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Traditional association rule mining has been widely studied, but this is not applicable to practical applications that must consider factors such as the unit profit of the item and the purchase quantity. High-utility itemset mining (HUIM) aims to find high-utility patterns by considering the number of items purchased and the unit profit. However, most high-utility itemset mining algorithms are designed for static databases. In real-world applications (such as market analysis and business decisions), databases are usually updated by inserting new data dynamically. Some researchers have proposed algorithms for finding high-utility itemsets in dynamically updated databases. Different from the batch processing algorithms that always process the databases from scratch, the incremental HUIM algorithms update and output high-utility itemsets in an incremental manner, thereby reducing the cost of finding high-utility itemsets. This paper provides the latest research on incremental high-utility itemset mining algorithms, including methods of storing itemsets and utilities based on tree, list, array and hash set storage structures. It also points out several important derivative algorithms and research challenges for incremental high-utility itemset mining.

Using CaO, Y2O3, Al2O3, and SiO2 micron-powders as raw materials, CaO–Y2O3–Al2O3–SiO2 (CYAS) glass was prepared using water cooling method. The coefficient of thermal expansion (CTE) of CYAS glass was found to be 4.3 × 10−6/K, which was similar to that of SiCf/SiC composites. The glass transition temperature of CYAS glass was determined to be 723.1 °C. With the increase of temperature, CYAS glass powder exhibited crystallization and sintering behaviors. Below 1300 °C, yttrium disilicate, mullite and cristobalite crystals gradually precipitated out. However, above 1300 °C, the crystals started diminishing, eventually disappearing after heat treatment at 1400 °C. CYAS glass powder was used to join SiCf/SiC composites. The results showed that the joint gradually densified as brazing temperature increased, while the phase in the interlayer was consistent with that of glass powder heated at the same temperature. The holding time had little effect on phase composition of the joint, while longer holding time was more beneficial to the elimination of residual bubbles in the interlayer and promoted the infiltration of glass solder into SiCf/SiC composites. The joint brazed at 1400 °C/30 min was dense and defect-free with the highest shear strength of about 57.1 MPa.

Ag/ZnO hybrid cages with well-preserved polyhedron shape and rich mesoporous structures were prepared thorough in situ pyrolysis of AgNO3 impregnated ZIF-8 precursor. Due to the bi-template function of ZIF-8, the as-prepared cages show well-defined hollow chamber inherited from the precursor and uniformly embedded Ag nanoparticles (NPs). The as-introduced Ag NPs could enhance the light absorption and promote charge separation, which finally improve the antibacterial performances. Therefore, compared with pure ZnO, the Ag/ZnO hybrid cages demonstrate prominent photocatalytic degradation of different organic dyes, such as Methylene Blue, Methylene Orange, Eosin and Rhodamine B under simulated sunlight. In addition, the hybrid Ag/ZnO cages exhibit outstanding inhibition performances against Escherichia coli, Staphylococcus aureus, and the highly infective Mycobacterium-tuberculosis. The photocatalytic and antibacterial mechanism of the hybrid Ag/ZnO cages were also studied in detail by means of optical/electrochemical dynamic tests and Ag+ and Zn2+ release measurements.

A combination method of precursor infiltration and pyrolysis (PIP), chemical vapor infiltration (CVI) and liquid silicon infiltration (LSI) was proposed to prepare PIP-SiC modified C/C–SiC brake materials. The SiC ceramic matrix pyrolyzed by polymethysilane (PMS) homogeneously dispersed in the fiber bundles region, which improved the plough resistance of local C/C region and the wear resistance of C/C–SiC brake materials. When the braking speed rises to 28 m/s, the fluctuation range of friction coefficient was limited to 0.026. The linear wear rate of the as-prepared composites was could be ~50% less than that of C/C–SiC, when the braking speed was above 15 m/s (for instance, the wear rate of 1.02 μm/(side·cycle) at 28 m/s less than 2.02 μm/(side·cycle) of traditional C/C– SiC). The fading ratio D of CoF under wet conditions was ~11%. The results showed that introducing PIP-SiC could stabilize the braking process and effectively prolong the service life of C/C–SiC brake materials.

Abandoned houses (AH) are focal points in urban communities by threatening local security, destroying housing markets, and burdening government finance in the U.S. legacy cities. In particular, individual-level AH detection provides essential information for fine-resolution urban studies, government decision-makers, and private sector practitioners. However, three primary conventional data sources (field data, utility data, and remote sensing data) cannot suffice to collect such fine-resolution data in the large spatial area via a cost-effective approach. To this end, Google Street View (GSV) imagery, which emerges as the mainstream open-access data source with global coverage, provides an opportunity to address this issue. Subsequently, a follow-up challenge confronting the detection of AH arises from the fact that it lacks an effective method that can discern authentic visual features from the redundant noise in GSV images. In this study, we aim to develop an effective method to detect individual-level AH from GSV imagery. Specifically, we developed a new hierarchical deep learning method to leverage both global and local visual features of AH in the detection. The method can be further divided into three steps: (1) Scene-based classification that can extract global visual features of AH was implemented through fine-tuning a pre-trained deep convolutional neural network (CNN) model. (2) We developed a patch-based classification method that can extract specific local features of AH. In this method, patches were generated from GSV images based on auto-detected local features, followed by being labeled as three categories: building patches, vegetation patches, and others. Two deep CNN models were employed to identify deteriorated building facade patches and overgrown vegetation patches, respectively. (3) Individual-level AH were detected by integrating scene classification results and patch classification results in a decision-tree model. Experimental results showed that the F-score of AH was 0.84 in a well-prepared dataset collected from five different Rust Belt cities. The proposed hierarchical deep learning approach effectively improved the accuracy comparing with the traditional scene-based method. In addition, the proposed method was applied to generate an AH map in a new site in Detroit, MI. Our study demonstrated the feasibility of GSV imagery in AH detection and showed great potential to detect AH in a large spatial extent.

As the permanent submarine support structures for subsea wells, pipeline manifolds and pipeline terminations, the mudmat foundation works under obviously complex, nonlinear and uncertain loading, w...

Deep neural networks (DNNs) have been widely adopted but they are vulnerable to intentionally crafted adversarial examples. Various attack methods against DNNs have been proposed, yet there still lacks theoretical explanation of adversarial examples. In this paper, we aim to understand adversarial examples from the attacking process and we assume adding perturbations to the key/sensitive regions of the image could fool image classification DNNs. We propose gradient shielding to verify the assumption which ignores insensitive information during generating adversarial examples. Specifically, we propose interactive gradient shielding (IGS) method which selects sensitive regions and then applies gradient-based attack. To remove region selection, we propose adaptive gradient shielding (AGS) method which ignores insensitive gradients automatically. We conduct extensive experiments to evaluate the performance and the results also corroborate our perspective. With this method, we won the first place in IJCAI-AAAC 2019 Non-targeted Adversarial Attack competition.

In this study, a fully nonlinear method, in the time domain, is used to simulate ship motion caused by large waves, and the problem of wave climbing along the freeboard in large waves is studied. The method is based on a three-dimensional potential flow theory. Further, the nonlinear free surface condition is adopted, the incident potential and disturbance potential are separated from each other, and the problem of determining the disturbance potential is established. In order to consider the nonlinearity of the body surface, the wetted surface area of the hull is continuously updated with time and extended along the tangential direction of the uppermost grid when the free liquid level exceeds the height of the hull deck. In addition, an artificial damping layer is provided to eliminate the reflection of waves at the outflow boundary. Under the fully nonlinear boundary conditions, the perturbation potential is solved by the Rankine source boundary element method. Introducing auxiliary functions solves the coupling problem between motion and load in the process of solving rigid body motion equations. After the solution is completed, it is updated to the next time step using the Runge-Kutta 4th order method. In this study, the convergence of the computational grid of the numerical model is firstly verified. Then, the motion and load responses of a zero-speed ship in the regular wave of unit wave amplitude using this method are examined and compared with the linear method. The latter verifies the accuracy of this method in the linear field. Afterwards, in order to investigate the superiority of the fully nonlinear method when the nonlinear phenomenon is strong, the motion and load of the ship in the large amplitute wave are simulated and the influence of the nonlinear phenomenon is analyzed. Finally, the phenomenon of wave climbing generated in high waves is analyzed, and the relationship between wave and water heights is evaluated.

MAA (mesh aluminium alloy) is one of the most widely used explosion suppression materials in military and civilian applications. To systematically research the effect of MAA on the explosion reactions of flammable gases, we investigated the effect of MAA and AV (aluminium velvet) on the explosion of hydrogen-air, methane-air and acetylene-air mixtures. The results indicated that MAA and AV suppress the methane-air mixture explosion but significantly promote the explosions of the hydrogen-air mixture and the acetylene-air mixture. MAA and AV have the dual effect of promoting and suppressing an explosion. In addition, with an increase in filling density, the promotion of MAA and AV first strengthens and then weakens. The results of this study show that the properties of flammable gas, not the shapes of the explosion suppression materials, determine whether the dominant effect of explosion suppression material is promotion or suppression. Use of explosion suppression materials is not suitable for all flammable gases, especially highly reactive chemical fuels. Applying explosion suppression materials blindly may greatly increase safety risk.

We present an efficient approach for temporal action co-localization (TACL), which means to simultaneously localize all action instances in an untrimmed video. Compared with the conventional instance-by-instance action localization, TACL can exploit the contextual and temporal relationships among action instances to reduce the localization ambiguities. Motivated by the strong relational modeling capability of graph neural networks, we propose a Graph-based Temporal Action Co-Localization (G-TACL) method. By considering each action proposal as a node, G-TACL effectively aggregates contextual and temporal features from related action proposals to jointly recognize and localize all action instances in a single shot. Moreover, we introduce a novel multi-level consistency evaluator to measure the relatedness between any two action proposals. This is achieved by considering their high-level contextual similarities, low-level temporal coincidences and feature correlations. We exploit the Gated Recurrent Units (GRUs) to iteratively update the features of each node, which are then used to regress the temporal boundaries of action proposals and finally achieve action co-localization. Experimental results on three datasets, i.e., THUMOS14, MEXaction2 and ActivityNet v1.3 datasets demonstrate that our G-TACL is superior or comparable to the state-of-the-arts.

This study considers the tracking control problem of the nonstrict-feedback nonlinear system with unknown backlash-like hysteresis, and a finite-time adaptive fuzzy control scheme is developed to address this problem. More precisely, the fuzzy systems are employed to approximate the unknown nonlinearities, and the design difficulties caused by the nonlower triangular structure are also overcome by using the property of fuzzy systems. Besides, the effect of unknown hysteresis input is compensated by approximating an intermediate variable. With the aid of finite-time stability theory, the proposed control algorithm could guarantee that the tracking error converges to a smaller region. Finally, a simulation example is provided to further verify the above theoretical results.

Timely mapping of corn and soybean plays an important role in food security in the USA. A subpixel fraction derived from Land Remote-Sensing Satellite (System, Landsat) imagery during growing seaso...

In this article, we investigate the privacy issue of the remote state estimation problem in cyber-physical systems. Specifically, in the presence of an eavesdropper, a sensor observes a discrete linear time-invariant process and then sends the measurements to a remote state estimator with arbitrary finite kinds of transmission options through an unreliable wireless channel. The transmission options of the sensor are in silence state or transmitting aided by injection noise with different energy levels. The eavesdropper wiretaps the channel when the sensor transmits packets to the estimator. Aiming at minimizing the remote estimation error and the cost of the sensors transmission energy while maximizing the eavesdropper state estimation error, we theoretically prove that there exist some structural properties for the optimal transmission schedule for both the known and the unknown eavesdropper's estimation errors. Numerical simulation results are provided to validate the theoretical analysis.

A series of experiments were conducted to investigate the wettability of graphite plate, graphite paper, NWCNTs Buckypaper, CVD-diamond by molten Ce and graphite plate by Cu–Ce binary alloy using a modified sessile drop method at 950 °C. The remarkable apparent equilibrium contact angles (graphite plate (0°)

PurposeThe purpose of this paper is to understand the antecedents of peer recommendations (generating positive word-of-mouth and recruiting others) in the context of mobile social games.Design/methodology/approachDrawing on the needs–supplies fit framework and social identity theory, this paper proposes that game design characteristics (challenge, fairness, innovativeness and ease of use) influence game identification, which further predicts word-of-mouth (WOM) generation and recruitment intention. This paper further suggests fits between gamer orientation (passing time and seeking achievements) and game design lead to enhanced game identification. The model was tested using data from an empirical survey with 767 mobile social gamers.FindingsGame challenge, game fairness, game innovativeness and ease of use are positively associated with game identification, whereas game identification positively predicts WOM generation and recruitment intention. Achievement-seeking use was found to enhance the effects of game challenge and game fairness on game identification, and passing time use was found to strengthen the effects of game innovativeness and ease of use on game identification.Research limitations/implicationsThe findings of this study provide operable implications to facilitate peer recommendations in a mobile gaming context. The model was only tested within the context of mobile social games, however, so caution is advised when generalizing the findings to other game subgenres.Originality/valueThis study distinguishes itself from other peer recommendation studies by taking recruitment, a more straightforward and salient form of peer recommendation, into account. This paper enriches theory by investigating the antecedents and consequences of game identification. This study clarifies the underlying mechanism of how game design influences peer recommendations and examines the interactions between game design and gamer orientation.

Sortition is one fairness-preserving decision-making method, whereby each of the involved legitimate users can obtain a completely random but mutually different message. Here, using the fantastic high-dimension multi-particle singlet states as the random lot pool, we propose the first authenticated quantum sortition protocol in theory with some desirable properties of privacy, fairness, and uniqueness, which shows particular function glamour over to the classical sortitions. The proposed protocol also can expand to solve some related problems, defined as “picking at random”. Any effective attacks from an outside eavesdropper, semi-honest designated authority, and inside malicious user will be detected by honest participants, and thus guarantee the security. This work to sortition theory helps elucidate how quantum mechanics can be harnessed for secure strategic advantage.

Oral administration is a facile and safe way for medication. However, most of the reported nanomedicines could not be taken orally, partially due to their unsatisfied stability, poor absorbance, or toxicity in the gastrointestinal tract. Here, we demonstrate that we could robustly synthesize gold nanoparticles (GNPs) in vivo by orally administering two starting materials, tetrachloroauric acid and aminophenyl boronic acid (ABA). The ABA-activated GNPs (A-GNPs) synthesized in vivo could be absorbed by the gastrointestinal tract and reach the remote infection lesions such as peritonitis caused by multidrug resistant (MDR) bacteria in mice. The A-GNPs exhibit excellent antibacterial efficacy (MIC, 3 μg/mL), long half-life (16-17 h), effective clearance (residual concentration is near 0 within 72 h), and high biosafety (safe dose/effective dose, 8 times). Our study is a pioneering attempt for synthesizing and taking nanomedicines orally just like preparing and drinking a cocktail.

Yellow-emitting YAG:Ce transparent ceramic is recognized as an ideal color converter in high-power blue LEDs and LDs, but the absence of scattering centers in its microstructure leads to a low light extraction efficiency and poor light uniformity. Here, taking advantage of the scattering effect and the transparency of YAG:Ce ceramics, Ce-free YAG phase was used as a second component to form a composite with YAG:Ce phosphor. The sintered YAG:Ce-YAG ceramic possessed a high transparency of ∼63 % and a thermal conductivity of 8.9 Wm−1 K−1. Due to its beneficial thermal properties and high external quantum efficiency of 70.2 %, the YAG:Ce-YAG ceramic could be excited under a high blue-laser flux density of up to 9.60 W/mm2 and showed a luminous emittance of 1220 lm/mm2. Due to light scattering arising from the slightly different refractive indices of the two phases, the designed YAG:Ce-YAG ceramic showed better lighting effects than a single-phase transparent YAG:Ce ceramic.

This paper studies the classification of unbalanced data sets. First, this kind of data sets is briefly introduced, and then the classification methods of unbalanced data sets are analyzed in detail from different perspectives such as data sampling method, algorithm level, feature level, cost-sensitive function, and deep learning. In addition, the data sampling methods are divided into different technologies for introduction: unbalanced data set classification method based on synthetic minority over-sampling technology (SMOTE), support vector machine (SVM) technology, and k-nearest neighbor (KNN) technology, etc. Then, the advantages and disadvantages of these methods are compared. Finally, the evaluation criteria of the unbalanced data set classifier are summarized, and the future work directions are prospected and summarized.

With the target of simultaneously segmenting semantically related videos to identify the common objects, video object cosegmentation has attracted the attention of researchers in recent years. Existing methods are primarily based on pair-wise relations between adjacent pixels and regions, which are susceptible to performance degradation from object entries/exists or occlusions. Specifically, we refer these video frames without the common objects present as the “empty” frames. In this paper, we propose a multilevel hypergraph-based full Video object CoSegmentation (VCS) method, which incorporates high-level semantics and low-level appearance/motion/saliency to construct the hyperedge among multiple spatially and temporally adjacent regions. Specifically, the high-level semantic model fuses multiple object proposals from each frame instead of relying on a single object proposal per frame. A hypergraph cut is subsequently utilized to calculate the object cosegmentation. Experiments on four video object segmentation/cosegmentation datasets against state-of-the-art methods with both objective and subjective results manifest the effectiveness of the proposed VCS method, including the SegTrack and VCoSeg datasets without “empty” frames, the XJTU-Stevens dataset with 3.7% “empty” frames, and the Noisy-ViCoSeg dataset proposed together with our method with 30.3% “empty” frames.

Carbon dots (CDs), possessing unexpected advantages of photostability, biocompatibility and low toxicity, are regarded as novel nanomaterials in fluorescence (FL) imaging. Doping Gd element in CDs makes them have the ability to be used for magnetic resonance (MR) and FL imaging simultaneously. However, CDs reported before exhibit obvious defects like low photoluminescence (PL) quantum yield (QY) or biotoxicity. In this work, we use gadolinium meglumine, a material with relatively low biotoxicity, along with citric acid and diethylenetriamine to synthesize Gd-doped CDs (Gd-CDs) by a one-step hydrothermal method. The prepared Gd-CDs exhibit excitation-independent emission with a PL QY of 78.05% and a longitudinal relaxivity of 7.37 mM-1 S-1, which endows the composite with high-performance in MR/FL imaging. Meanwhile, the FL intensity of Gd-CDs remains stable in the presence of multiple amino acids, which indicates that the FL imaging effect should not be impacted significantly in microenvironments in vivo. In addition to the inconspicuous cytotoxicity, Gd-CDs could be used efficiently for dual-modal molecular imaging to detect diseases such as tumors in the early stages.

For high-order linear networked systems with switching topologies and the random communication silence, energy-constraint output formation problems are investigated. Firstly, the dynamics associated with the coordinated output is decomposed from the whole dynamics of each intelligent agent and a new control protocol is constructed on the basis of the coordinated outputs and the protocol states of neighboring intelligent agents, where switching topologies, the energy constraint and the random communication silence are contained. Then, by introducing the silent rate and the dwell time, the impacts of the random communication silence and switching topologies are dealt with and sufficient conditions for energy-constraint output formation design and analysis are proposed, where the output formation feasible conditions are required to guarantee the output formation achievement property. Especially, an explicit expression of the output formation center function is determined, which depicts the whole motion of a networked system when energy-constraint output formation is achieved. Finally, a numerical example is given to demonstrate theoretical conclusions.

Copper oxide has aroused great concern in energy storage fields due to its properties of high theoretical capacitance, low cost and mild toxicity. However, its wide application still remains challenges owing to its poor electrical conductivity and unstable cycling life. Binder-free foam electrodes possess abundant porous structures and high specific surface area, which could get good contact with electrolyte. Herein, we demonstrate Ag nanoparticles decorated CuxO nanowires grown spontaneously on copper foam (CF) electrode for asymmetric supercapacitor. The skeleton structure of CF provides large amounts of active sites for the growth of CuxO nanowires. Moreover, Ag nanoparticles further decrease the internal resistance and enhance the electrochemical performance. Ag/CuxO/CF-40 electrode presents a high area specific capacitance of 1192 mF cm−2 at 2 mA cm−2 and the influence of surface capacitance-dominated process and diffusion-controlled process are discussed in detail. Besides, the energy density of the as-prepared asymmetric supercapacitor (ASC) reaches 46.32 μWh cm−2 at a power density of 3.00 mW cm−2. A 2V LED is lighted successfully by two ASC in series. This work provides a new strategy to prepare low internal resistance and binder-free flexible Ag/CuxO/CF electrode, which demonstrates a good potential application in flexible supercapacitors or other wearable electronic devices.

Fingerprints form when fingers touch a solid surfaceand are considered the best way for individual identification. However, the current latent fingerprint (LFP) developing methods cannot meet the demand for high sensitivity and being convenient and healthy. Herein, bifunctional Fe3O4@SiO2-CsPbBr3 powders have been designed and fabricated and exhibit good magnetic and strong fluorescent properties. The magnetism of Fe3O4 can avoid dust flying, while the fluorescence of CsPbBr3 ensures the high definition of LFPs. Clear fingerprints have been detected on various solid substrates using the Fe3O4@SiO2-CsPbBr3 powders instead of eikonogen. Detailed characterization studies suggest that the ammonium cationic groups on the surface of nanoparticles (NPs) have strong adhesive interactions with the residues of fingerprints because of the electrostatic attraction between them. Therefore, the convenient operation and excellent resolution offer great opportunity in the practical application of fingerprint detection and other areas.

In order to study the process of Fe3O4 reduction by melt electro-deoxidation. Electrochemical method was used to analyze the reduction mechanism of Fe3O4 in NaCl-CaCl2 melts. The effects of cell voltage and time on the product were discussed through constant cell voltage electrolysis. The results showed: (1) The reduction of solid Fe3O4 to metallic Fe is a two-step process for obtaining electrons. (2) The transformation process (600 min, 0–1.0 V) of the electrolysis products with the increase of the cell voltage is as follows: Fe3O4 → FeO → FeO + Fe → Fe. (3) The intermediate product Ca2Fe2O5 was formed (2.0 V, 10–300 min), which inhibited the deoxygenation process in the early stage of the reaction. When the electrolysis time exceeds 60 min, the main reaction is the reduction of Ca2Fe2O5 to Fe.

In this study, Y2O3–Al2O3–SiO2 (YAS) glass was prepared from Y2O3, Al2O3, and SiO2 micron powders. Thermal expansion coefficient of as-obtained YAS glass was about 3.9 × 10−6, matching-well with that of SiCf/SiC composites. SiCf/SiC composites were then brazed under pressure-less state by YAS glass and effects of brazing temperature on microstructures and properties of resulting joints were investigated. The results showed that glass powder in brazed seam sintered and precipitated yttrium disilicate, cristobalite, and mullite crystals after heat treatment. With the increase in temperature, joint layer gradually densified and got tightly bonded to SiCf/SiC composite. The optimal brazing parameter was recorded as 1400 °C/30 min and shear strength of the joint was 51.7 MPa. Formation mechanism of glass-ceramic joints was proposed based on combined analysis of microstructure and fracture morphology of joints brazed at different temperatures. Thermal shock resistance testing of joints was also carried out, which depicted decline in shear strength with the increase of thermal shock times. The strength of the joint after three successive thermal shock cycles at 1200 °C was 35.6 MPa, equivalent to 69% of that without thermal shock.

Low-dimensional metal halide hybrids (OIMHs) have recently been explored as single-component white-light emitters for use in solid-state lighting. However, it still remains challenging to realize tunable white-light emission in lead-free zero-dimensional (0D) hybrid system. Here, a combination strategy has been proposed through doping Sb3+ enabling and balancing multiple emission centers toward the multiband warm white light. We first synthesized a new lead-free 0D (C8NH12)6InBr9·H2O single crystal, in which isolated [InBr6]3- octahedral units are separated by large organic cations [C8NH12]+. (C8NH12)6InBr9·H2O exhibits dual-band emissions with one intense cyan emission and a weak red emission tail. The low-energy ultrabroadband red emission tail can be greatly enhanced by the Sb3+ doping. Experimental data and first-principles calculations reveal that the original dominant cyan emission is originated from the organic cations [C8NH12]+ and that the broadband red emission is ascribed to self-trapped excitons in [In(Sb)Br6]3-. When the Sb concentration is 0.1%, a single-component warm white-light emission with a photoluminescence quantum efficiency of 23.36%, correlated color temperature of 3347 K, and a color rendering index up to 84 can be achieved. This work represents a significant step toward the realization of single-component white-light emissions in environmental-friendly, high-performance 0D metal halide light-emitting materials.

Multidrug-resistant (MDR) bacteria-induced infections are becoming challenging issues threatening human health and life. Current antibiotics can hardly tackle this problem. Herein, we present a strategy to prepare mercaptophenylboronic acid (MBA)-activated gold nanoparticles (Au NPs) as an antibacterial agent against MDR bacteria. Both Au NPs and MBA cannot serve as antibiotics. However, when MBA attaches on Au NPs, the Au_MBA NPs show potent antibacterial activities against Gram-positive MDR clinical isolates (e.g., MDR Staphyloccocus aureus, MDR S. aureus; MDR Staphyloccocus epidermidis, MDR S. epidermidis). Furthermore, Au_MBA NPs show an extremely high median lethal dose (LD50,i.v., 960 mg/kg), which is much higher than those of most of the clinically used antibiotics. As an application example, we dope Au_MBA NPs with electrospun poly(e-caprolactone) (PCL)/gelatin nanofibrous membranes as wound dressings, which show striking ability to remedy S. aureus- or MDR S. aureus-infected full-thickness skin wounds on rats. Our study provides a novel strategy for treating MDR bacteria-infected wounds in a simple, low-cost, and efficient way, which holds promise for broad clinical applications.

Epitaxial Fe3O4 thin films grown on single crystal MgO(001) present well-defined model systems to study fundamental multivalent ion diffusion and associated phase transition processes in transition...

Isolation and screening of microalgal species from natural habitats should be a continues work to discover effective species for biofuel generation and wastewater treatment. In the current study, microalgal species namely Tetradesmus dimorphus GEEL-04 and Desmodesmus asymmetricus GEEL-05 were isolated, identified, and assessed for growth kinetics, nutrients removal efficiency, and whole biomass composition. T. dimorphus showed higher growth (1.46 OD680nm) compared with D. asymmetricus (1.16 OD680nm), and both showed 99% total nitrogen and total phosphorous removal. T. dimorphus and D. asymmetricus accumulated higher protein content (40.02 and 45.10%), carbohydrate (31.91 and 24.64%), and lipid (15.41 and 24.16%), respectively. The FTIR spectra absorbance revealed different function groups in microalgal biomass available for biofuel generation. Elemental analysis of microalgal biomass showed high carbon content 50.13% and 43.01% for T. dimorphus and D. asymmetricus, respectively. Thermogravimetric analysis indicated ≥ 80% volatile content in both isolates. The fatty acid composition of both microalgal strains showed high palmitic acid and linoleic acid corresponding to high quality biodiesel. These results indicated that the T. dimorphus and D. asymmetricus could be potential candidates for high biocomponents accumulation and N, P removal.

This paper discusses limited-budget time-varying formation design and analysis problems for a high-order linear swarm system with a fixed communication topology. Firstly, the communication topology among agents is modeled as an undirected and connected graph, and a new formation control protocol with an energy integral term is proposed to realize formation control and to guarantee the practical energy assumption is less than the limited energy budget. Then, by the matrix inequality tool, sufficient conditions for limited-budget formation design and analysis are proposed, respectively, which are scalable and checkable since they are independent of the number of agents of a swarm system and can be transformed into linear matrix inequality constraints. Moreover, an explicit expression of the formation center function is given, which contains the formation function part and the cooperative state part and is not associated with the derivatives of the formation functions. Finally, a numerical simulation is shown to demonstrate the effectiveness of theoretical results.

Ti3SiC2, as ternary layered ceramic with good electrical and thermal conductivity, has great application potential in the field of absorbing materials. Absorbing materials are also increasingly required to be lightweight, ultrathin, and flexible. Herein, Ti3SiC2/poly (TEP, DOP and PVB) composite film was biomimetically designed and fabricated by type casting process. As-fabricated composite film with 38% content of Ti3SiC2 was only 1.62 mm in thickness but exhibited excellent absorbing performance. The maximum reflection loss value of Ti3SiC2-based films was as high as −38.41dB and absorption bandwidth below −10 dB was 2.480 GHz. Polymer matrix wrapped around Ti3SiC2 not only enhanced the flexibility of the film, but also regulated its impedance matching and complex dielectric constant compared with pure Ti3SiC2. Superior wave absorption and flexibility imply excellent potential of this Ti3SiC2-based composite film for eliminating electromagnetic interference.

This study investigated the limited-budget finite-time average consensus problem of multi-agent systems. Different from the existing results about the guaranteed-cost asymptotical consensus, all agents can achieve the average consensus within a finite time and the limited budget can be given previously. Firstly, a novel consensus protocol is proposed with non-linear cost indexes to trade off the control energy consumption against the consensus regulation performance for the limited budget within a finite time. Then, sufficient conditions for limited-budget finite-time average consensus design and analysis are respectively given, where the limited budget is utilised to determine the value range of the control gain, and the consensus value obtained by all agents is the average of initial states. Moreover, for the case without giving the limited budget, guaranteed-cost finite-time average consensus design and analysis criteria are presented, respectively, in which an upper bound of the cost index is determined. Finally, a numerical simulation is shown to illustrate the effectiveness of theoretical results.

Cancer therapeutics are varied and target diverse processes in cancer progression. Photodynamic therapy (PDT), photothermal therapy (PTT), and the inhibition of pro-cancer proteases are non-invasive anticancer therapeutics that attract increasing attentions for their enhanced specificities and milder systemic toxicities compared to traditional therapeutics. These modalities offer advantages to compensate for the shortcomings of their counterparts. For instance, PDT or PTT efficiently eliminates locally confined tumor cells while exhibiting no effect on metastatic tumor cells. In contrast, the inhibition of pro-cancer proteases systemically suppresses the proliferation and metastasis of cancer cells but does not eradicate existing cancer cells. To synergize these therapeutics, we hereby report a versatile nanoparticle that integrates the effects of PDT, PTT, and enzyme-inhibition. This nanoparticle (CIKP-NP) was synthesized by covalently or non-covalently modifying a photothermal nanoparticle with a photosensitizer, a pro-cancer protease inhibitor, and an albumin-binding molecule. After confirming the PDT, PTT, albumin-binding, and enzyme-inhibition properties at the molecular level, we demonstrated that CIKP-NP killed tumor cells through PDT or PTT and suppressed tumor cell invasion through enzyme-inhibition. In addition, through a breast cancer xenograft mouse model, we demonstrated that CIKP-NP suppressed tumor growth by PDT or PTT effect. Notably, the synergism of PDT and PTT significantly enhanced its anticancer efficiency. Furthermore, CIKP-NP significantly suppressed cancer metastasis in a lung metastatic mouse model. Last, biodistribution and the in vivo retention of CIKP-NP confirmed the tumor-targeting property. Beyond demonstrating the anti-tumor and anti-metastatic efficacy of CIKP-NP, our study also suggests a new strategy to synergize multiple anticancer therapeutics.

Ti3C2TX MXenes have great application prospects in the electromagnetic shielding field owing to their unique accordion structure and excellent electrical conductivity. However, understanding the correlation between their thermal stability and electromagnetic shielding performance is still lacking. Additionally, owing to the complex etching environment, some termination groups are present on the surface of MXenes, significantly affecting their thermal and electromagnetic performance. Here, to solve these problems, a heat treatment process was used. In this study, the effect of heat treatment on the removal of these surface adsorption groups was evaluated. Moreover, the evolution of structure, phase, and electromagnetic shielding properties of MXenes with the change in heat treatment temperature was also studied in detail. After heat treatment at 1100 °C, the phase of MXenes changed. Multilayer-TiC, a derivative of MXenes, still exhibited excellent shielding performance, which can be attributed to the elimination of surface end groups, the maintenance of multiple structure, and the increase in content about amorphous C. The total and absorbing shielding effectiveness reached 76.1 dB and 61.3 dB, respectively. Its conductivity was 265 S/m. This study is valuable in studying application prospects of Ti3C2TX MXene in high temperature fields, such as the field of electromagnetic shielding.

BACKGROUND: The cardiomyocyte apoptosis is considered as one of major contributions to cardiac remodeling after myocardial infarction (MI). Numerous studies find that circular RNAs (circRNAs) play pivotal roles in a variety of biological functions. However, the role of circ_0068655 in MI and human induced pluripotent stem-derived cardiomyocytes (HCMs) remains unknown. METHODS: The expression of circ_0068655, miR-498, and PRKC apoptosis WT1 regulator (PAWR) in human MI heart tissues and hypoxia subjected HCMs was evaluated with qRT-PCR and Western blot. The effects of circ_0068655 on hypoxia-induced apoptotic death and cell migration in HCMs were evaluated with qRT-PCR, cell viability, cell death ELISA (POD), and Caspase-3 activity assay, and Trans-well assay, respectively. Furthermore, luciferase assay, qRT-PCR, biotin-labeled miRNA pulldown assay, and Western blot were employed in the functional studies. RESULTS: We found that the expression of circ_0068655 and PAWR was enhanced in MI patients and hypoxia subjected HCMs; by contrast, the expression of miR-498 decreased. Inhibited expression of circ_0068655 in HMCs counteracted hypoxia-induced apoptotic death and impaired cell migration, in sharp contrast to circ_0068655 knockdown. We identified that circ_0068655 sponged an endogenous miR-498 to sequester and inhibit its activity, leading to the increased PAWR expression. CONCLUSIONS: Our findings reveal that the expression of circ_0068655 can promote cardiomyocyte apoptosis through the modulation of miR-498-PAWR axis in vitro, which highlights the diagnostic and therapeutic value of circ_0068655 in patients with MI.

Circularly polarized light carries light spin angular momentum, which may lead helicity-resolved Raman scattering to be sensitive to the electronic spin configuration in magnetic materials. Here, we demonstrate that all Raman modes in the 2D ferromagnet VI3 show different scattering intensities to left and right circularly polarized light at low temperatures, which gives direct evidence of the time-reversal symmetry breaking. By measuring the circular polarization of the dominant Raman mode with respect to the temperature and magnetic field, the ferromagnetic (FM) phase transition and hysteresis behavior can be clearly resolved. Besides the lattice excitations, quasielastic scattering is detected in the paramagnetic phase, and it gradually evolves into the acoustic magnon mode at 18.5 cm-1 in the FM state, which gives the spin wave gap that results from large magnetic anisotropy. Our findings demonstrate that helicity-resolved Raman spectroscopy is an effective tool to directly probe the ferromagnetism in 2D magnets.

Nowadays, we are in a typical information age, and network and information security systems are facing severe challenges. However, there is currently no suitable method for the detailed analysis and protection of Internet information security. In order to analyze Internet security information more accurately, we proposed an improved KPCA (Kernel Principle Component Analysis) algorithm within the context of the big data era and in view of the shortcomings and disadvantages of the KPCA feature extraction algorithm. The proposed algorithm not only retains its performance ability, but also improves the subsequent classification ability. This paper uses the KDDCUP99 security audit data set to simulate network intrusions, and the data set used network information data resources within a total of 9 weeks. The training data set contains a total of 7 weeks of data information, and the other 2 weeks of data information are used as a validation data set. The training data set contains a total of 5 million records of network security information, while the verification data set contains 2 million records. The experimental results show that for the network intrusion classification test, the improved algorithm is more efficient, convenient, and faster than the traditional KPCA one. Furthermore, the simulation results also show that the proposed algorithm has achieved a very high degree of accuracy and improvement in terms of “accuracy rate,” “false alarm rate,” and “missing alarm rate.”

The current paper investigates energy-constraint formation design and analysis problems for multiagent systems with two types of switching interaction topologies; that is, leaderless ones and leader-following ones. Firstly, a new formation control protocol with switching interaction topologies is shown, where the whole energy supply is limited previously. Then, by constructing the relationship of the whole energy supply and the matrix variable, sufficient conditions for leaderless energy-constraint formation design and analysis are respectively presented by the linear matrix inequality tool. Furthermore, an approach is proposed to determine an explicit expression of the formation center function, which determines the macroscopic motion of a multiagent system as a whole and consists of two parts: the initial state term and the formation function term. Moreover, main conclusions of leaderless energy-constraint formation are extended into leader-following multiagent systems by a new two-step transformation approach, where the asymmetric structure feature of leader-following switching interaction topologies is well dealt with. Finally, two numerical examples are provided to demonstrate the effectiveness of main conclusions.

The joint intelligence ranking of intelligent systems like autonomous driving is of great importance for building a more general, extensive, and universally accepted intelligence evaluation scheme. However, due to issues such as privacy security and industry or area competition, the integration of isolated test results may face large unimaginable difficulty in information security and encrypted model training. To address this, we derive the federated multiplicative update (FMU) algorithm with boundary constraints to solve the nonnegative matrix factorization based joint intelligence ranking. The encrypted learning process is developed to alternate original computation steps in multiplicative update algorithms. Owning feasible property for the fast convergence and secure exchange of variables, the proposed framework outperforms the previous work on both real and simulated data. Further experimental analysis reveals that the introduced federated mechanism does not harm the overall time efficiency.

Pretreatment to enhance the enzymatic digestibility of cellulose usually alters the structure of lignin, resulting in subsequent inferior depolymerization and utilization. Herein, a physicochemical pretreatment strategy, specifically, using a recyclable acid hydrotrope (p-toluenesulfonic acid, p-TsOH) followed by 10 s of ultrasonic treatment, was developed to facilitate high-value lignin extraction from lignocellulosic biomass and improve enzymatic hydrolysis for high-titer ethanol production. The wood material (poplar) was first treated with the recyclable p-TsOH aqueous solution under mild conditions (C80T80t15) to extract the lignin. The obtained lignin exhibited excellent properties, including a high hydroxyl (OH) content (4.19 and 4.07 mmol/g of aliphatic and phenolic OH, respectively), abundant β-O-4 aryl ether linkages (60%), a low Mw (3357 ± 121 g/mol), and a narrow polydispersity (2.28, Mw/Mn), according to the results from FTIR spectroscopy, TGA, 31P NMR spectroscopy, 2D-HSQC NMR spectroscopy, and GPC. The pretreated substrates were then subjected to 10 s of ultrasonication to improve the enzymatic saccharification and finally afford ethanol by quasi-simultaneous enzymatic saccharification and fermentation (Q-SSF). The highest ethanol concentration (40.08 ± 3 g/L) was obtained after 60 h of fermentation, and the residual glucose concentration was only 4.22 ± 1 g/L; this experimental ethanol yield was equivalent to the theoretical ethanol yield of 81.87 ± 4% based on the glucan content. In short, this pretreatment method simultaneously enhanced the accessibility of cellulose to enzymatic hydrolysis and provided high-value lignin.

Determining the role of lattice oxygen in the oxygen evolution reaction (OER) is pivotal to understanding reaction mechanisms and predictive design of electrocatalysts based on transition metal oxi...

Fluidised bed technology is a very common industrial process and has a wide range of applications in process engineering. Though indirectly, a common way to infer the end product uniformity is through investigating the solid residence time distribution (RTD) in the system. A good understanding of the particle RTD is crucial for the proper design, optimisation, and scale-up of a fluidisation process. Flexible ribbon particles have a very different flow behaviour in a fluidised bed compared to that of spheres which in turn influences the RTD of the particles. However, this issue is still not very well addressed to date. In this paper, a double chain model is adopted to model cut tobacco strips in a fluidised bed riser. The spring constants of this chain model are calibrated, and the model is validated against experimental datum. Finally, the particle RTD as a function of different process parameters is investigated.

In this paper, we propose a multiple-input single-output ghost imaging scheme, named MISO-GI. In the scheme, K spatiotemporal speckle pattern sources ( multiple input ) simultaneously generate K different spatiotemporal modulated speckle patterns which then are illuminated on an unknown object at the same time. Then, a non-spatial-resolution bucket detector ( single output ) is used to detect the light field interacting with the object. According to the orthogonality of speckle patterns from different spatiotemporal speckle pattern sources, the detection signal is separated into K components corresponding to K spatiotemporal modulated speckle patterns. With the effective recovery algorithm, an image is reconstructed by using all spatiotemporal modulated speckle patterns and their corresponding components of detection signals. Both experimental and simulation results verify the feasibility of the proposed MISO-GI scheme. Moreover, the results also show that the proposed MISO-GI scheme could reduce the total sampling time by K times and improve the imaging quality comparing to traditional GI, without the decrease of the number of speckle patterns and the picture time as well as the consumption of other light field dimensions. It provides a promising avenue to realize GI with limited sampling time and has potential for more applications.

With the widespread use of antibiotics, the number of complex infection cases caused by unknown pathogens is increasing and novel antibiotics with tunable antibacterial spectra and low toxicity are highly desirable. Herein, we report that, by selecting thiol or amine, two groups with different binding affinities with gold, as anchoring groups, phenylboronic acid can be decorated on gold nanoparticles (AuNPs) with different densities, which contributes to Gram-selective antibacterial activities of the AuNPs. The AuNPs modified with amine- or thiol-tethered phenylboronic acids specifically bind to lipopolysaccharide (LPS, Gram-negative) or lipoteichoic acid (LTA, Gram-positive), respectively. By modifying AuNPs with different ratios of thiol- and amine-tethered phenylboronic acids, the resulting AuNPs show potent and tunable antibacterial activity. The AuNP-based antibacterial agents with optional Gram selectivity are promising for applications in personalized therapy.

The high surface energy of nanomaterials endows them a metastable nature, which greatly limits their application. However, in some cases, the degradation process derived from the poor stability of nanomaterials offers an unconventional approach to design and obtain functional nanomaterials. Herein, based on the poor stability of ZnSe-[DETA]0.5 hybrid nanobelts, we developed a new strategy to chemically graphitize and functionalize graphene oxide (GO). When ZnSe[DETA]0.5 hybrid nanobelts encountered a strong acid, they were attacked by H+ cations and could release highly reactive Se2− anions into the reaction solution. Like other common reductants (such as N2H4·H2O), these Se2− anions exhibited an excellent ability to restore the structure of GO. The structural restoration of GO was greatly affected by the reaction time, the volume of HCl, and the mass ratio between GO and ZnSe[DETA]0.5 nanobelts. By carefully controlling the reaction process and the post-processing process, we finally obtained several Se-based reduced GO (RGO) nanocomposites (such as ZnSe/Se-RGO, ZnSe-RGO, and Se-RGO) and various selenide/metal-RGO nanocomposites (such as Ag2Se-RGO, Cu2Se-RGO, and Pt-RGO). Although the original structure and composition of ZnSe[DETA]0.5 nanobelts are destroyed, the procedure presents an unconventional way to chemically graphitize and functionalize GO and thus provides a new material synthesis platform for nanocomposites.

This study was designed to isolate microalgal species which can tolerate severe environmental stresses and can be used for wastewater treatment and biofuel generation. Three different microalgal strains (including Chlorella sorokiniana GEEL-01, Parachlorella kessleri GEEL-02, and Parachlorella kessleri GEEL-03) were isolated from a wastewater treatment plant and Waterwheel Park. The highest growth rate (1.61 OD680nm) was observed for C. sorokiniana GEEL-01 with highest removal of total nitrogen (1.5 mg L−1 day−1) and total phosphorus (1.82 mg L−1 day−1). The biocomponents of the isolated species ranged from 19.47–29.64%, 39.39–52.51%, and 15.08–22.75% for carbohydrate, protein, and lipid, respectively, based on the dry cell weight (DCW). The function groups in microalgal biocompounds were also confirmed by Fourier-transform infrared radiation (FT-IR) spectra, indicated their ability for biofuel generation. Ultimate and proximate analyses of C. sorokiniana GEEL-01 showed high carbon (54.24% DCW) and volatile content (92.69% DCW), compare to other strains. Moreover, it exhibited a significant accumulation of lipid with an increase in the fractions of saturated fatty acids (64.5%), and the major fatty acids were palmitic acid (11.17%), stearic acid (33.86%), oleic acid (9.84%), and linoleic acid (11.56%). Biodiesel derived from the major fatty acids had optimum engine efficiency properties including iodine value (77.34 g I2/100 g oil) and cetane number (54.83). Cultivation of C. sorokiniana GEEL-01 can serve as a dual function of biodiesel feedstock generation and nutrients removal.

Hematite (Fe2O3) is a well-known oxide semiconductor suitable for photoelectrochemical (PEC) water splitting and industry gas sensing. It is widely known that Sn doping of Fe2O3 can enhance the device performance, yet the underlying mechanism remains elusive. In this work, we determine the relationship between electronic structure, optical properties, and PEC activity of Sn-doped Fe2O3 by studying highly crystalline, well-controlled thin films prepared by pulsed laser deposition (PLD). We show that Sn doping substantially increases the n-type conductivity of Fe2O3, and the conduction mechanism is better described by a small-polaron hopping (SPH) model. Only 0.2% Sn doping significantly reduces the activation energy barrier for SPH conduction from at least 0.5 eV for undoped Fe2O3 to 0.14 eV for doped ones. A combination of X-ray photoemission, X-ray absorption spectroscopy, and DFT calculations reveals that the Fermi level gradually shifts toward the conduction band minimum with Sn doping. A localized Fe2+-like gap state is observed at the top of the valence band, accounting for the SPH conduction. Interestingly, different from the literature, only 0.2% Sn doping in Fe2O3 significantly improves the PEC activity, while more Sn decreases it. The improved PEC activity is partially attributed to an increased band bending potential which facilitates the charge separation at the space charge region. The reduced activation energy barrier for SPH will facilitate the transport of photoexcited carriers for the enhanced PEC, which is of interest for further carrier dynamics study.

Objective This study was aimed to identify prognostic factors in glioma by analysis of the gene expression and DNA methylation data. MethodsThe RNAseq and DNA methylation data associated with glioma were downloaded from GEO and TCGA databases to analyze the differentially expressed genes (DEGs) and methylated genes between tumor and normal tissues. Function and pathway analyses, co-expression network and survival analysis were performed based on these DEGs. The intersection genes of DEGs and differentially methylated genes were obtained followed by function analysis. Results Total 2190 DEGs were identified between tumor and normal tissues, which were significantly enriched in neuron differentiation associated functions, as well as ribosome pathway. There were 6186 methylation sites (2834 up-regulated and 3352 down-regulated) with significant differences in tumor vs. normal. In the constructed co-expression network, DPP6, MAPK10 and RPL3 were hub genes. Survival analysis of 20 DEGs obtained 18 prognostic genes, among which 9 were differentially methylated, such as LHFPL tetraspan subfamily member 3 (LHFPL3), cadherin 20 (CDH20), complexin 2 (CPLX2), and tenascin R (TNR). The intersection of DEGs and differentially methylated genes (632 genes) were significantly enriched in functions of neuron differentiation. Conclusion DPP6, MAPK10 and RPL3 may play important roles in tumorigenesis of glioma. Additionally, methylation of LHFPL3, CDH20, CPLX2, and TNR may serve as prognostic factors of glioma.

Vacancy-ordered double perovskites, having a great application in optoelectronic and thermoelectric devices, are variants of metal-halide perovskites. The PBE and HSE06 functionals for the first-pr...