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Excessive production of inflammatory chemokines and reactive oxygen species (ROS) can cause a feedback cycle of inflammation response that has a negative effect on cutaneous wound healing. The use of wound-dressing materials that simultaneously absorb chemokines and scavenge ROS constitutes a novel ‘weeding and uprooting’ treatment strategy for inflammatory conditions. In the present study, a composite hydrogel comprising an amine-functionalized star-shaped polyethylene glycol (starPEG) and heparin for chemokine sequestration as well as Cu5.4O ultrasmall nanozymes for ROS scavenging (Cu5.4O@Hep-PEG) was developed. The material effectively adsorbs the inflammatory chemokines monocyte chemoattractant protein-1 and interleukin-8, decreasing the migratory activity of macrophages and neutrophils. Furthermore, it scavenges the ROS in wound fluids to mitigate oxidative stress, and the sustained release of Cu5.4O promotes angiogenesis. In acute wounds and impaired-healing wounds (diabetic wounds), Cu5.4O@Hep-PEG hydrogels outperform the standard-of-care product Promogram® in terms of inflammation reduction, increased epidermis regeneration, vascularization, and wound closure., Graphical abstract Image 1, Highlights • Cu5.4O@Hep-PEG hydrogels capture pro-inflammatory factors, decreasing immune cell influx and inflammatory level in wounds. • Hydrogels can scavenge ROS, reducing secretion of pro-inflammatory factors and inflammatory cell infiltration in wounds. • This strategy disrupts the feedback relationship between ROS and inflammation and improve the wound-healing environment.

Electrochemical water splitting is a facile and effective route to generate pure hydrogen and oxygen. However, the sluggish kinetics of hydrogen evolution reaction (HER) and especially oxygen evolution reaction (OER) hinder the water splitting efficiency. Meanwhile, the high-cost of noble-metal catalysts limit their actual application. It is thus highly urgent to exploit an economical and earth-abundant bifunctional HER and OER electrocatalyst to simplify procedure and reduce cost. Herein, we synthesize the three-dimensionally ordered macro-/mesoporous (3DOM/m) NixCo100-x alloys with distinctive structure and large surface area via a dual-templating technique. Among them, the 3DOM/m Ni61Co39 shows the lowest overpotentials of 121 mV and 241 mV at 10 mA/cm2 for HER and OER, respectively. Furthermore, when employed for water splitting, the Ni61Co39 only requires 1.60 V to approach 10 mA/cm2 and presents excellent stability. These encouraging performances of the Ni61Co39 render it a promising bifunctional catalyst for overall water splitting.

Purpose The behavioral decision-making of digital-self is one of the important research contents of the network of crowd intelligence. The factors and mechanisms that affect decision-making have attracted the attention of many researchers. Among the factors that influence decision-making, the mind of digital-self plays an important role. Exploring the influence mechanism of digital-selfs’ mind on decision-making is helpful to understand the behaviors of the crowd intelligence network and improve the transaction efficiency in the network of CrowdIntell. Design/methodology/approach In this paper, the authors use behavioral pattern perception layer, multi-aspect perception layer and memory network enhancement layer to adaptively explore the mind of a digital-self and generate the mental representation of a digital-self from three aspects including external behavior, multi-aspect factors of the mind and memory units. The authors use the mental representations to assist behavioral decision-making. Findings The evaluation in real-world open data sets shows that the proposed method can model the mind and verify the influence of the mind on the behavioral decisions, and its performance is better than the universal baseline methods for modeling user interest. Originality/value In general, the authors use the behaviors of the digital-self to mine and explore its mind, which is used to assist the digital-self to make decisions and promote the transaction in the network of CrowdIntell. This work is one of the early attempts, which uses neural networks to model the mental representation of digital-self.

Lignite briquetting provided an effective method for the utilization of lignite powder. Based on the briquetting conditions of lignite, two kinds of binders (sodium humate and polyvinyl alcohol) we...

Fine slag (FS), which is a by-product from coal gasification, is composed of inorganic minerals and residual carbon. Acid treatment has high efficiency to separate the residual carbon in FS but the changes of properties of FS treated by acid remain unclear. To have a deep understanding of effects of acid treatment on physicochemical properties and gasification activity of FS, FS was subjected to different acid treatment, and then were characterized using Nitrogen adsorption technique, Raman spectroscopy and thermo-gravimetric analyzer. The results showed that the combined treatment with hydrochloric acid and hydrofluoric acid can remove the almost all mineral matters. Acid treatments did not modify the continuous and complete pores structure of FS. While, hydrochloric acid has a major influence on carbon structure, which produces the highest carbon actives and amorphous carbon. Nitric acid has positive influence on carbon structure transformation to crystalline structure. Notably, the gasification time can be shortened by the reduction of ash content. The carbon active sites in samples governed the initial reactivity while at the late stage of gasification the amount of inorganic elements controlled the gasification rate.

With the emergence of outsourcing logistics and the rapid development of the e-commerce business, Third Party Logistics (TPL) plays an indispensable role in modern business. In the TPL provider selection process, uncertain information brings more challenges to decision makers. This paper uses probabilistic linguistic term sets (PLTSs) to describe uncertain decision making information. Firstly, we propose an improved Decision Making Trial and Evaluation Laboratory method, which allows a certain relationship between decision criteria and calculates criteria weights in multi-criteria decision making (MCDM) problems. Then, in order to make full use of uncertain TPL provider information and maximize the values of data, the probabilistic linguistic complex proportional assessment method is proposed and applied to solve the MCDM problems under probabilistic linguistic environment, which needs much less computation than other MCDM methods. Finally, an application example of TPL provider selection is presented to demonstrate the proposed method. A comparative analysis is further conducted to validate the effectiveness of the proposed method.

Through the COVID-19 epidemic in 2020, the society has deeply realized the inevitability and necessity of building a community that shares the future of mankind. In the face of severely complex international trends and domestic and international economic conditions, artificial intelligence plays an important auxiliary role in the regular prevention and management of COVID-19. In order to effectively correspond to the formalized extensional prevention and control theory, it is essential to use coordination models, rule systems, prevention and control mechanisms, and governance landscapes to build artificial intelligence corresponding systems. This article uses a basic genetic algorithm to realize the robot path plan. This mainly includes the establishment of environmental models, the discovery of chromosomes and the determination of coding methods, the selection and design of fitness functions, and related designs. This paper proposes a new adaptive adjustment mode based on the basic genetic algorithm, which improves the selection and mutation operation, and improves the optimization efficiency of the genetic algorithm. Building an artificial intelligence response system may face various technical risks and governance dilemmas. Only by improving the rule system of artificial intelligence, creating an epidemic prevention and control ecology, conserving the public spirit of the whole people, strengthening the governance of the source of crisis, and further improving the new momentum of economic and social development and public safety. The modernization of governance capabilities can better respond to the current complex situation.

Ultrasmall Ru nanoparticles is expected as a potential alternative to Pt for efficient hydrazine oxidation (HzOR). However, preparation of ultrasmall and well-distributed Ru nanoparticles usually s...

Photodynamic therapy (PDT) is a new therapeutic strategy for hypertrophic scars (HSs), and nanoethosomes (ES) have attracted considerable attention as an efficient transdermal delivery system for PDT of HSs (HS-PDT). However, the delivery of photosensitizers and the hypoxic microenvironment of HSs limit HS-PDT efficacy. Consequently, functional transdermal ES (A/A-ES) that are loaded with the photosensitizer, 5-aminolevulinic acid (ALA), and immobilized nanoenzyme Au nanoclusters (ANCs) within the ES surface have been developed that exhibit superior co-delivery characteristics and produce catalase that enhances HS-PDT efficacy. The unique structure of A/A-ES enables them to co-deliver ALA and ANCs into the HS tissue and to efficiently decompose the endogenous hydrogen peroxide in the HS to generate oxygen. The findings from in vitro and in vivo experiments demonstrated that A/A-ES efficiently co-delivered ALA and ANCs into the HS tissue and that they improved the hypoxic microenvironment of the HS. Systematic assessments reveal that A/A-ES enhance HS-PDT efficacy and that they are highly effective at improving the morphology and promoting HS fibroblast apoptosis and the rearrangement of collagen. These works give rise to an effective treatment option for HSs that integrates the transdermal co-delivery of ALA and nanoenzymes, thereby enabling them to exert their respective beneficial effects, and they highlight the enhancement of HS-PDT efficacy via self-generating oxygen.

Large earthquakes frequently occurred and caused substantial damage and losses in Chinese densely populated urban areas. It is worth clarifying that the existing earthquake loss assessment tools in China do not consider its special characteristics (e.g., tectonics, geology and building inventory). In this paper, an integrated framework for earthquake loss assessment in China is proposed and a geographic information system (GIS)-based system, referred to as China Earthquake Disaster Loss Assessment System, is developed. The individual building is considered as the basic geographical unit and described in three levels (i.e., basic attributes, structural performance parameters, and functional parameters. A three-step data collection method is proposed, and the mobile GIS-based field collection tool is developed. A broad, reasonable, and upgradeable building typology is then presented for the seismic fragility assessment of building blocks. A new economic loss model and casualty model are also presented by considering the characteristics of economics and population. The proposed methodology is implemented in Baqiao District, and the estimation of economic losses and casualties under a scenario earthquake is discussed, which can provide information for urban disaster risk assessment and mitigation.

It is a coupling solution for optimizing the materials with good thermal conductivity and anti-corrosive modified coating of flue-gas condensation heat exchangers. The paper experimentally studied ...

Robust array beamforming is a challenging task in radar, sonar and communications due to the influence of direction of arrival (DOA) mismatch and sensor position errors. However, how to enhance the robustness of beamforming is a key issue in antenna arrays. The current paper focuses on a novel approach called the improved chicken swarm optimization (ICSO) method to settle the optimization model of conventional linearly constrained minimum variance (LCMV) based on support vector machine (SVM) to against the mismatch problems as well as control the sidelobe level (SLL). As far as the ICSO method is concerned, considering that the particle swarm optimization (PSO) algorithm has outstanding convergence performance in the early iteration, the dominance of the alpha wolf in the grey wolf optimization (GWO) algorithm and the innovative mutual attraction mechanism in the firefly algorithm (FA), and we introduce these three strategies into the solution update method of conventional chicken swarm optimization (CSO) algorithm for achieving better optimization capability. Moreover, an operation of removing duplicate solutions is proposed to enhance the utilization of the population. In terms of the SVM-based LCMV beamforming algorithm, we adopt the so-called linear $\varepsilon $ - insensitive loss function to reconstruct the final cost function of LCMV by penalizing the errors between the actual and ideal array responses. Finally, we conduct simulations to evaluate the performance of the swarm intelligent optimization algorithms under an ideal scenario without mismatch and an actual scenario with the mismatch, respectively. And the results demonstrate that the developed ICSO algorithm obtains excellent robustness for different scenarios compared to PSO, FA, GWO and CSO optimization algorithms.

In order to enhance the mechanical properties of a hydrogel film and broaden its applications in the medical field, polydopamine (PDA) was used as the “medium” to construct a dynamically united calcium alginate/carboxymethyl chitosan (CA/CMCS) dual network structure using the Michael addition reaction in this study. A high-strength and high-toughness medical film with a united dual network was prepared by a flow-casting/solvent evaporation method. When the content of sodium alginate (SA)–PDA was 2 wt%, the mechanical properties of the prepared film were the best. The tensile strength and elongation at break were 68.81 Mpa and 3.31%, which increased by 231.61% and 47.77% compared with the CA film. The best comprehensive performance for the medical film could be achieved at the same time. The water absorption rate, maximum swelling rate, water vapor transmission rate, contact angle and degradation rate of the film were 417%, 455%, 1000.45 g m−2 d−1, 55° and 13.13%, respectively. The united dual network structure film had potential applications in the medical field.

Microbial fuel cells (MFC) can use microorganisms to directly convert the chemical energy of organic matter into electrical energy, and generate electrical energy while pollutants degradation. To solve the critical problem of lower power yield of power production, this study selected Saccharomyces cerevisiae, Escherichia coli, Pseudomonas aeruginosa, and Bacillus subtilis as the anodic inoculums. The influence of the mixed bacteria on the power-producing effect of MFC and the synergy effect between the electrochemically active bacteria in mixed cultures were discussed. The results showed that among the mixed culture system, only the mixed cultures MFC composed of Saccharomyces cerevisiae and Bacillus subtilis had a significant increase in power generation capacity, which could reach to 554 mV. Further analysis of the electrochemical and microbiological performance of this system was conducted afterward to verify the synergy effect between Saccharomyces cerevisiae and Bacillus subtilis. The riboflavin produced by Bacillus subtilis could be utilized by Saccharomyces cerevisiae to enhance the power generation capacity. Meanwhile, Saccharomyces cerevisiae could provide carbon source and electron donor for Bacillus subtilis through respiration. Finally, in the experiment of adding exogenous riboflavin in the mixed bacterial MFC, the result indicated that the mixed bacterial MFC chose the self-secreting riboflavin over the exogenous riboflavin as the electron mediator, and the excess riboflavin might hinder the electron trasfer., Graphical abstract

There are abundant resources of low-rank coal powder in the world. Powder briquetting technology has opened up a new avenue for large-scale utilization of low-rank coal. Water repellency is of grea...

The copper(II) diethyldithiocarbamate (Cu(DDC)2) complex exhibited excellent inhibition to cancer cells. The usual administration is intravenous injection for disulfram and oral for copper. A new strategy was reported to improve the administration efficiency of the Cu(DDC)2 drug. Poly(lactide-co-glycolide) (PLGA) nanoparticles were used to trap disulfram and copper gluconate separately, the two types of drug loaded nanoparticles were injected in mesothelioma-bearing nude mice via intraperitoneal injection. The in vivo formation of Cu(DDC)2 complex was induced by disulfiram and Cu2+ released from PLGA nanoparticles. This strategy avoided many obstacles in the use of Cu(DDC)2 complex as chemotherapeutic and exhibited excellent anticancer activity to mesothelioma.

Coal ash melting characteristics has a direct impact on the smooth operation of entrained gasifier. Mineral conversion of coal ash is very significant to be investigated, because the mineral can affect the melting temperature and viscosity under high temperature conditions. In this paper, the effects of different Al2O3/CaO on the mineral conversion, melting temperature and viscosity of Ningdong coal ash are studied by the combination of experiment and simulation. The trend of melting temperature decreases firstly and rises with increasing Al2O3/CaO. The ash melting point reached to the lowest when the ratio is 1.23. XRD and Factsage software are used to analyze crystallization behavior of samples. The results show that the content of anorthite, albite and corundum increases and subsequently decreases, while the content of mullite decreases firstly and then rises with increasing Al2O3/CaO. High content with CaO can contribute to form albite and anorthite of low-melting. Besides, high content with Al2O3 can tend to produce mullite of high-melting. The results of experimental and simulation are basically the same, which lays a foundation for the melting characteristics of Ningdong coal ash and can provide technical support for the smooth operation of the entrained-gasifier.

The evaluation performance of PDP (policy decision point), especially in large-scale policy sets, is one of the most significant challenges in XACML (eXtensible Access Control Markup Language). With high time-consuming and extensive storage policies, large-scale policy sets are becoming more complicated when their evaluation performance need to be improved. Based on numericalization and batch processing, a new locomotive algorithm is proposed to design and implement a novel policy evaluation engine called XDPNBE that can efficiently deal with large-scale policy sets and make authorization decisions in multiple circumstances. XDPNBE enables efficient decisions within an attributed-based access control framework that has a strong promotion of evaluation performance. By simulating requests, XDPNBE is compared with the Sun PDP, XEngine, HPEngine and SBA-XACML. Experimental results show that if the number of requests reaches 10,000, the evaluation time of XDPNBE on the large-scale policy set with 120,000 rules is approximately 0.21%, 4.69%, 5.67% and 9.66% of that of the Sun PDP, XEngine, HPEngine and SBA-XACML, respectively.

We explore the influence of absorption, anisotropy and unstable layered turbulence on the channel capacity of horizontal seawater link. By developing the spectrum average coherence length of collim...

Fine slag (FS) is byproduct of the coal gasification process, consisting of mineral-rich particles (MRP) and discrete residual carbon (DRC). MRP were separated using froth flotation method from FS and the ash content of separated MRP was higher than 98%. MRP were sieved into five sized fractions and its properties were studied by SEM/EDS, XPS, XRD, FT-IR and Raman spectroscopy. The results show that MRP are heterogeneous material which contain not only minerals but also residual carbon. The minerals in MRP contain most amorphous glass, together with minor proportions of crystal quartz. The MRP mainly consist of aluminosilicate and smallest (0–23 µm) particles have the most of aluminosilicate. Except for discrete residual carbon particles, there are also another two types of residual carbon within MRP. The first is embedded in the MRP matrix. The second is associated in chemical and/or physical way with the inorganic matter within MRP matrix. Residual carbon within MRP has a low degree of crystalline order. The main functional groups of residual carbon within MRP matrix are C-C, C-H and C-O. C-O which chemically bound with inorganic elements in the MRP forming C-O-M (M represents inorganic elements existing in MRP) groups.

Fine slag (FS) consists of residual carbon (RC) and slag particles (SP). This paper studies the characteristics of SP and RC separately. SP contain a little of pores and mainly consist of spherical particles most of which are solids. RC have a higher pore surface, more continuous and complete pore structure. The chemical structure of inorganic minerals in SP has the following characteristics: According to nuclear magnetic resonance results, the amounts of network structure Q4 and Q3 are more than that of chain structure Q2 and Q1. The 4-coordinated aluminum consists of 74% and the octahedral coordination (Al(VI)) takes up only 11%. SP is a heterogeneous material which contain not only inorganic minerals but also organic carbon. C atom associated in chemical way with the inorganic matter within SP matrix. The predominant groups of organic carbon within SP matrix are C-C and C-O. C-O groups organically bound with inorganic elements in SP forming C-O-M (M: inorganic elements) bands. The predominant components in RC are C-C and C-O.

Disaster has great destructiveness and a wide influence on urban and rural construction, and more than one place is affected by disaster. Thus, it needs to take multiple disaster points into account. In view of different rescue missions, both medical rescue teams and search rescue teams also need to be dispatched. That is the multi-sided matching among medical rescue teams, search rescue teams and disaster points. Firstly, we describe the matching process, including the related symbols used in the process, and define a concept called multi-sided matching. Then, we aim to solve two problems: determining the competency degree of rescuers and calculating the time reliability of rescue teams arriving at disaster points. For the first one, we invite experts to evaluate pending rescue teams in terms of professional ability and collaboration ability using probabilistic linguistic term sets (PLTSs) because PLTSs not only keep original linguistic information but also give distributed expressions. For the second one, we determine the arriving time and calculating the time reliability by using the improved Bureau of Public Road (BPR) function. After that, we construct the two-stage multi-sided matching programming models based on the improved BPR function and PLTSs. Finally, a case study is used to demonstrate the proposed matching process, some comparative analyses and discussions are also conducted to validate the proposed models.

Exploring the thermal transport of graphene is significant for the application of its thermal properties. However, it is still a challenge to regulate the thermal conductivity of graphene interface. We study the interfacial thermal transport mechanism of the bilayer graphene by utilizing the molecular dynamics simulations. During the simulation, the interfacial thermal conductivity is regulated and controlled by lattice matching and tailoring. The lattice mismatched bilayer graphene model, combining the straining and torsion, can increase the interfacial thermal resistance (ITR) about 3.7 times. The variation trend of the ITR is explained by utilizing the vibrational spectra and the overlap factor. Besides, the thermal conductivity is proportional to the overlapping area. Our results show that the tailoring models can regularly control the thermal conductivity in a wide range by twisting the angle between upper and lower layers. These findings can provide a guideline for thermoelectric management and device design of thermal switch.

The probabilistic linguistic term set (PLTS) is a useful tool and has been widely applied to deal with uncertain information for decision-making problems. It allows the experts to evaluate the alte...

Residual carbon can be recycled from the solid-waste gasification fine slag by froth flotation which is suspended into bio-oil to produce a new type of slurry fuel, so the comprehensive utilization...

The coal fly ash produced by gasification is estimated to be over 80 million ton per year in China by 2021. It has mainly been disposed as solid waste by landfill. There is lack of study focused on its utilization. In this paper, the coal fly ash produced by gasification was at first analyzed and then applied to synthesize zeolite as an adsorbent. The effects of synthesis conditions on the cation exchange capacity (CEC) of zeolite were investigated. The results from X-ray diffraction and scanning electron microscope indicated that the crystallinity of the synthesized zeolite is the most important factor to affect the CEC. When the synthesized zeolite with the highest CEC (275.5 meq/100 g) was used for the adsorption of Cr(VI) from aqueous solution, the maximum adsorption capacity for Cr(VI) was found to be 17.924 mg/g. The effects of pH, contact time and initial concentration on the adsorption of Cr(VI) were also investigated. The adsorption kinetics and isotherms can be well described by the pseudo-second-order model and Langmuir isotherm model, respectively.

In multi-attribute two-sided matching (MATSM) problems, the attribute weights play an important role. The existing methods usually neglect the interaction and the effect among multiple attributes, resulting in irrational matching results. This paper takes this interaction into consideration. With the complexity of the matching environment, the uncertainties of agents should be considered. The probabilistic linguistic term set (PLTS) is a useful tool to describe the uncertainty and the limited cognition of agents. Thus, this paper aims to provide a novel MATSM method under the probabilistic linguistic environment with unknown attribute weights. Firstly, the attribute weights are determined by providing the probabilistic linguistic decision-making trial and evaluation laboratory (PL-DEMATEL) method. Besides, this paper constructs the gain and loss (GL) matrices and calculates the agents’ perceived values (PVs) by introducing prospect theory (PT). Then, the PVs are aggregated into the comprehensive PVs (CPVs) based on the obtained attribute weights. Next, this paper also proposes a ranking method, called probabilistic linguistic multi-attribute border approximation area comparison (PL-MABAC) method, to rank the multiple agents, which lay a solid foundation for stable matching constraint of the programming model. The matching results are obtained by solving the programming model. Finally, a case study of matching medical treatment service providers and demanders is presented to validate the proposed method. The comparative analyses and discussions are also provided to demonstrate its effectiveness.

The implementation of cost leadership strategy can enable enterprises to obtain a lasting competitive advantage. In this paper, we construct a supply chain with two competing suppliers and two competing manufacturers. The suppliers act as the Stackelberg leaders, selling components to the follower manufacturers. The manufacturers use different sourcing strategies, one of which only uses the reliable supplier, while another adopts contingent dual sourcing. We derive the analytical form of the equilibrium solution of order quantities of manufacturers and wholesale prices of suppliers in different scenarios and compare the decision differences when reliable supplier stays in different game positions. We further investigate the impact of different cooperation contract between the manufacturer who adopts dual sourcing and unreliable supplier on the procurement and pricing strategies by numerical experiments. The results illustrate that reliable supplier acts as the Stackelberg leader are more beneficial to suppliers. Manufacturer with dual sourcing can work with the unreliable supplier by revenue sharing contract to achieve a win–win situation.

Online customer reviews (OCRs) provide much information about products or service, but the mass of information increases the difficulty for customers to make decisions. Thus, we establish a multi-criteria decision making (MCDM) model to evaluate products or service. To analyze OCRs, the sentiment analysis (SA) is introduced to identify the sentiment orientation of reviews. Considering that the textual information in OCRs is linguistic information, probabilistic linguistic term sets (PLTSs) are applied to present the results of the SA. A process of extracting probabilistic linguistic information based on SA from OCRs is also presented. Then, for the MCDM problems with unknown criteria weights, we combine the PP (projection pursuit) method and the MULTIMOORA (multiplicative multi-objective optimization by ratio analysis) method, and develop an extended method (named as the PP-MULTIMOORA method). The projection pursuit (PP) method is developed to derive objective criteria weights and the MULTIMOORA method is to derive final rankings of products or service. Finally, we apply the proposed model to a case of evaluating doctors’ service quality and further conduct a comparative analysis to illustrate the effectiveness of our work.

Most traditional decision making methods cannot deal with intensive uncertain data that varies with time effectively, and they only derive the static risk analysis by different aggregation operators. There is little research of the dynamic decision making problems with massive uncertain information. To manage with different kinds of uncertain knowledge and hesitancy in the dynamic decision-making process, this paper combines the advantages of hesitant fuzzy sets (HFSs) in depicting information and Bayesian Network (BN) in uncertain reasoning. Considering the uncertain information of risk factors varies with time, the concept of Dynamic Hesitant Fuzzy Bayesian Network (DHFBN) is proposed to deal with dynamic decision making problems under the hesitant fuzzy environment. Then, an improved Particle Swarm Optimization (PSO) algorithm and the Expectation-Maximization (EM) algorithm are adopted for the structure learning and parameters learning of DHFBN respectively. Based on the learned optimal DHFBN, a dynamic reasoning and prediction method is developed. Furthermore, a case about the optimal port investment decision making problem of “21st Century Maritime Silk Road” is presented to illustrate the application of the proposed method. Finally, we also conduct a comparative experiment to testify the validity and advantages of the method in detail.

As new gasification materials for gasification industry, gasification-coke can be produced with coking coal, coal by-product, and a high ratio of low-rank coal. Microscopic structure of gasificatio...

By developing the complex phase perturbation for vortex pulsed beams in asymmetric oceanic turbulence and the spatiotemporal orthogonal basis for Lommel-Gaussian pulsed beam, we establish the received probability model of orbital angular momentum (OAM) modes for vortex pulsed beams propagating through asymmetric oceanic turbulence. Using this new model, we investigate the received probability and the pulse broadening of OAM modes of Lommel-Gaussian pulsed beam in asymmetric oceanic turbulence. Numerical simulation results show that Lommel-Gaussian pulsed beam causes a smaller pulse broadening when it propagates through oceanic turbulence with higher asymmetric factor, lower temperature structure constant, smaller inner scale and outer scale. In addition, Lommel-Gaussian pulsed beam with lower carrier frequency propagates through the oceanic turbulence with higher asymmetric factor, larger inner scale, smaller outer scale and smaller temperature structure constant, which obtains a higher received probability of signal OAM modes. For Lommel-Gaussian pulsed beams, the change of OAM quantum number has a week effect on the pulse broadening and the received probability.

Background 1-(4-isopropylphenyl)-β-carboline-3-carboxylic acid (ICCA) was modified by Trp-Phe-Phe to form 1-(4-isopropylphenyl)-β-carboline-3-carbonyl-Trp-Phe-Phe (ICCA-WFF). Purpose The object of preparing ICCA-WFF was to enhance the in vivo efficacy of ICCA, to explore the possible targeting action, and to visualize the nano-feature. Methods The advantages of ICCA-WFF over ICCA were demonstrated by a series of in vivo assays, such as anti-tumor assay, anti-arterial thrombosis assay, anti-venous thrombosis assay, P-selectin expression assay, and GPIIb/IIIa expression assay. The nano-features of ICCA-WFF were visualized by TEM, SEM and AFM images. The thrombus targeting and tumor-targeting actions were evidenced by FT-MS spectrum analysis. Results The minimal effective dose of ICCA-WFF slowing tumor growth and inhibiting thrombosis was 10-fold lower than that of ICCA. ICCA-WFF, but not ICCA, formed nano-particles capable of safe delivery in blood circulation. In vivo ICCA-WFF, but not ICCA, can target thrombus and tumor. In thrombus and tumor, ICCA-WFF released Trp-Phe-Phe and/or ICCA. Conclusion Modifying ICCA with Trp-Phe-Phe successfully enhanced the anti-tumor activity, improved the anti-thrombotic action, formed nano-particles, targeted tumor tissue and thrombus, and provided an oligopeptide modification strategy for heterocyclic compounds.

Fine slag (FS), a byproduct of coal gasification, consists of mineral-rich particles (MRP) and residual carbon particles (RCP). The characteristics of the MRP were investigated by laser particle si...

The two-sided matching has been widely applied to the decision-making problems in the field of management. With the limited working experience, the two-sided agents usually cannot provide the preference order directly for the opposite agent, but rather to provide the preference relations in the form of linguistic information. The preference relations based on probabilistic linguistic term sets (PLTSs) not only allow agents to provide the evaluation with multiple linguistic terms, but also present the different preference degrees for linguistic terms. Considering the diversities of the agents, they may provide their preference relations in the form of the probabilistic linguistic preference relation (PLPR) or the probabilistic linguistic multiplicative preference relation (PLMPR). For two-sided matching with the expected time, we first provide the concept of the time satisfaction degree (TSD). Then, we transform the preference relations in different forms into the unified preference relations (u-PRs). The consistency index to measure the consistency of u-PRs is introduced. Besides, the acceptable consistent u-PRs are constructed, and an algorithm is proposed to modify the unacceptable consistent u-PRs. Furthermore, we present the whole two-sided matching decision-making process with the acceptable consistent u-PRs. Finally, a case about aviation technology suppliers and demanders matching is presented to exhibit the rationality and practicality of the proposed method. Some analyses and discussions are provided to further demonstrate the feasibility and effectiveness of the proposed method.

Invisible photonic crystal (PC) pattern with encrypted and discoverable information is potentially useful for anti-counterfeiting labels, but it is still a big challenge to realize strict invisibility, fast response, and convenient triggering. Here, a new kind of soaking-revealed invisible PC pattern is fabricated by the regional coating of "ethylene glycol-ethanol" ink on a collapsed inverse opaline macroporous polyurethane (IOM-PU) film, followed by a quick thermal treatment. During the above process, wet heating retains the collapsed but recoverable IOM structure, but dry heating disables the recovery of ordered IOM structure due to the adhesion of macropore walls, which render the "pattern" and the "background" with different optical responses to the solvent. In the dry state, the pattern was invisible because both the collapsed IOM-PU film and the adhesive PU film are colorless and transparent. Once the sample is soaked in ethanol-water mixtures, the invisible pattern appears immediately because only the "wet-heated" region recovers the ordered macroporous structure and shows color, which forms a significant contrast in color to the "dry-heated" region. Compared to the previously invisible PC pattern, the current material has many superior properties, such as high invisibility, large color contrast in showing, excellent recyclability, and good toughness in bending and stretching.

In marine information networks, localization information is crucial for AUVs to label their collected data as well as to support intelligent auto-navigation or timely remote control. However, the extremely hostile underwater environments impose a number of challenges on designing AUV localization and tracking algorithms that can strike flexible balances among energy, accuracy, and practicability. To deal with these challenges, this article provides a systematic research roadmap for AUVs' localization and tracking, spreading from anchor deployment to time synchronization and range estimation and to trajectory prediction. Specifically, we first review the existing research on anchor deployment schemes, based on which we propose a spatially circular deployment configuration that achieves higher localization accuracy and discuss the anchors' number determination problem for balancing the energy-accuracy tradeoff. We then describe the principles for time synchronization and range estimation and summarize their state-of-the-art research advances. Finally, after introducing some widespread trajectory tracking methods, we develop a Kalman filtering based trajectory prediction algorithm to compromise tracking accuracy and signaling overheads. In particular, we also present and analyze the related open issues and challenges in each direction for future investigations.

In smart grid, the “smartness” usually comes from the two-way communication between the utility and its users as well as the sensing along the transmission lines. As a result, securing grid data that are transmitted over public network has always been one big challenge. Different authentication schemes have been proposed to address this security problem. However, most of them still suffer from privacy and/or performance issues. In this paper, we propose a lightweight anonymous authentication and key agreement scheme for smart grid, which allows the smart meter and the service provider to authenticate each other and establish a shared session key between them. Compared with existing authentication solutions for smart grid, it achieves fast mutual authentication between the smart meter and the service provider while ensuring the smart meter anonymity and untraceability. We evaluate the proposed scheme using Real-or-Random Oracle Model as well as the actual hardware prototype implementation. The results show that our proposed scheme can outperform the state-of-the art schemes in terms of the performance overhead while ensuring privacy protection.

Microscopic hydrogels, also referred to as microgels, find broad application in life and materials science. A well-established technique for fabricating uniform microgels is droplet microfluidics. Here, optimal mixing of hydrogel precursor components is crucial to yield homogeneous microgels with respect to their morphology, mechanics, and distribution of functional moieties. However, when processing premixed polymer precursors that are highly reactive, fast or even instantaneous gelation inside fluid reservoirs or the microchannels of the flow cell commonly occurs, leading to an increase of fluid viscosity over time, and thus exacerbating the intrinsic control over fluid flow rates, droplet and microgel uniformity, which are key selling points of microfluidics in material design. To address these challenges, we utilize microflow cells with integrated electrodes, which enable fast addition and mixing of hydrogel precursors on demand by means of emulsion droplet coalescence. Here, two populations of surfactant-stabilized aqueous droplets – the first containing the material basis of the microgel, and the second containing another gel-forming component (e.g., a crosslinker) are formed at two consecutive microchannel junctions and merged via temporary thin-film instability. Our approach provides the ability to process such hydrogel systems that are otherwise challenging to process into uniform droplets and microgels by conventional droplet microfluidics. To demonstrate its versatility, we fabricate microgels with uniform shape and composition using fast hydrogelation via thiol-Michael addition reaction or non-covalent self-assembly. Furthermore, we elucidate the limitations of electrocoalescence of reactive hydrogel precursors by processing sodium alginate, crosslinked by calcium-induced ionic interactions. For this instantaneous type of hydrogelation, electrocoalescence of alginate and calcium ions does not result in the formation of morphologically isotropic microgels. Instead, it enables the creation of anisotropic microgel morphologies with tunable shape, which have previously only been achieved by selective crosslinking of elaborate higher-order emulsions or by aqueous two-phase systems as microgel templates., Controlled electrocoalescence of droplet pairs containing fast-gelling hydrogel precursors is highlighted as a versatile method for processing reactive species into well-defined uniform microgels as well as a special type of anisotropic microgels with a tunable curvature via droplet microfluidics.

A submarine cable monitoring system based on enhanced coherent optical time-domain reflectometry (E-COTDR) is realized. An improved optimal peak-seeking (OPS) based I/Q demodulation method is employed for simultaneous loss measurement and vibration monitoring. A single-end diagnosis range over 74km is achieved for the proposed E-COTDR, enabling the double-end cooperative system to have a single-span of 148km. For the multi-span cascaded cables over 1000km, the loss and vibration monitoring without fading zone is carried out for a single-span of 121km. The proposed system provides a reliable technical option for the next generation underwater cable monitoring applications.

Transdermal drug delivery system (TDDS) is an attractive method for drug delivery with convenient application, less first-pass effect, and fewer systemic side effects. Among all generations of TDDS, transdermal nanocarriers show the greatest clinical potential because of their non-invasive properties and high drug delivery efficiency. However, it is still difficult to design optimal transdermal nanocarriers to overcome the skin barrier, control drug release, and achieve targeting. Hence, surface modification becomes a promising strategy to optimize and functionalize the transdermal nanocarriers with enhanced penetration efficiency, controlled drug release profile, and targeting drug delivery. Therefore, this review summarizes the developed transdermal nanocarriers with their transdermal mechanism, and focuses on the surface modification strategies via their different functions.

Social commerce is an extension of e‐commerce, in which social media is leveraged to promote user contributions. Our study asks how interruptions in relation to interface design influence two types of user contributions: creating shared content and appreciating others' content. We use two interface designs, pagination and infinite scrolling, to manipulate the extent of interruptions to social commerce users. On the basis of the capacity theory of attention, we develop five hypotheses. We empirically test our model using a lab experiment and a field study to show that interruptions reduce users' content appreciation but increase their content creation and that user characteristics moderate these effects. The theoretical and practical contributions of our study are discussed.

Considering the effects of the oceanic turbulence and pointing error on the communication link, we derive the analytical expressions of the wave structure functions and the spatial coherence radius for Gaussian waves propagating through oceanic turbulence in the unstable stratification. Based on the new spatial coherence radius, we develop the analytical model of the pointing error variance in oceanic turbulence. By this pointing error variance, the channel capacity model is established. By investigating the effects of oceanic turbulence and light source parameters on the pointing errors and the channel capacity, we find that the outer scale and the inner scale of oceanic turbulence have a significant influence on the pointing error and the channel capacity.

Field-effect transistors (FETs), when functionalized with proper biorecognition elements (such as antibodies or enzymes), represent a unique platform for real-time, specific, label-free transduction of biochemical signals. However, direct immobilization of biorecognition molecules on FETs imposes limitations on reprogrammability, sensor regeneration, and robust device handling. Here we demonstrate a modularized design of FET biosensors with separate biorecognition and transducer modules, which are capable of reversible assembly and disassembly. In particular, hydrogel "stamps" immobilizing bioreceptors have been chosen to build biorecognition modules to reliably interface with FET transducers structurally and functionally. Successful detection of penicillin down to 0.25 mM has been achieved with a penicillinase-encoded hydrogel module, demonstrating effective signal transduction across the hybrid interface. Moreover, sequential integration of urease- and penicillinase-encoded modules on the same FET device allows us to reprogram the sensing modality without cross-contamination. In addition to independent bioreceptor encoding, the modular design also fosters sophisticated control of sensing kinetics by modulating the physiochemical microenvironment in the biorecognition modules. Specifically, the distinction in hydrogel porosity between polyethylene glycol and gelatin enables controlled access and detection of larger molecules, such as poly-l-lysine (MW 150-300 kDa), only through the gelatin module. Biorecognition modules with standardized interface designs have also been exploited to comply with additive mass fabrication by 3D printing, demonstrating potential for low cost, ease of storage, multiplexing, and great customizability for personalized biosensor production. This generic concept presents a unique integration strategy for modularized bioelectronics and could broadly impact hybrid device development.

Hyperspectral image contains abundant spectral information with hundreds of spectral continuous bands that allow us to distinguish different classes with more details. However, the number of available training samples is limited and the high dimensionality of hyperspectral data increases the computational complexity and even also may degrade the classification accuracy. In addition, the bottom line is that only original spectral is difficult to well represent or reveal intrinsic geometry structure of the hyperspectral image. Thus, feature extraction is an important step before classification of high dimensional data. In this paper, we proposed a novel supervised feature extraction method that uses a new geometric mean vector to construct geometric between-class scatter matrix ($$S_b^G$$) and geometric within-class scatter matrix ($$S_w^G$$) instead of traditional mean vector of state-of-the-art methods. The geometric mean vector not only can reveal intrinsic geometry structure of the hyperspectral image, but also can improve the ability of learning nonlinear correlation features by maximum likelihood classification (MLC). The proposed method is called geometric mean feature space discriminant analysis (GmFSDA) that uses three measures to produce the extracted features. GmFSDA, at first, maximizes the geometric between-spectral scatter matrix to increase the difference between extracted features. In the second step of GmFSDA, maximizes the between-class scatter and minimizes the within-class scatter simultaneously. The experimental results on three real-world hyperspectral image datasets show the better performance of GmFSDA in comparison with other feature extraction methods in small sample size situation by using MLC.

The demand for distributed acoustic sensors, which are capable of reconstructing the amplitude, frequency, and phase of an acoustic field, is increasing. These sensors are typically realized by phase-sensitive optical time-domain reflectometry (Φ-OTDR). However, common Φ-OTDR systems suffer from a fading phenomenon, which causes amplitude fluctuation on Rayleigh backscattering traces, and the scattered light may not have enough intensity in some regions. These areas have low amplitude backscattering that may be even lower than the system noise floor during some periods of time. Therefore, we cannot reconstruct the phase signal properly in such low intensity areas. Systems with multiple frequencies have been proposed to achieve fading suppression. However, online data processing of such schemes remains a challenge, especially for continuous in-field applications. Prediction of fading must be performed in real time. Any delay caused by massive calculations is not acceptable. In this paper, a continuous fading suppression method based on a Φ-OTDR system with three different probe frequencies is presented as well as a tracking algorithm for selecting the optimum probe signal for any time, which predicts the occurrence of fading before it actually occurs. The performance of the proposed method has been experimentally evaluated and statistically analyzed. The distortion induced by the fading effect could be suppressed to 1.15% under continuous real-time running. The method is highly effective and repeatable, which makes it suitable for practical online purposes.

The ability to manipulate and control the inner surface properties of silica capillary is of crucial importance for analysis of proteins by capillary electrophoresis. In this work, surface-initiate...

Dendrimers have become effective drug carriers and gene transfection vectors for medical biomaterials. In this experiment, UCNPs (NaGdF4:Tm, Yb@NaGdF4) and three-generation PAMAM dendrimers...

We demonstrate an enhanced distributed acoustic sensing (DAS) system based on ultra-weak fiber Bragg grating (UWFBG) array and self-heterodyne detection. By using the interaction process between nearby UWFBGs, the distribution of acoustic field along the sensing fiber could be fully captured. Self-heterodyne detection was applied, leading to much lower noise density level for the proposed sensing system. The experimental results have shown that the acoustic field could be reconstructed with high fidelity even at the rear end of a 42 km long sensing fiber with the spatial resolution of 11.7 m. The proposed sensing system has a linear intensity response of R2 = 0.9988, while the peak-to-peak value (VPP) of dynamic strain was tuned from 9.28 nϵ to 176.96 nϵ. The root-mean-square (RMS) measurement error of our sensing system was less than 1.32 nϵ. The frequency response range of the proposed system was from 8 Hz to 1 kHz. The proposed sensing system offered a promising solution for the performance enhancement of DAS system that could achieve high spatial resolution, high sensing sensitivity, long sensing distance and dead zone free measurement at the same time.

We investigate the effects of the moderate to strong fluctuation on the propagation of orbital angular momentum (OAM) modes carried by Bessel Gaussian beams in turbulent atmosphere. The analytic expression of the received probability of the signal and crosstalk OAM mode is derived based on the theories of extended Rytov and non-Kolmogorov turbulence. Our results show that turbulence with smaller non-Kolmogorov index, smaller inner-scale factor is more easily to induce OAM crosstalk between modes. With the increase of turbulence strength, the OAM spreads from adjacent modes to peripheral modes. Our results also indicate that the received signal intensity can be improved by use of Bessel Gaussian beams with small initial radii of beam, low OAM quantum number and long wavelength.