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Objective: To study whether subcutaneously embedding xenogeneic protein threads or synthetic polymer absorbable threads can improve obesity phenotypes and metabolic conditions, and to further explore its underlying mechanism. Methods: Thirty-six 8-week-old ob/ob mice were randomly allocated to three groups, respectively, receiving catgut embedding, PGA thread embedding or sham treatment bilaterally to the groin. Individual parameters including weight, food intake, and core temperature are recorded and metabolism assessment, energy expenditure analysis, and PET/CT scanning are also performed at fixed timepoints. After surgical incision, the inguinal white adipose tissue was histologically examined and its expression profile was tested and compared among groups 4 weeks and 12 weeks after operation. Results: Catgut embedding reduced weight gain and improved metabolic status in ob/ob mice. Browning of bilateral inguinal WAT (white adipose tissue) was induced after catgut embedding, with massive infiltration of Treg cells and M2 macrophages in the tissue slices of fat pads. IL-10 and TGF-β released by Treg cells targeted macrophages and the induced M2 macrophages increased the expression of thermogenic and anti-inflammatory genes in fat. The secretion of catecholamines by polarized M2 macrophages led to the activation of β3-AR-related pathways in adipocytes and the browning of adipose tissue. Conclusions: Abdominal subcutaneous catgut embedding has the potential to combat obesity through the induction of WAT browning mediated by infiltrated Treg cells and macrophages. [ABSTRACT FROM AUTHOR]

Time-of-use pricing of electric energy, as an important part of the national policy of energy conservation and emission reduction, requires accurate electric energy data as support. However, due to various reasons, the electric energy data are often missing. To address this thorny problem, this paper constructs a CNN and GRU-based recovery model (RCNN-BiGRU) for electric energy data by taking the missing data as the output and the historical data of the neighboring moments as the input. Firstly, a convolutional network with a residual structure is used to capture the local dependence and periodic patterns of the input data, and then a bidirectional GRU network utilizes the extracted potential features to model the temporal relationships of the data. Aiming at the difficult selection of network structure parameters and training process parameters, an accelerated adaptive differential evolution (AADE) algorithm is proposed to optimize the electrical energy data recovery model. The algorithm designs an accelerated mutation operator and at the same time adopts an adaptive strategy to set the two key parameters. A large amount of real grid data are selected as samples to train the network, and the comparison results verify that the proposed combined model outperforms the related CNN and GRU networks. The comparison experimental results with other optimization algorithms also show that the AADE algorithm proposed in this paper has better data recovery performance on the training set and significantly better performance on the test set. [ABSTRACT FROM AUTHOR]

All humans are universally affected by inflammatory diseases, and there is an urgent need to identify new anti-inflammatory drugs with good therapeutic benefits and minimal side effects to the organism. Recently, it has been found that plant-derived vesicle-like nanoparticles (PDVLNs) have good biocompatibility, with their active ingredients exhibiting good therapeutic effects on inflammation. They can also be used as drug carriers for targeted delivery of anti-inflammatory drugs. Therefore, PDVLNs represent a popular research area for novel anti-inflammatory drugs. This paper details the origin, biological functions, isolation and purification, and identification of PDVLNs, as well as the therapeutic effects of their intrinsic bioactive components on inflammatory diseases. It also introduces their targets as drug carriers to facilitate the development and application of PDVLNs anti-inflammatory drugs. [ABSTRACT FROM AUTHOR]

Local exhaust systems based on range hoods are widely used to reduce cooking oil fumes (COF) of kitchen spaces. This work proposes a range-hood-integrated air cleaner to improve air distribution in residential kitchens and reduce individual inhalation exposure to COF. Effects of hood exhaust rates, cooking–heating intensities, and airflow parameters of the air cleaner on the volume-averaged concentration (VAC) of kitchen space and the intake fraction (IF) are discussed through orthogonal experimental design, and significant factors are the hood exhaust rate, the air supply velocity, and angle of the air cleaner by evaluating significance levels. Optimal airflow parameters of the air cleaner are obtained through single-factor analysis, and VAC is reduced by approximately 90% compared with the single range-hood exhaust system. The energy-saving potential of the air cleaner is identified and evaluated using the concept of the equivalent exhaust rate. The air cleaner is more conducive to creating a comfortable kitchen environment and reducing heat transfer load. This work provides a new solution for optimizing air distribution in highly polluted kitchen environments. [ABSTRACT FROM AUTHOR]

Ecological and environmental pollution is a common important problem, and it is impossible to talk about the relationship between humans and nature without involving human behavior. The analysis of human behavior not only sheds light on understanding man but also represents the importance of ecological development and growth. This paper builds a framework of external and internal factors to analyze human behavior, and game theory is used to simulate the conflicting interests of human behavior. Then the GMM method is used to empirically analyze the deduction function of the benefit and payment function from the game analysis, besides the MS-VAR model is also used to capture the dynamic change of human behavior in environmental protection. Games analysis integrating the use of GMM and MS-VAR links the theory analysis with the practice and uses real data to analyze human behavior instead of virtual assumptions. Although this paper takes the situation in China as an example, the framework of empirical analysis suggests a framework of quantitative analysis of human behavior in environmental protection for other countries and regions. [ABSTRACT FROM AUTHOR]

Tunnels play a vital role in enhancing traffic flow and supporting public transportation systems. However, the discharge of polluted air and waste heat from vehicles passing through tunnels significantly raises the temperature inside, presenting challenges in terms of occupant comfort, tunnel safety, and infrastructure integrity. Therefore, ensuring proper temperature control is essential for their efficient operation. This study aims to investigate the phenomenon of temperature rise in ultra-long tunnels during normal operations, as limited research has been conducted in this area. The Shanghai Yangtze River Tunnel serves as a case study, utilizing temperature and air velocity data collected throughout the year (2021) from the management company. The analysis reveals that the temperature distribution near the tunnel exit is influenced by outdoor temperature fluctuations and traffic volume. The highest temperatures occur on 25 August (39.74 °C) during peak traffic hours. On-site measurements of tunnel temperature, humidity, and air velocity during winter and summer seasons yield the following results. During winter, the air temperature and wall temperature inside the tunnel experience significant increases along its length. The air temperature rises by approximately 11 °C from the entrance to the exit, while the wall temperature increases by about 15 °C. In contrast, during summer, the air temperature only rises by 2.7 °C, and the wall temperature increases by around 3 °C. Consequently, the humidity decreases along the tunnel, and this decrease is correlated with the magnitude of temperature increase. Furthermore, measurements of air velocity indicate that natural and traffic-induced winds contribute to the overall airflow inside the tunnel. A temperature data logger installed in the tunnel recorded temperature changes during the period of pandemic lockdown and subsequent recovery, spanning the spring and summer seasons. During the lockdown period, there was a relatively small increase in temperature along the tunnel, suggesting that vehicle heat dissipation is the primary factor contributing to temperature rise inside. Additionally, a method is proposed to predict the cross-sectional temperature of the tunnel using measured air velocities. [ABSTRACT FROM AUTHOR]

Maintaining accurate topology of the low-voltage distribution grid (LVDG) are critical to the operations and maintenance of power distribution systems. However, this goal is hard to achieve due to the fast-changing LVDG topology. To this end, we focus on the abnormal customer-transformer relationships identification in the LVDG and propose an identification method based on an Adaptive Dual-channel Graph Wavelet Neural Network (ADGWN) consisting of two identical GWNs connected with the attention mechanism. In the proposed ADGWN, two GWNs learn customer embedding simultaneously from the LVDG topology graph and the feature graph that is constructed from customer electricity consumption data with the k-Nearest Neighbor algorithm. The topology identification results of these two GNNs are then adaptively fused to form the ultimate identification result with the attention mechanism by dynamically balancing the aforementioned two types of information. To validate the performance of our proposed method, we further build a real benchmarking dataset from customer electricity consumption data collected from a certain substation in Shanghai, China. Experimental results show that the proposed ADGWN achieves 100.0% LVDG topology identification accuracy and significantly outperforms the state-of-the-art. Our proposed method can help operators of power distribution systems maintain the accurate topology in a timely and economic manner. [ABSTRACT FROM AUTHOR]

Diabetes is the most common chronic disease in the world, and it brings a heavy burden to people's health. Against this background, diabetic research, including islet functionalization has become a hot topic in medical institutions all over the world. Especially with the rapid development of microencapsulation and three-dimensional (3D) bioprinting technologies, organ engineering and manufacturing have become the main trends for disease modeling and drug screening. Especially the advanced 3D models of pancreatic islets have shown better physiological functions than monolayer cultures, suggesting their potential in elucidating the behaviors of cells under different growth environments. This review mainly summarizes the latest progress of islet capsules and 3D printed pancreatic organs and introduces the activities of islet cells in the constructs with different encapsulation technologies and polymeric materials, as well as the vascularization and blood glucose control capabilities of these constructs after implantation. The challenges and perspectives of the pancreatic organ engineering/manufacturing technologies have also been demonstrated. [ABSTRACT FROM AUTHOR]

How to reduce environmental pollution is fundamental for current civilization. Increasing in R&D investment may reduce the environmental pollution, yet whether and how R&D investment influence the environmental pollution needs further discussion and verification. Considering that the R&D investment can directly and also indirectly influence the environmental pollution by affecting the economic growth, and the fact that there is an obvious discontinuity for economic growth during the observed period, this paper firstly proposes an integrated approach based on panel moderated mediation analysis and regression discontinuity. It examines the R&D impact on environmental pollution on the basis of province-level data in China and uses the integrated approach to test its direct and indirect effect. Finally conclusion is made according to the findings. [ABSTRACT FROM AUTHOR]

In industrial sites, the movement and contact behaviors of workers are random, but their frequency and statistical characteristics can be determined. Particularly in machining workshops, metalworking fluids (MWFs) cause liquid oil contamination on the processed workpieces, and the contamination spreads to the entire workshop given the random contact of workers or the handling of workpieces. This study proposes a contact transmission model based on the Markov chain to quantify oil contamination transfer. First, the transfer efficiency between the glove and the workpiece, which is regarded as a key model parameter in this research, was determined through experiments. The model was used to characterize and predict the spread of oil contamination across different regions, including production and assembly areas. Specifically, the oil contamination concentrations on workbench surfaces in seven locations of a machining workshop in Shanghai GKN HUAYU Driveline Systems Co., Ltd. (SDS) were measured on-site. Findings showed that the model could feasibly depict the transfer process of oil contamination across different surfaces. Then, the variation law of oil contamination concentration on the workbench surfaces over time was analyzed, the oil contamination distribution map of the entire workshop plane was drawn, and the effectiveness of two cleaning measures to reduce oil contamination concentrations was compared. The proposed contact transmission model offers a basis for identifying highly polluted surfaces in machining workshops and controlling the spread of liquid oil contamination. [ABSTRACT FROM AUTHOR]

Anti‐icing polyimide (PI) thin films are a promising anti‐icing technology for aircraft. A processing method combining reactive ion etching with cooling and plasma chemical vapour deposition is proposed to fabricate anti‐icing PI thin films with microcolumns (PI‐M). The anti‐icing performance of PI‐M was examined. The apparent contact angle (APCA) was 153° ± 1.4°, and the APCA hysteresis was 8.5° ± 0.5°. The calculated Weber number was high, and a droplet on PI‐M rebounded within 2.56 s, whereas rebounding occurred more slowly on a smooth PI surface (PI‐S). The freezing time of droplets on PI‐M was 70% longer than that on PI‐S. The average ice adhesion force on PI‐M was 42% smaller than that on PI‐S. Repeated measurements of the ice adhesion force on PI‐M demonstrated that it was stable (deviation: ±1 N). The APCA showed that PI‐M is superhydrophobic, which indicates that droplets on PI‐M were in the Cassie state. The droplet bouncing behaviour was explained in terms of horizontal force equilibrium at the interface. The anti‐icing mechanism of PI‐M was modelled using heterogeneous nucleation theory and a contact area model. The results explained the good anti‐icing performance and suggested that PI‐M may have excellent potential for anti‐icing applications. [ABSTRACT FROM AUTHOR]

To study the nonlinear dynamic characteristics of the dual-mass flywheel (DMF) under the conformal contact action between the friction damping ring and primary flywheel pressure plate, the contact action model is established and analyzed based on Winkler model. Through analysis and calculation, the contact deformation, contact pressure at different contact positions, and equivalent torsional contact stiffness are obtained. The nonlinear dynamic analysis model of three-degree-of-freedom (3DOF) which takes the conformal contact into account and two-degree-of-freedom (2DOF) without considering conformal contact is established. The approximate analytical solution of the nonlinear frequency characteristics of the system at steady state is derived. By comparing with the results obtained from numerical method, the theoretical analysis process is proved to be valid. And it is found that the overall amplitude and angular displacement transmissibility of the 3DOF model are smaller than the 2DOF model, especially at resonance frequency. The effects of the friction damping ring moment inertia, stiffness of DMF, and axial friction torque on the frequency characteristics of system and angular displacement transmissibility are analyzed. The forced vibration response analysis of the 3DOF model is conducted, through which the torsional angle variations of the primary flywheel, friction damping ring, and secondary flywheel with time are obtained. The results show that the amplitude of the secondary flywheel is much smaller than that of the primary flywheel, indicating that the DMF has prominent damping performance. [ABSTRACT FROM AUTHOR]

Background. MicroRNA (miRNA) has been confirmed to be involved in the occurrence, development, and prevention of diabetic nephropathy (DN), but its mechanism of action is still unclear. Objective. With the help of the GEO database, bioinformatics methods are used to explore the miRNA-mRNA regulatory relationship pairs related to diabetic nephropathy and explain their potential mechanisms of action. Methods. The DN-related miRNA microarray dataset (GSE51674) and mRNA expression dataset (GSE30122) are downloaded through the GEO database, online analysis tool GEO2R is used for data differential expression analysis, TargetScan, miRTarBase, and miRDB databases are used to predict potential downstream target genes regulated by differentially expressed miRNAs, and intersection with differential genes is used to obtain candidate target genes. According to the regulatory relationship between miRNA and mRNA, the miRNA-mRNA relationship pair is clarified, and the miRNA-mRNA regulatory network is constructed using Cytoscape. DAVID is used to perform GO function enrichment analysis and KEGG pathway analysis of candidate target genes. By GeneMANIA prediction of miRNA target genes and coexpressed genes, the protein interaction network is constructed. Results and Conclusions. A total of 67 differentially expressed miRNAs were screened in the experiment, of which 42 were upregulated and 25 were downregulated; a total of 448 differentially expressed mRNAs were screened, of which 93 were upregulated and 355 were downregulated. Using TargetScan, miRTarBase, and miRDB databases to predict downstream targets of differentially expressed miRNAs, 2283 downstream target genes coexisting in 3 databases were predicted to intersect with differentially expressed mRNAs to obtain 96 candidate target genes. Finally, 44 miRNA-mRNA relationship pairs consisting of 12 differentially expressed miRNAs and 27 differentially expressed mRNAs were screened out; further analysis showed that miRNA regulatory network genes may participate in the occurrence and development of diabetic nephropathy through PI3K/Akt, ECM-receptor interaction pathway, and RAS signaling pathway. [ABSTRACT FROM AUTHOR]

For large space buildings like industrial plants with huge heat generation, the role that surface-source plumes play becomes more crucial. To study the air distribution and movement of plumes, the first step is to quantify how the airflow gets distributed in chambers. The experiment was carried out in a thermostatic chamber where there was no ventilation. Four hundred flow field snapshots (in each region) were measured by a two-dimensional particle image velocimetry system at a sampling frequency of 3 Hz, and the time-average flow field was processed by the adaptive correlation algorithm to quantify the air distribution of the plume. According to the measured data, the variation law of the axial velocity of the surface-source plume under different heat source parameters was analysed. The formula coefficients of the axial velocity, the extended radius and the mass flow of the plume were discussed, and the coefficients from current two mainstream methods and those obtained in this paper were compared. The results of this study will be useful to predict motion of surface-plumes and optimize airflow patterns in large spaces. [ABSTRACT FROM AUTHOR]

In the present work, dislocation structures at the grain boundary (GB) pop-in events were studied around and below the Berkovich indentations using electron channeling contrast imaging (ECCI) in polycrystalline tungsten. The GB pop-in events were identified as displacement bursts in the load–displacement curve, and the indentation experiments were stopped just after the occurrence of the displacement burst. A significant hardness increase was observed before the GB pop-in event. The careful ECCI analysis on the sequential polished cross sections clearly shows the dislocation pile-up in the vicinity of the GB along with transmitted dislocations in the adjacent grain. The transmitted dislocations were also found to be influenced by the indenter orientation with respect to the GB. [ABSTRACT FROM AUTHOR]

Traditional design of airflow distributions in large spaces does not consider the interference of thermal plumes on jets. In order to quantitatively describe the indoor environment, it is first necessary to quantify how the airflow gets distributed. In this study, a two-dimensional particle image velocimetry (PIV) system for measuring a wide indoor flow field was established. A total of 24 sub-regions (each with a size of 400 mm × 350 mm) were accurately measured in an unmanned room, and the overall cross-sectional flow field was obtained by splicing. Uncertainty analysis proved the rationality of this experimental method. According to the damage extent of the jet structure introduced by the thermal plume, two groups were divided, i.e. Groups A and B. The distribution of velocity fields, trajectories and velocity attenuation of jet centerlines, and velocity magnitude profiles at nozzle and head levels were compared and analyzed in detail. Through this investigation, detailed information of indoor air flow in large spaces can be effectively characterized, which can be useful to help understand the indoor physics and validate CFD models. Practical application : The key to creating a comfortable and healthy indoor thermal environment is the rational design of the airflow distribution. This paper proposes a method for quantitatively describing the airflow distribution in an enclosed space. The equation of the non-dimensional velocity attenuation of jet centerlines is obtained by using advanced technology (PIV), which provides theoretical basis and useful reference for the design of airflow distribution. [ABSTRACT FROM AUTHOR]

This paper is concerned with the state estimation problem for a class of recurrent neural networks with interval time-varying delay, where time delay includes either slow or fast time-varying delay. A novel delay-dependent criterion, in which the rate-range of time delay is also considered, is established to estimate the neuron states through available output measurements such that, for all admissible time delays, the dynamics of the estimation error system is globally asymptotically stable. The proposed method is based on a new Lyapunov-Krasovskii functional with triple-integral terms and free-weighting matrix approach. Numerical examples are given to illustrate the effectiveness of the method. [ABSTRACT FROM AUTHOR]

Electric energy metering plays a crucial role in ensuring fair and equitable transactions between grid companies and power users. With the implementation of the State Grid Corporation's energy Internet strategy, higher requirements have been put forward for power grid companies to reduce costs and increase efficiency and user service capabilities. Meanwhile, the accuracy and real-time requirements for electric energy measurements have also increased. Electricity information collection systems are mainly used to collect the user-side energy metering data for the power users. Attributed to communication errors, communication delays, equipment failures and other reasons, some of the collected data is missed or confused, which seriously affects the refined management and service quality of power grid companies. How to deal with such data has been one of the important issues in the fields of machine learning and data mining. This paper proposes a collaborative fitting algorithm to solve the problem of missing collected data based on latent semantics. Firstly, a tree structure of user history data is established, and then the user groups adjacent to the user with missing data are obtained from this. Finally, the missing data are recovered using the alternating least-squares matrix factorization algorithm. Through numerical verification, this method has high reliability and accuracy in recoverying the missing data. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) bioprinting is a family of rapid prototyping technologies, which assemble biomaterials, including cells and bioactive agents, under the control of a computer-aided design model in a layer-by-layer fashion. It has great potential in organ manufacturing areas with the combination of biology, polymers, chemistry, engineering, medicine, and mechanics. At present, 3D bioprinting technologies can be used to successfully print living tissues and organs, including blood vessels, skin, bones, cartilage, kidney, heart, and liver. The unique advantages of 3D bioprinting technologies for organ manufacturing have improved the traditional medical level significantly. In this article, we summarize the latest research progress of polymers in bioartificial organ 3D printing areas. The important characteristics of the printable polymers and the typical 3D bioprinting technologies for several complex bioartificial organs, such as the heart, liver, nerve, and skin, are introduced. [ABSTRACT FROM AUTHOR]

Multiple sets of spring, spring seat structures are uniformly arranged in circumferential short spring dual mass flywheel (DMF), which generally have a symmetrical structure. The internal springs and spring seats are constrained by the shape of the primary flywheel and the secondary flywheel. At different rotational speeds, the springs and spring seats have different centrifugal forces. To study the dynamic characteristics of the DMF including torque and stiffness with considering the influence of centrifugal force and friction, the discrete method is used to analyze the mechanical actions of the transmission parts in DMF. The torque action between the spring seat and the secondary flywheel is deduced. The dynamic characteristics of the DMF are obtained through analyzing and calculating. Due to the symmetry of the structure, the torque transmitted and the stiffness of the DMF also have specific symmetrical characteristics. Namely, at two relative rotational angles of the same magnitude and opposite direction, the magnitude of the transmitted torque is the same, the direction is opposite. The magnitude and direction of stiffness are the same. The influence of speed, friction coefficient, spring mass, and spring seat mass on the torque and stiffness characteristics are analyzed. Finally, the theoretical analysis is proved to be valid by the torque characteristics test of DMF. [ABSTRACT FROM AUTHOR]

This paper examines the price of carbon emission rights published by the China Emissions Exchange (Shenzhen), analyzes the statistical characteristics of the price series and uses a generalized autoregressive conditional heteroskedasticity (GARCH) model to describe the price fluctuation of carbon emission rights and risk formation mechanisms. The study shows the following results: since 2013, China's carbon emission rights prices have become more stable. The fluctuation of yield has gradually decreased and the market has approached a more mature stage. However, after 2018, due to factors such as the economic downturn and insufficient market information, the amplitude of price fluctuations has started to rise while frequency is increasing, which shows an asymmetry trend. The market trading risk is accumulating constantly. [ABSTRACT FROM AUTHOR]