Study on Performance Optimization and Physical Properties Testing of a New Type of High Thermal Conductive Damping Coating

Surface coating of damping paint is a common method to suppress structural vibration and reduce noise, but damping paint has poor thermal conductivity which limits it’ s application to transformers, reactors and other equipment that have high requirements for heat dissipation. In this paper, a new type of high thermal conductivity damping coating is prepared by emulsion polymerization, among which, a polyurethane emulsion with internal cross-linking structure and an acrylic emulsion with polymerization function are used as main agents, mica powder is used as the main damping function filler. By adjusting the proportion of non-metallic thermal conductive filler Al2O3 and thermal conductive fiber to explore the influence of different thermal conductive fillers on the thermal conductivity and damping performance of the damping coating. The paint is applied to aluminum and iron plates, and the sound insulation capacity is tested to study the influence of paint thickness, fiber addition, fiber type, viscoelasticity, and temperature aging on the sound insulation performance of damping sound insulation panels. The test results show that by adding thermally conductive filler Al2O3 and thermally conductive fibers, a thermally conductive network chain is formed inside the damping coating, which greatly improves the thermal conductivity of the coating while ensuring the damping performance and the effect of vibration and noise reduction.

Characterization of Burning Behaviors and Particulate Matter Emissions of Crop Straws Based on a Cone Calorimeter

Crop residue burning is one of the major sources of particulate matter (PM) in the air. The burning behaviors and PM emissions of the three typical crop residues (rice straw, wheat straw, corn straw) in China were characterized by a cone calorimeter (CONE) coupled with a laser dust meter. The water-soluble compounds, carbonaceous content, and morphology of PM were measured by ion chromatography, elemental analyzer, transmission electron microscopy (TEM) and energy-dispersive X-ray spectrometer (EDS). The results showed that thermal stability of corn straw was the worst among the three crop straws. The heat release rate (HRR) curves of the three crop straws were the typical curves of thermally thick charring (residue forming) samples. Wheat straw had the highest smoke yield, which was 2.9 times that of rice straw. The PM emission factor of wheat straw was 180.91 µg/g, which was about three times that of rice straw. The contents of K+, Na+, and Cl− in PM were significantly higher than those of the other six water-soluble inorganic ions. The ratio of organic carbon and elemental carbon (OC/EC) ranged from 14.82 to 30.82, which was similar to the results of open burning. There were mainly three kinds of aggregates in the PM of crop straws: network, chain-like, and soot. Individual particles were mixtures of KCl and organic matters. Core-shell structures were found in PM of rice straw and corn straw. The results in this study were provided based on CONE, an ISO-standard apparatus, which could avoid data conflicts caused by the difference of combustion devices. The relationship between the burning behavior and PM emission characteristics of crop straws was established, which is helpful to understand emissions of crop straws and to find a novel way to solve the problems from the burning of crop residues.

Selection of Solar Powered Unmanned Aerial Vehicles for a Long Range Data Acquisition Chain

The paper presents a long range data acquisition chain operating in areas without access to the electricity grid or communication infrastructure built with unmanned aerial vehicles (UAVs). It is assumed that the length of the network chain significantly exceeds the flight range of a single drone. To build such a network three basic problems have to be solved. The first is energy harvesting for battery charging. The second concerns the choice of drone models that can cover a given distance in the shortest time. The third problem is the reduction of the flight range of drones as a function of payload mass. The evaluation of the proposed method is based on the results of simulations and cost analysis of 54 drones and 25 solar cells. The analysis ends with a proposition of seven steps that can help to choose the most suitable drone model for a given task.

Accounting for Cooperativity in the Thermotropic Volume Phase Transition of Smart Microgels

A full quantitative description of the swelling of smart microgels is still problematic in many cases. The original approach of Flory and Huggins for the monomer–solvent interaction parameter χ cannot be applied to some microgels. The reason for this obviously is that the cross-linking enhances the cooperativity of the volume phase transitions, since all meshes of the network are mechanically coupled. This was ignored in previous approaches, arguing with distinct transition temperatures for different meshes to describe the continuous character of the transition of microgels. Here, we adjust the swelling curves of a series of smart microgels using the Flory–Rehner description, where the polymer–solvent interaction parameter χ is modeled by a Hill-like equation for a cooperative thermotropic transition. This leads to a very good description of all measured microgel swelling curves and yields the physically meaningful Hill parameter ν. A linear decrease of ν is found with increasing concentration of the cross-linker N,N′-methylenebisacrylamide in the microgel particles p(NIPAM), p(NNPAM), and p(NIPMAM). The linearity suggests that the Hill parameter ν corresponds to the number of water molecules per network chain that cooperatively leave the chain at the volume phase transition. Driven by entropy, ν water molecules of the solvate become cooperatively “free” and leave the polymer network.

Construction of a competitive endogenous RNA network and analysis of potential regulatory axis targets in glioblastoma

Background Glioblastoma is the most common primary malignant brain tumor. Because of the limited understanding of its pathogenesis, the prognosis of glioblastoma remains poor. This study was conducted to explore potential competing endogenous RNA (ceRNA) network chains and biomarkers in glioblastoma by performing integrated bioinformatics analysis. Methods Transcriptome expression data from The Cancer Genome Atlas database and Gene Expression Omnibus were analyzed to identify differentially expressed genes between glioblastoma and normal tissues. Biological pathways potentially associated with the differentially expressed genes were explored by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, and a protein-protein interaction network was established using the STRING database and Cytoscape. Survival analysis using Gene Expression Profiling Interactive Analysis was based on the Kaplan–Meier curve method. A ceRNA network chain was established using the intersection method to align data from four databases (miRTarBase, miRcode, TargetScan, and lncBace2.0), and expression differences and correlations were verified by quantitative reverse-transcription polymerase chain reaction analysis and by determining the Pearson correlation coefficient. Additionally, an MTS assay and the wound-healing and transwell assays were performed to evaluate the effects of complement C1s (C1S) on the viability and migration and invasion abilities of glioblastoma cells, respectively. Results We detected 2842 differentially expressed (DE) mRNAs, 2577 DE long non-coding RNAs (lncRNAs), and 309 DE microRNAs (miRNAs) that were dysregulated in glioblastoma. The final ceRNA network consisted of six specific lncRNAs, four miRNAs, and four mRNAs. Among them, four DE mRNAs and one DE lncRNA were correlated with overall survival (p < 0.05). C1S was significantly correlated with overall survival (p= 0.015). In functional assays, knockdown of C1S inhibited the proliferation and invasion of glioblastoma cell lines. Conclusions We established four ceRNA networks that may influence the occurrence and development of glioblastoma. Among them, the MIR155HG/has-miR-129-5p/C1S axis is a potential marker and therapeutic target for glioblastoma. Knockdown of C1S inhibited the proliferation, migration, and invasion of glioblastoma cells. These findings clarify the role of the ceRNA regulatory network in glioblastoma and provide a foundation for further research.

Construction of a competitive endogenous RNA network and analysis of potential regulatory axis targets in glioblastoma

Background: Glioblastoma is the most common primary malignant brain tumor. Because of the limited understanding of its pathogenesis, the prognosis of glioblastoma remains poor. This study was conducted to explore potential competing endogenous RNA (ceRNA) network chains and biomarkers in glioblastoma by performing integrated bioinformatics analysis.Methods: Transcriptome expression data from The Cancer Genome Atlas database and Gene Expression Omnibus were analyzed to identify differentially expressed genes between glioblastoma and normal tissues. Biological pathways potentially associated with the differentially expressed genes were explored by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, and a protein-protein interaction network was established using the STRING database and Cytoscape. Survival analysis using Gene Expression Profiling Interactive Analysis was based on the Kaplan–Meier curve method. A ceRNA network chain was established using the intersection method to align data from four databases (miRTarBase, miRcode, TargetScan, and lncBace2.0), and expression differences and correlations were verified by quantitative reverse-transcription polymerase chain reaction analysis and by determining the Pearson correlation coefficient. Additionally, an MTS assay and the wound-healing and transwell assays were performed to evaluate the effects of complement C1s (C1S) on the viability and migration and invasion abilities of glioblastoma cells, respectively.Results: We detected 2842 differentially expressed (DE) mRNAs, 2577 DE long non-coding RNAs (lncRNAs), and 309 DE microRNAs (miRNAs) that were dysregulated in glioblastoma. The final ceRNA network consisted of six specific lncRNAs, four miRNAs, and four mRNAs. Among them, four DE mRNAs and one DE lncRNA were correlated with overall survival (p < 0.05). C1S was significantly correlated with overall survival (p = 0.015). In functional assays, knockdown of C1S inhibited the proliferation and invasion of glioblastoma cell lines.Conclusions: We established four ceRNA networks that may influence the occurrence and development of glioblastoma. Among them, the MIR155HG/has-miR-129-5p/C1S axis is a potential marker and therapeutic target for glioblastoma. Knockdown of C1S inhibited the proliferation, migration, and invasion of glioblastoma cells. These findings clarify the role of the ceRNA regulatory network in glioblastoma and provide a foundation for further research.

Optimal Key Handover Management for Enhancing Security in Mobile Network

The 3GPP long term Evolution or System Architecture Evolution (LTE/SAE) was designed for the dispositioning of the mobile networks towards 4G. The significant hurdle of 4G is about cementing the privacy and security gap. Due to the disclosures in the connectivity of public networks, a single malicious device could jeopardize the operation of a whole network of devices. The key deliverance handling within the 3GPP LTE/SAE is developed to unauthorize the keys that are being attacked and, in result, to alienate the miscreant keys off the chain of network. The proposed article recognizes the attacks that jeopardize the safe connectivity among the stops in the network chain and details the vulnerability of the key deliverance administration to desynchronization attacks. Even though the periodic upgrade of the root could prove to be a fundamental part of the system, the work proposed brings an emphasis on reducing the impact of desynchronization attacks which currently are unable to be prevented efficiently. The main focus of the design is to shed light on the ways the network operators work to confirm the optimal intervals for the periodic updates to reduce the signal weightage while providing secure user mobility. The analysis and model simulations intend to disclose the influence of the period of root key upgrade on integral operational levels such as constellation and user experience.

The role of organizational commitment, entrepreneurial orientation, and architectural marketing capabilities on improving marketing performance by using network chain capability of goods in tourism market

Entrepreneurial orientation is carried out to improve management's ability to deal with market changes. This study examines a new concept of network chain capability that is capable of mediating the relationship between entrepreneurial orientation and marketing performance of goods in tourism market. The study also verifies the architectural marketing capabilities and organizational commitment to improve network chain capabilities that have an impact on marketing performance of goods in tourism market. In this study, 6 hypotheses are developed and tested with data collected from 185 respondents in the handicraft industry focused on tourism market. Data are analyzed using AMOS 22.0 statistical software which successfully tested 6 hypotheses with significant results. The study proves that network chain capability is declared feasible as a mediating variable. Managerially, network chain capabilities can be practiced as a marketing tool to improve performance.

Construction of a competitive endogenous RNA network and analysis of potential regulatory axis targets in glioblastoma

Background Glioblastoma is the most common primary malignant brain tumor. Due to the limited understanding of its pathogenesis, the prognosis of glioblastoma is poor. The purpose of this study is to explore potential ceRNA network chains and biomarkers in glioblastoma through integrated bioinformatics analysis. Methods Transcriptome expression data from The Cancer Genome Atlas database and Gene Expression Omnibus were analyzed to identify differentially expressed genes between glioblastoma tissue and normal tissue. The potential biological pathways associated with the differentially expressed genes were explored using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, and a protein-protein interaction network was established using the STRING database and Cytoscape. Survival analysis using Gene Expression Profiling Interactive Analysis was based on the Kaplan-Meier curve method. The ceRNA network chain was established using the intersection method to align data from four databases (miRTarBase, miRcode, TargetScan, and lncBace2.0), and expression differences and correlations were verified by using quantitative reverse-transcription polymerase chain reaction analysis and determining the Pearson correlation coefficient. Results A total of 2842 DEmRNAs, 2577 DElncRNAs, and 309 DEmiRNAs were dysregulated in glioblastoma. The final ceRNA network consisted of six specific lncRNAs, four miRNAs, and four mRNAs. Among them, four DEmRNAs and one DElncRNA were correlated with overall survival (p < 0.05). We found that C1S was significantly correlated with overall survival (p = 0.015) and could therefore be used as a biomarker for glioblastoma. Conclusions Four ceRNA networks were established that may influence the occurrence and development of glioblastoma. Among them, the MIR155HG/has-miR-129-5p/C1S axis may be a potential marker and therapeutic target. In particular, C1S has not yet been reported in glioblastoma studies. These findings clarify the role of the ceRNA regulatory network in glioblastoma and lay a foundation for further research.