of the control group, P < 0.05 . It can be seen that the use of network continuation care can reduce the negative emotions of patients more than general care. Through psychological counseling and postoperative follow-up, it can improve the optimism and positive emotions of the patients, reduce the negative emotions of the patients, and improve it to a certain extent.

As industry is the world's leading carbon emitter, promoting industrial carbon reduction is of key significance to carbon peak and carbon neutrality. Using a data-driven method, based on the collection and processing of relevant data from statistical yearbooks and others, we analyze the efficiency and amount of carbon emission of each industrial sector after processing multi-dimensional data by the improved IPCC EF method of calculating carbon emissions. In addition, we adopt the LMDI decomposition method for data modeling to measure the contribution of energy efficiency, industrial structure, GDP per capita, and population size to carbon emission changes, to identify targets for industrial carbon reduction, and to propose a targeted optimization path for carbon emission. We show how the method is implemented by taking the statistics of Anhui Province from 2010 to 2019 as an example and advises on an optimization path for carbon emission in Anhui Province. This study is of both theoretical and practical significance as it provides theoretical and methodological support for the low-carbon development of the regional industry, and provides a reference for other countries and regions to explore the path of low-carbon and environment-friendly green transformation and upgrading.

Background Osteoporosis and arthritis are two common orthopedic diseases in the general population, with multiple common risk factors. The purpose of this study was to evaluate the correlation between osteoporosis (OP) and arthritis.Methods This cohort study included 13,310 eligible participants aged over 40 years with valid data on hypertension and arthritis from the National Health and Nutrition Examination Survey (NHANES) 2005–2020 (pre-pandemic). The association between osteoporosis and arthritis was studied by logistic regression, adjusted for demographic, socioeconomic factors, insufficient calcium intake, physical activity, smoking history, hypertension, diabetes, body mass index (BMI), blood calcium levels, blood phosphorus levels, and blood uric acid levels.Results Among the participants, 10267 (77.14%) had osteopenia or osteoporosis, and 4230 (31.78%) had self-reported arthritis. Osteoporosis was associated with arthritis [OR = 2.388, (95% CI: 2.111–2.702), P Conclusions In this large nationally representative survey, arthritis (including RA and OA) is closely related to osteoporosis. Our study shows that patients with arthritis need osteoporosis screening and bone mineral density monitoring.

In this study, a data-driven way is proposed to evaluate and optimize the sustainable development of the logistics industry (LI). Based on a comprehensive consideration of economic, societal, and environmental factors, an evaluation index system was established for the sustainable development of the logistics industry (LISD). Logistics industry-related data were collected from the Yangtze River Delta (YRD) from 2011 to 2020. The anti-entropy method was used to determine the index weight and process the data. Furthermore, the coupling harmonization degree and barrier degree models were used to analyze the coordinated development of each subsystem and identify key obstacles. Our results indicate that there are significant temporal and spatial differences in the level of LISD in YRD, with Shanghai (score 0.4834) being the best and Anhui (score 0.4553) the worst, showing a wave-like evolution in time. The coupling and coordination states among the subsystems are significantly different, with that of environmental benefits and other subsystems being poor. Moreover, innovation ability and environmental benefits are the main obstacle factors of this system. Based on the results of this study, targeted optimization countermeasures are put forward and evaluation indicators and research methods are suggested, which will provide the government and practitioners decision support, as well as provide theoretical and methodological support for LISD.

Graphene is a two-dimensional material that can be folded into diverse and yet interesting nanostructures like macro-scale paper origami. Folding of graphene not only makes different morphological configurations but also modifies their mechanical and thermal properties. Inspired by paper origami, herein we studied systemically the effects of creases, where sp2 to sp3 bond transformation occurs, on the thermal properties of graphene origami using molecular dynamics (MD) simulations. Our MD simulation results show that tensile strain reduces (not increases) the interfacial thermal resistance owing to the presence of the crease. This unusual phenomenon is explained by the micro-heat flux migration and stress distribution. Our findings on the graphene origami enable the design of the next-generation thermal management devices and flexible electronics with tuneable properties.

This study aims to promote the high-quality development of regional agriculture. This study proposes a data-driven method for regional agricultural analysis and evaluation. Based on the data collection and processing related to regional agricultural development, the location entropy index was used to analyze the industrial agglomeration level, and the shift-share model was constructed to evaluate the industrial structure and competitiveness. Based on the above analysis and evaluation, high-quality development policy suggestions for regional agriculture were provided. Taking the agricultural development of the Yangtze River Delta from 2010 to 2019 as an example, this study shows the implementation process of the method. From the perspective of high-quality agricultural development in the Anhui Province, this paper proposes policy suggestions on industrial structure adjustment and promoting competitiveness. This study provides theoretical and methodological support for the development of high-quality regional agriculture.

This study aimed to explore the influence of clinical pathway combined with high-quality nursing on endometrial cancer (EC) patients undergoing radical resection. Methods: A total of 116 EC patients who underwent surgery in our hospital from July 2017 to December 2019 were randomized into control group (CG) and observation group (OG). The CG (n=58) took routine nursing mode, while the OG (n=58) received clinical pathway combined with high-quality nursing. The postoperative recovery, psychological emotion and quality of life of the two groups were observed. Results: The postoperative recovery, psychological emotion and quality of life of the OG were better than those of the CG. Conclusion: Clinical pathway combined with high-quality nursing can effectively improve the quality of life and postoperative recovery of EC patients after radical resection.

Graphene reinforced metal matrix composites (MMCs) have received extensive research interests as promising structural materials in developing lightweight structures. The mechanical performance of such composites, however, is considerably hindered by weak van der Waal (vdW) interaction between graphene and metal matrix. The present work shows that this challenging issue can be effectively alleviated by the use of chemically functionalized graphene fillers with mechanically induced wrinkles. Our extensive molecular dynamics (MD) simulations on graphene reinforced copper (Cu) composite manifest that the presence of shear-induced wrinkles and chemical modification of graphene using functional groups can significantly increase its surface roughness, enhance the vdW interaction and consequently lead to higher interfacial shear strength (IFSS) between graphene and Cu matrix. Compared with its counterpart functionalized with hydrogen, graphene functionalized with alkyl (methyl, ethyl, propyl, and butyl) offers better interfacial interactions with Cu matrix because these functional groups are longer than hydrogen functional group and can be embedded deeper into the matrix.

Industrial ecological efficiency is regarded as an urgent challenge that affects the development of ecological civilization and environmental governance. Here, we propose a data-driven approach to measure and promote regional industrial ecological efficiency. We collected data related to regional industrial development and used the Data Envelopment Analysis-Banker Charnes and Cooper (DEA-BCC) model to measure regional industrial ecological efficiency from a static perspective. The Malmquist index model was then used to measure regional industrial ecological efficiency from a dynamic perspective. In addition, we used a Tobit regression model to identify the factors affecting regional industrial ecological efficiency. Through a case study of regional industrial ecological efficiency, we demonstrate the specific application of the proposed data-driven approach. This study provides a new and effective tool for improving industrial ecological efficiency at a regional scale. This method can help enterprises and local governments improve industrial ecological efficiency, coordinate the relationship between industrial economic growth and the ecological environment, and boost regional efforts to achieve carbon peaking and carbon neutralization goals.

Graphene has been widely used as new generation reinforcing nanofiller to achieve significantly improved mechanical properties in composites. However, its reinforcing effect has been considerably affected by the poor interfacial strength between graphene and the matrix. By using molecular dynamics simulations, the present work explores an effective route to improve the interfacial shear strength (ISS) of graphene sheets through the introduction of mechanically induced wrinkles that are formed by applying shear/compressive strains to graphene. The slide-out tests of a wrinkled graphene sliding over the graphene substrate show that the strain-induced wrinkles in graphene slider gives rise to larger surface roughness which leads to stronger interfacial interactions between graphene layers and consequently, significant improvement in ISS. Compared with compression induced wrinkles, shear induced wrinkles are found to be much more effective in enhancing ISS. Our results indicate that applying mechanical pre-strain, in particular, shear strain to graphene is a very useful strategy to improve its reinforcing effect in composites.

Graphene origami (G-ori) can possess unique mechanical properties and achieve some distinctive functionalization by engineering their configurations. However, it remains a tremendous challenge to modulate its formation and properties at the micro- and nano-scales. Herein, we systemically present the formation of G-ori activated by creased marks via molecular dynamics (MD) simulations. The pre-existing creased mark in graphene is created in a controlled way by transforming sp2 to sp3 bonds at the crease. Our results show that the presence of interlayer sp3 bonds at the crease can direct crack growth and hence pave a new way to tailor graphene sheets into specified pieces. The crease also guides the folding process of graphene into various geometric configurations. Sophisticated G-ori can be constructed by designing rational crease distribution on the graphene surface. Checking against the folding process of paper origami shows that the crease-induced targeted folding can be achieved at both nano- and macro-scales in exactly the same way. Our findings provide a simple and feasible method to construct graphene-based nano-devices by designing rational morphological configurations of G-ori.

Though graphene is the strongest material in nature, its intrinsic brittleness hinders its applications where flexibility is the key figure of merits. In this work, we report the enhanced flexibility of graphene under nanoindentation by using kirigami technique. Based on molecular dynamics simulations, we find that graphene kirigami designed at the optimal cut parameter can sustain more than 45% larger out-of-plane deformation than its pristine counterpart while the maximum impact load is reduced by 20% due to the flexible cut edges. This trade-off between flexibility and strength in a graphene kirigami can be overcome by adding a pristine graphene as a supporting substrate. This double-layer structure consisting of one graphene kirigami and one pristine graphene can stand the maximum impact load three times larger than the single-layer graphene kirigami but its maximum indentation depth is merely 8% smaller. Our simulation results provide useful insights into the failure mechanism of the graphene kirigami under nanoindentation and useful guidelines to enhancing the flexibility of graphene for its applications as protection materials.

This study aims to effectively reduce carbon emissions by selecting the low-carbon technology service emission reduction modes. This paper constructs a revenue-sharing contract model based on game theory. The purpose of this paper is to analyze the choice of carbon emission reduction strategies for carbon emission-dependent manufacturers and low-carbon technology service providers with advance funding risk aversion. This study analyzes the effects on the optimal decision-making and profits of both parties of the degree of risk aversion and the investment cost coefficient of carbon emissions reduction for service providers, and initial carbon emissions of manufacturers. The optimal carbon emissions reduction strategy of manufacturers and service providers with numerical analysis is obtained, and the revenue-sharing contract coordination is realized. Finally, the validity of the contract is verified by simulation analysis. The results show that manufacturers and service providers can only achieve optimal cooperation for emission reduction within a certain range of parameters. With different investment cost coefficients of carbon emissions reduction and with different initial carbon emissions, manufacturers will adjust the fixed emissions reduction fee and the revenue-sharing coefficient to encourage service providers to offer the optimal carbon emissions reduction rate. This study enriches theoretical research on low-carbon service chains. It also provides important practical evidence to help manufacturers and service providers choose optimal strategies for coordinating revenue-sharing contracts.

Thermal rectification is of great importance in various thermal management and thermal logic applications, where heat flux runs preferentially in one direction over the opposite one. This phenomenon is mostly reported in previous simulations and experiments by introducing asymmetry shape-tailoring, defects and doping, etc. However, these approaches break the structure of the heat conductor. In this paper, we report thermal rectification induced by modulating the substrate stiffness on the supported graphene, which preserves structural integrity of graphene, making it reusable. Our results show that the heat flux prefers to flow toward the stiffer part of a substrate. The maximum thermal rectification factor can reach ∼48% by using the ideal substrate model prediction. Moreover, a wide range thermal rectification factor of 3.5%–22.7% can be achieved by using a sandwich model. These phenomena are explained by phonon vibration spectra and excitation simulations. Our results should be of great help for understanding the modulation of thermal rectification in supported material and shed light on the design of a new thermal logic gate and thermal management devices.

Directional motion plays a crucial role in various mechanical systems. Although mechanisms for nanoscale directional motion have been widely used in many aspects of nanotechnology, it remains a great challenge to generate continuous and controllable motion at the nanoscale. Herein, we propose a nanoscale continuous directional motion in cyclic thermal fields by using a double-walled system which consists of an outer BN/C heterojunction nanotube and a concentric inner carbon nanotube (CNT). By manipulating the heating regions of the outer BN/C heterojunction tube, the continuous motion of the inner CNT can be realized with ease. The inner CNT demonstrates three distinct movements due to the joint actions of the asymmetric thermal gradient forces and interlayer attraction forces caused by the presence of the outer BN/C heterojunction nanotube. The mechanism revealed in the present study may be useful in designing novel devices for energy conversion and directional transportation.

This study aims to promote the high-quality development of regional agriculture. This study proposes a data-driven method for regional agricultural analysis and evaluation. Based on the data collection and processing related to regional agricultural development, the location entropy index was used to analyze the industrial agglomeration level, and the shift-share model was constructed to evaluate the industrial structure and competitiveness. Based on the above analysis and evaluation, high-quality development policy suggestions for regional agriculture were provided. Taking the agricultural development of the Yangtze River Delta from 2010 to 2019 as an example, this study shows the implementation process of the method. From the perspective of high-quality agricultural development in the Anhui Province, this paper proposes policy suggestions on industrial structure adjustment and promoting competitiveness. This study provides theoretical and methodological support for the development of high-quality regional agriculture.

This study develops a data-driven, comprehensive evaluation method to improve the science and technology innovative efficiency of industrial enterprises above designated size (hereinafter “industrial enterprises”). Based on an innovation value chain perspective, a two-stage evaluation index system is constructed. Thereafter, the Pearson correlation coefficient method was used to analyze correlations in the constructed index system. A two-stage network data envelopment analysis model with additional intermediate input was constructed to measure and evaluate industrial enterprises’ science and technology innovative efficiency from three aspects—research and development (R&D), commercialization, and comprehensive efficiencies—to reveal the temporal and spatial evolution. The feasibility and effectiveness of the method was verified using the statistical data of industrial enterprises in 16 cities in Anhui Province, China, from 2011 to 2020. The results show that the comprehensive efficiency of the scientific and technological innovation of industrial enterprises in these cities is at a medium level, and the efficiency development of the two stages is uncoordinated; the two-stage efficiency distribution tends to be “high R&D–high commercialization” and “low R&D–low commercialization”, and targeted countermeasures and suggestions are proffered. This study provides a reference for the sustainable development of industrial enterprises in relevant regions.

Using molecular dynamics (MD) simulations, we investigate the mechanical properties of hexagonal BCN monolayer, a newly synthesized two-dimensional material with an atom ratio of B/C/N = 1:1:1. The Tersoff potential is modified to get good agreement between predicted and measured fracture strengths of graphene. With this modified Tersoff potential, we perform extensive MD simulations to study the effect of temperature, strain rate and vacancy defect on the mechanical properties of h-BCN. It is found that h-BCN is a strong material with fracture strength of 81.4–93.5 GPa, albeit ∼35% lower than that of graphene. Similar to graphene, temperature has strong effect on the mechanical properties of h-BCN. As the temperature increases from 10 K to 1300 K, the fracture strength and strain of h-BCN drops by 55% and 62%, respectively. The strain rate is found to have a moderate effect. When the strain rate increases from 0.00002 to 0.0125 ps−1, the fracture strength and strain of h-BCN increases 6.1% and 12%, respectively. As for the atomic defect, a very small concentration (0.028%) of vacancy in h-BCN is able to cause a 28% reduction in fracture strength and a 35.5% reduction in fracture strain. These findings have significance for its future applications in nanodevices.