The relationship of peripheral blood lncRNA-PVT1 and miR-146a levels with Th17/Treg cytokines in patients with Hashimoto's thyroiditis and their clinical significance.

Hashimoto's thyroiditis (HT) is a prevalent autoimmune disease. We investigated the relationship of peripheral blood long noncoding RNA-plasmacytoma variant translocation 1 (lncRNA-PVT1) and microRNA (miR)-146a levels with Th17/Treg-related cytokines in HT patients and their clinical significance. Correlations of lncRNA-PVT1 and miR-146a with Th17/Treg-related cytokines were analyzed, and its clinical value in diagnosing HT was assessed. Results showed reduced lncRNA-PVT1 and interleukin (IL)-10 levels and increased miR-146a and IL-17 levels in HT patients. lncRNA-PVT1 negatively interrelated with miR-146a, IL-17, IL-23 and IL-6, and positively interrelated with IL-10; miR-146a positively correlated with IL-17, IL-23 and IL-6, but negatively correlated with IL-10 in HT patients. The area under the curve (AUC) of lncRNA-PVT1 and miR-146a levels for diagnosing HT were 0.822 and 0.844, respectively (sensitivity 88.73% and 86.62%, specificity 67.02% and 69.15%, cut-off values 0.76 and 2.73), with their combined detections yielding a higher AUC. Patients with poorly expressed lncRNA-PVT1 and highly expressed miR-146a had elevated HT incidence. lncRNA-PVT1 and miR-146a levels were also found to be an independent influencing factor for HT occurrence. Our findings suggest that HT patients have low peripheral blood lncRNA-PVT1 expression and high miR-146a expression. lncRNA-PVT1 and miR-146a level changes were correlated with Th17/Treg cytokine imbalance and could be a potential diagnostic tool and independent influencing factor for HT.

Highly Sensitive Weaving Sensor of Hybrid Graphene Nanoribbons and Carbon Nanotubes for Enhanced Pressure Sensing Function.

Carbon nanotubes (CNTs) hold great promise in next-generation sensors because of their remarkable physical properties. Yet, maintaining precise stacking configurations of CNTs to make full use of their remarkable properties is challenging because of their susceptibility to spontaneous reconstruction. Inspired by the weaving technology, we propose a CNT-graphene nanoribbon hybrid woven model that can maintain the specific structure of CNTs to achieve their elaborately designed function. In this study, comprehensive molecular dynamics simulations are carried out to investigate the thermal stability of the CNT-graphene hybrid woven model, as well as their potential for pressure sensing applications by utilizing the unique response of thermal transport to mechanical deformation at heterojunctions. The thermal stability is sensitive to the size of the graphene nanoribbon, and the woven structure remains stable from 200-500 K when its width is greater than 2.0 nm. Moreover, it is exciting that the sensors are effective at predicting the shapes of externally loaded objects through the analysis of the thermal conductivity distribution, which can be derived from the relationship between the thermal conduction and the pressure. Our findings shed light on the bottom-up functional design of nanomaterials and expand wider applications of high-performance nanosensors in other related fields.

A data-driven approach for the measurement and improvement of regional industrial ecological efficiency for carbon peaking and carbon neutralization.

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.

Molecular Dynamics Simulation on In-Plane Thermal Conductivity of Graphene/Hexagonal Boron Nitride van der Waals Heterostructures.

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.

Analysis of the Influence of Network Continuous Care on the Quality of Life of Patients with Coronary Artery Disease (CAD) after PIC.

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.

Research on carbon emission measurement and low-carbon path of regional industry.

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.

Failure mechanism of graphene kirigami under nanoindentation.

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.

Data-driven evaluation and optimization of the sustainable development of the logistics industry: case study of the Yangtze River Delta in China.

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.

Low-carbon technology service mode with revenue-sharing contract considering advance funding risk.

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.

Data-driven analysis and evaluation of regional agriculture for high-quality development of Anhui Province in the Yangtze River Delta.

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.

Position effects of the graphene-origami actuators on the rotation of a CNT nanomotor.

This study designs a carbon nanotube (CNT)-based rotary nanomotor actuated by four graphene origami (G-ori) drivers with adjustable positions. When the drivers' tips have different contact states with the CNT rotor at a finite temperature, the rotor has different rotational states due to different interaction strength between the rotor and the tips. Using the molecular dynamics simulation approach, we study the effects of the drivers' position, such as the gaps between the rotor and the drivers' tips and their layout angles. Numerical results indicate that both the stable rotational frequency (SRF) and the rotational direction change with the layout angles. In an interval from -40° to -25°, the SRF increases monotonously. There also exists an angle interval in which the G-ori drivers fail to actuate the rotor's rotation. The gap offset leads to different SRF of the same rotor. Hence, one can design a rotary nanomotor with controllable rotation, which is critical for its applications in a nanomachine.

Long noncoding RNAs profiling in ovary during laying and nesting in Muscovy ducks (Cairina moschata).

There are recent reports of the important functions of long noncoding RNAs (lncRNAs) in female reproductive and ovarian development. Studies in which there was characterization of lncRNAs in the ovaries of laying compared with nesting poultry, however, are limited. In this study, RNA libraries were constructed by obtaining sequencing data of ovarian tissues from laying and nesting Muscovy ducks. In the ovarian tissues of Muscovy ducks, a total of 334 differentially abundant mRNA transcripts (DEGs) and 36 differentially abundant lncRNA transcripts were identified in the nesting period, when compared with during the laying period. These results were subsequently validated by qRT-PCR using nine randomly-selected lncRNAs and six randomly-selected DAMTs. Furthermore, the cis- and trans-regulatory target genes of differentially abundant lncRNA transcripts were identified, and lncRNA-gene interaction networks of 34 differentially abundant lncRNAs and 263 DEGs were constructed. A total of 7601 lncRNAs neighboring 10,542 protein-coding genes were identified and found to be enriched in the Wnt signaling pathway and oocyte meiosis pathways associated with follicular development. Overall, only 11 cis-targets and 57 mRNA-mRNA except trans-targets were involved in the lncRNA-gene interaction networks. Based on the interaction networks, nine DEGs were trans-regulated by differentially abundant lncRNAs and 20 differentially abundant lncRNAs were hypothesized to have important functions in the regulation of broodiness in Muscovy ducks. In this study, a predicted interaction network of differentially abundant lncRNAs and DEGs in Muscovy ducks was constructed for the first time leading to an enhanced understanding of lncRNA and gene interactions regulating broodiness.

Efficiency of CNT-based rotation transmission nanosystem in water.

Carbon nanotubes (CNTs) have been widely used as the motor and rotor in a rotational transmission nanosystem (RTnS), whose function is to transfer the input rotational frequency of the motor into the output frequency of the rotor through motor-rotor interactions. A wide range of techniques has been explored to achieve a CNT-based RTnS with a stable and adjustable transmission. In this work, a CNT-based rotor is partly immersed into a water box and the associated water-rotor interaction leads to effective manipulation of the transmission efficiency of RTnS. Molecular dynamics simulations are performed on this new RTnS to investigate the dynamic response of the rotor and the local flow field near the water-rotor interface. Various parameters, including ambient temperature, tubes' radii, and volume fractions of water in the box (Vf) are examined for their effects on the rotational transmission efficiency. This study offers useful guidelines for the design of stable RTnS with controllable transmission efficiency.

Recent progress in the development of thermal interface materials: a review.

Modern electronic devices are characterized by high-power and high-frequency with excessive heat accumulation. Thermal interface materials (TIMs) are of crucial importance for efficient heat dissipation to maintain proper functions and lifetime for these devices. The most promising TIMs are those polymer-based nanocomposites consisting of polymers and low-dimensional materials with high thermal conductivity (TC). This perspective summarizes the recent progress on the thermal transport properties of newly discovered one-dimensional (1D) nanomaterials and two-dimensional (2D) nanomaterials as well as three-dimensional (3D) nanostructures consisting of these 1D and 2D nanomaterials. Moreover, the applications of various nanomaterials in polymer nanocomposites for advanced TIMs are critically reviewed and the mechanism of TC enhancement is analysed. It is hoped that the present review could provide better understanding of the thermal transport properties of recently developed 2D nanomaterials and various 3D nanostructures as well as relevant polymer-based TIMs, shedding more light on the thermal management research.

Thermo-mechanical correlation in two-dimensional materials.

Two-dimensional (2D) materials have received tremendous attention from the research community in the past decades, because of their numerous striking physical, chemical and mechanical properties and promising potential in a wide range of applications. This field is strongly interdisciplinary, requiring efficient integration of knowledge with different insights. In this review, we summarize the up-to-date research on the thermal and mechanical properties and thermo-mechanical correlation in 2D materials, including both theoretical and experimental insight. Firstly, the mechanical properties of 2D nanomaterials are discussed, in which the underlying physics is summarized. Then, we discuss the impacts of thermal fluctuation on the mechanical properties. Next, from experimental points of view, we present the methods to introduce strain in 2D materials experimentally and the experimental tools to measure the degree of strain. Finally, we discuss the fundamental phonon and thermal properties of 2D materials, including the strain effects on phonon dispersion, phonon hydrodynamic behavior, phonon topological feature, ballistic thermal conductance and diffusive thermal conductivity. This article presents an advanced understanding of the mechanical and thermal properties of 2D materials, which provides new opportunities for promoting their applications in nanoscale electronic, optoelectronic, and thermal functional devices.

Mechanical properties of graphene-reinforced aluminium composite with modified substrate surface: a molecular dynamics study.

Due to its extraordinary properties, graphene has been widely used as reinforcing nanofillers to enhance the mechanical properties of polymer- or metal-based composites. However, the weak interfacial interaction between the matrix and graphene is still a major bottleneck that considerably hinders its reinforcing effectiveness and efficiency. This study presents an atomistic study via molecular dynamics simulation on a chemical modification strategy where the aluminium (Al) substrate is modified with Al2O3 (with or without covalent bonds formed between Al2O3 and graphene) or Al4C3 to achieve significantly improved interfacial shear strength and overall mechanical properties of graphene-reinforced aluminium (Al/Gr) composites. Numerical results show that this strategy works very well and among the three cases considered, modifying Al substrate by Al2O3 without covalent bonds formed at the interface between Al2O3 and graphene produces the strongest interfacial interaction and the best mechanical properties. In the presence of covalent bonds, however, the reinforcing effect is adversely affected due to the sp2-sp3 bond transformation which partially degrades graphene. The present work provides, for the first time, valuable insight into the role of substrate surface modification on the mechanical performance of Al/Gr nanocomposites.