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Fake detection has become an urgent task. Generative adversarial networks (GANs) extended to deep learning has shown its extraordinary ability in the fields of image, audio, and speech. But advanced technology benefits us, it also poses a threat to us when used in Cyber Crime. The Deepfake (common name for face manipulation methods) based on GANs can realize the replacement of different faces. Due to the development of GANs, faces generated by Deepfake can already be visually real. Deepfake can purposely replace any face to a different person, so that a fabricated event may be widely spread because of the convenience of the Internet, causing serious impacts such as personal attacks and cyber crime. Based on cutting-edge research , this paper proposes a intelligence forensic method of Deepfake detection. We first discover the subtle texture differences between real and fake image in image saliency, which shows difference in the texture of faces. To amplify this difference, we exploit guided filter with saliency map as guide map to enhance the texture artifacts caused by the post-processing and display the potential features of forgery. Resnet18 classification network efficiently learns the exposed difference and finally realizes the real and fake detection of face images. We evaluate the performance of the method and experiments verify that the proposed method can achieve the state-of-the-art detection accuracy .

Microbial electrosynthesis is a biocathode-driven device for chemicals production from carbon dioxide reduction and has been a promising carbon-consuming technology to alleviate the greenhouse effect and acquire the renewable energy. However, previous studies primarily focused on the effect of the operating parameters on the biocathode with an indirect electron transfer (IDET) pathway instead of a direct electron transfer (DET) pathway for CO2 reduction. In this work, we aim to study the effect of the operating parameters, including temperature, inorganic carbon source, and initial pH value, on the biocathode with a DET pathway for CO2 reduction to CH4. The CH4-producing biocathodes showed the respective optimum performance at the condition of 35 °C temperature, 4 g L−1 bicarbonate concentration, and pH 7.5 catholyte. This work provides an important guidance for the operation and development of microbial electrosynthesis for CO2 reduction to chemicals.

The rapid popularization of cloud computing and ultra-high-speed Internet has promoted the vigorous development of data sharing and collaborative office, especially in Big Data and AI. Aiming at protecting the security of users’ data, researchers developed PDP scheme to verify data. However, existing schemes all rely on semi-trusted Third Party Auditor (TPA) or group management to store verification information. In order to solve this problem, we propose a distributed data integrity audit scheme based on blockchain. This scheme provides a brand-new method, which allows customers to store data safely without relying on any specific TPA and protect users’ privacy at a lower cost. For the new concept, this paper points out the problems of the existing scheme and puts forward system model and security model. Then, a decentralized data integrity audit scheme using blockchain is designed. The proposed private PDP scheme based on blockchain is provably secure. At the same time, the security analysis and efficiency analysis show that the proposed PDP scheme is safe, efficient and practical.

Since toxic gas leakage may cause ecological environmental problems and even life-threatening damage, effective monitoring of toxic gas is of great importance and subject to increasing demand. However, complicated environmental factors, as well as various coexisting interferences can easily affect the sensitivity and selectivity of gas sensors, hindering their performance. Recent reports have successfully demonstrated the development of hierarchical nanostructures with desirable self-cleaning properties, yet gas sensors that can resist contamination have rarely been realized. Here, we developed a reentrant thorny ZnO/graphene hybrid nanowall structure that simultaneously repels liquid contamination and possesses NH3 gas sensing properties. The unique reentrant and hierarchical structure, featuring an interconnected vertical graphene nanowall framework with numerous ZnO nanospikes branched on the top nanowall, is highly repellent to liquids, even biofluids with low surface tension. The hierarchical structure consisting of gas sensing graphene and ZnO can be successfully applied as an NH3 gas sensor at room temperature, exhibiting not only excellent sensitivity, selectivity, and repeatability, but also outstanding stability even after bacterial contamination. This study provides a versatile method for fabricating reentrant and hierarchical structures with excellent liquid repellency, and offers a promising method for designing reliable gas sensors with anti-biofouling properties. A hybrid nanostructure can simultaneously repel contaminants and possess ammonia-sensing capabilities, making it an ideal pollution monitor. Gaseous pollutants such as ammonia have significant medical and environmental impacts. Hybrid structures of metal oxides and graphene have shown promising gas-sensing performance; however, their utility is hampered by the complexity of air composition and the presence of other contaminants. Xi Xie, of Sun Yat-Sen University, China, led a team of researchers to create a nanostructure of zinc oxide and graphene — both known as ammonia gas-sensitive materials — that repels liquids from its surface. The structure works by trapping “nano-air pockets” on the face of the device that prevent liquids from adhering to it, while the presence or absence of ammonia changes the conductivity of the nanostructure. The researchers’ paper shows an effective sensor for use in complicated environments.

Cloud storage is now a very popular service for many enterprises and their users. However, ensuring the integrity of the outsourced data is a very challenging problem. The concept of provable data possession is very effective for solving this problem. Based on this concept, in this paper we propose a new group-user-based privacy-preserving secure cloud auditing protocol for enterprise users and analyse its security. This protocol is also constructed on a recently proposed lightweight and privacy-preserving secure cloud auditing scheme for group users via a third-party medium. We point out that scheme is not secure and that the authenticators corresponding to the outsourced data blocks can be easily forged, that means the cloud servers can delete all the outsourced data but can still give correct proof for the possession of outsourced data, while our protocol has no such shortcoming. The performance analysis results demonstrate that our proposal is very practical and can have large-scale applications.

Mixing P2 and O3 phases in a single material is expected to take advantage of both phases. This work reports the successful synthesis of a Li-free P2/O3 biphasic cathode Na0.73Ni0.4Mn0.4Ti0.2O2 containing 33% of P2 phase by a solid-state method. According to XRD refinement, the interplanar distance along the c-axis decreases from 5.6055 A in the pure P2 material to 5.5710 A in the P2 phase of the biphasic material, while increases from 5.4502 A in the pure O3 material to 5.4855 A in the O3 phase of the biphasic material, indicating different electrostatic repulsions between transitional metal oxide layers. Compared to pure P2 or O3 phase, the biphasic cathode exhibits an initial Coulombic efficiency close to 100%, increased reversible capacity and average voltage, improved cycling stability, and rate performance in the voltage range of 1.5–4.3 V. The biphasic cathode is a promising candidate for full cell application of sodium-ion batteries.

Microbial electrosynthesis is an innovative technology capable of producing biofuels (particularly CH4) via CO2 reduction. Electron-uptaking from biocathode by microorganisms is the key step in the process of microbial electrosynthesis. However, the lack of understanding of electron transfer behaviors and their affecting factors largely limit the development of microbial electrosynthesis. Herein, we investigated the effects of initial startup cathode potentials (–0.7, –0.8, –0.9, –1.0 and –1.1 V vs. Ag/AgCl) on the electron transfer behaviors of biocathodes. The cyclic voltammetry (CV) showed typical sigmoidal catalytic currents corresponding to the CO2 reduction on the biocathodes started up at –0.7 and –0.8 V, but not on the other biocathodes. The CH4 production rate, Faradaic efficiency, scanning electron microscopy (SEM), and microbial community were also investigated. All the results indicated that the startup cathode potentials determine the electron transfer behaviors of biocathode: the biocathodes started up at –0.7 and –0.8 V mainly possessed a direct electron transfer manner, while the biocathodes started up at –0.9, –1.0 and –1.1 V mainly possessed an indirect electron transfer pathway. This study provides a guidance for the development of CH4-producing biocathodes with a desired electron transfer behavior.

The introduction of thermal relaxation makes non-Fourier heat transfer more effective than Pennes equation to reflect rapid bio-heat transferring during HIFU, however, the contribution of thermal relaxation in specific tissues needs to be further clarified. In this study, we first measured the thermal relaxation times of porcine muscle and porcine fat. Combining with experimental measurements, the effects of thermal relaxation on temperature elevation in the tissues were investigated by using Pennes equation, thermal wave model of bio-heat transfer (TWMBT) and dual phase-lag (DPL) bio-heat transfer. Results showed that: a) The thermal relaxation times of porcine muscle and porcine fat are experimentally determined as 5.71± 0.11 s and 5.02± 0.06 s, respectively. b) In the absence of cavitation, DPL bio-heat transfer is more accurate to predict the temperature elevation at the focus and 2 mm from the focus than Pennes equation and TWMBT. Particularly, comparing with the reported of bologna (16 s) used in most of the theoretical analysis, the utilization of the measured thermal relaxation time for a specific tissue in DPL bio-heat transfer is more effective in predicting the temperature elevation during HIFU. c) Acoustic cavitation and nonlinear propagation is easier to happen in fat, under which all bio-heat transfer models are failed to forecast the temperature elevation induced by HIFU. The results demonstrate that different tissues have different thermal relaxation, DPL bio-heat transfer with the measured thermal relaxation times of specific tissues can accurately predict the temperature elevation during HIFU without cavitation.

The long startup time and low current density of biocathodes limit the application of microbial electrosynthesis systems for CO2 reduction to CH4. Herein, we reported an approach to accelerate the startup and enhance the current density of CH4-producing biocathodes through reversing the polarity during the startup period. A bioanode was first developed at −0.2 V vs. SHE with acetate as electron donor, and then worked as a biocathode by reversing the potential of electrode to −0.5 V vs. SHE. The results showed that the startup time of the biocathode reversed from the bioanode (∼18 days) was shortened by approximately 40% in contrast to that (>30 days) of the control biocathode started up with a constant potential of −0.5 V vs. SHE. In addition, the maximum CH4 production was increased by 1.2 ± 0.2 times than that of the control biocathode. The results suggested that the “reversed” biocathode possessed a thicker biofilm and higher biomass content than the control biocathode. Our results showed that polarity reversal was an efficient approach for the startup and performance enhancement of CH4-producing biocathodes in microbial electrosynthesis systems.

Real-world sequential data are often generated based on complicated and latent mechanisms, which can be formulated as event sequences occurring in the continuous time domain. In addition, continuous signals may often be associated with event sequences and be formulated as time series with fixed time lags. Traditionally, event sequences are often modeled by parametric temporal point processes, which use explicitly defined conditional intensity functions to quantify the occurrence rates of events. However, these parametric models often merely take one-side information from event sequences into account while ignoring the information from concurrent time series, and their intensity functions are usually designed for specific tasks dependent on prior knowledge. To tackle the above-mentioned problems, we propose a model called recurrent point process networks which instantiates temporal point process models with temporal recurrent neural networks (RNNs). In particular, the intensity functions of the proposed model are modeled by two RNNs: one temporal RNN capturing the relationships among events and the other RNN updating intensity functions based on time series. Furthermore, an attention mechanism is introduced, which uncovers influence strengths among events with good interpretability. Focusing on challenging tasks such as temporal event prediction and underlying relational network mining, we demonstrate the superiority of our model on both synthetic and real-world data.

Detection of H2O2 in bio-fluids plays an important role in early-diagnosis of many diseases, and thus the development of electrochemical H2O2 sensors has been explored. However, constructing robust sensors that could self-clean and avoid biofouling is still challenging, because the complex compositions of bio-fluids could easily absorb to or even passivate the sensor electrode. In this work, we reported the development of H2O2 electrochemical sensor based on hierarchical vertical graphene/nanorods structure (vG/NRs) with self-cleaning and anti-biofouling properties. The hierarchical vG/NRs structure consisted of ZnO nanorods branched on vertical graphene nanowalls, which were fabricated through multiple steps of plasma enhanced chemical vapor deposition, atomic layer deposition and hydrothermal growth. The hierarchical vG/NRs after fluorination (vG/NRs-F) displayed excellent liquid repellence and anti-platelet adhesion properties. The vG/NRs-F was utilized as working electrodes and integrated as electrochemical sensors. H2O2 molecules in solution could access to the vG/NRs surface, inducing electrochemical signals for detection with reasonable sensitivity and selectivity. Meanwhile, the vG/NRs-F electrode could resist the contamination of biocomponents in blood serum after sensing experiment, enabling stable sensing of H2O2 without interfering by biofouling. Our work offers a promising strategy to design self-cleaning and anti-biofouling sensors with extended applicability for detection in complex biological fluids.

With the increase of the renewable energy sources connected to the power system, the fluctuation and uncertainty of the output of the renewable energy generator has significant effects on power system security and stability operation. The synchronicity of power generation characteristics and load demands are different, which leads to frequency regulation pressure of power system further prominent. The battery energy storage system has good frequency regulation ability and can quickly respond to system frequency change. In this paper, in the case of the energy storage required to be configured in new wind farms, the virtual inertia control, and droop control strategies of energy storage participating in frequency regulation are proposed. Then, the comprehensive control strategy is put forward, considering the frequency regulation ability of the wind turbines and energy storage system. Finally, the effectiveness of the proposed control strategy is verified by using the IEEE 30-bus system.

Cooperative cognitive radio network is a new method to alleviate the spectrum scarcity problem. Proactive content caching and UAV relaying techniques are deployed in a CRN, to enable the achievable rates for primary and secondary systems. Even though these two emerging technologies are grateful to solve the problem of spectrum scarcity, there are still open issues to influence the system performance and the utilization of spectrum. In this article, we provide an overview of the cooperation technique, including their theoretical schemes and the advanced performance in radio networks. Then, this article proposes a cache-enabled UAV cooperation scheme in CRN, which enhances the CRN's transmission capability and reduces the redundant traffic load of CRN. The experimental results show that the cache-enabled UAV scheme significantly improves the achievable rates for both systems in CCRN. In addition, we present future work related to content caching, deployment of UAVs and CCRN to support radio networks.

Against the background of global climate change and anthropogenic stresses, extreme climate events (ECEs) are projected to increase in both frequency and intensity. Precipitation is one of the main climate parameters for ECE analysis. However, accurate precipitation information for extreme climate events research from dense rain gauges is still difficult to obtain in mountainous or economically disadvantaged regions. Satellite precipitation products (SPPs) with high spatial and temporal resolution offer opportunities to monitor ECE intensities and trends on large spatial scales. In this study, the accuracies of seven SPPs on multiple spatiotemporal scales in the Yangtze River Basin (YRB) during the period of 2003&ndash, 2017 are evaluated, along with their ability to capture ECE characteristics. The seven products are the Tropical Rainfall Measuring Mission, Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS) (25), CHIRPS (05), Climate Prediction Center Morphing (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN)-Climate Data Record, PERSIANN-Cloud Classification System, and Global Precipitation Measurement (GPM) IMERG. Rain gauge precipitation data provided by the China Meteorological Administration are adopted as reference data. Various statistical evaluation metrics and different ECE indexes are used to evaluate and compare the performances of the selected products. The results show that CMORPH has the best agreement with the reference data on the daily and annual scales, but GPM IMERG performs relatively well on the monthly scale. With regard to ECE monitoring in the YRB, in general, GPM IMERG and CMORPH provide higher precision. As regards the spatial heterogeneity of the SPP performance in the YRB, most of the examined SPPs have poor accuracy in the mountainous areas of the upper reach. Only CMORPH and GPM IMERG exhibit superior performance, this is because they feature an improved inversion precipitation algorithm for mountainous areas. Furthermore, most SPPs have poor ability to capture extreme precipitation in the estuaries of the lower reach and to monitor drought in the mountainous areas of the upper reach. This study can provide a reference for SPP selection for ECE analysis.

Solar-driven electrochemical CO2 reduction to fuels has considerable potential to satisfy future renewable energy needs and mitigate CO2 emissions, but current approaches face significant challenges, such as poor selectivity and large overpotential for the catalytic reactions. Here we present a hybrid microbial-photoelectrochemical system that selectively converts CO2 into methane in a single step without any by-products. The hybrid system employs a biocathode that was capable of reducing CO2 into CH4 with an unprecedentedly low overpotential (

Microbial biochemicals have been indicated as the primary stimulators of innate immunity, the first line of the body’s defence against infections. However, the influence of topological features on a microbe’s surface on immune responses remains largely unknown. Here we demonstrate the ability of TiO2 microparticles decorated with nanospikes (spiky particles) to activate and amplify the immune response in vitro and in vivo. The nanospikes exert mechanical stress on the cells, which results in potassium efflux and inflammasome activation in macrophages and dendritic cells during phagocytosis. The spiky particles augment antigen-specific humoral and cellular immune responses in the presence of monophosphoryl lipid A and elicit protective immunity against tumour growth and influenza viral infection. The study offers insights into how surface physical cues can tune the activation of innate immunity and provides a basis for engineering particles with increased immunogenicity and adjuvanticity.

Due to the rapidly growing volume of publications, it is an urgent task to evaluate the potential impact of emerging works and identify valuable publications for the benefit of researchers with limited time. The impact of authors is significant in terms of personal promotion and fund raising. However, the criterion used to evaluate the impact of authors is largely based on credits they have received, not potential credits. We take the citation count, the most direct and widely used metric for publication popularity, as the potential impact and evaluate its predictability. To this end, we propose a neural network-based point process model for predicting the citation count of individual publications. Our approach integrates signals from paper-specific features and their citation traces, which reflect the trend of either losing or gaining popularity. The model is learned in an adversarial way, which mitigates the bias-exposure efficiently. We verify our model on the largest publicly available academic publication repository, and our model outperforms alternatives with a notable margin.

Nanowire thin films exhibiting superhydrophobicity or even superomniphobicity can protect themselves from liquid contamination. However, high contact angle of these thin films with liquid droplets limits the interfacial area between liquids and nanowire network, which is unfavorable for applications such as sensing suspended liquid droplets. In this study, slippery surface based on lubricant infused hierarchical Si nanowire film was developed, which provided low contact angle with liquid droplet, while possessing liquid repellent properties upon slight tilting. Si nanowire films were fabricated through chemical vapor deposition and were further branched with ZnO nanospikes for enhanced immobilization of lubricant. These hierarchical nanowire films were functionalized to enhance their superhydrophobicity and were further infused with perfluorinated lubricant to produce slippery surface. These infused slippery surfaces exhibited low contact angles with blood and corn oil along with high repellency towards these liquids. This study offers a promising approach for creating nanowire films that avoid liquid contamination.

With the development and application of blockchain technology, more and more fields are beginning to use blockchains for industrial innovation, In recent years. At the same time, the data integrity verification techniques based on blockchain have also attracted wide attention of researchers. However, the state-of-the-art schemes are only using the structure of the blockchain on centralized server which cannot leverage the characteristics of the blockchain and resist malicious modification attacks. In addition, the centralized blockchain structure introduces additional storage and computing costs. In this paper, we propose a decentralized verifiable outsourcing framework based on blockchain networks, in which no administrators are required to be in charge of auditing and recording data changes.

With the progress of society and the improvement of people’s democratic consciousness, voting, as a channel to fully develop democracy, is playing an increasingly important part in many application scenarios. In the era of Internet, electronic voting has replaced the traditional paper voting with the advantages of low cost, high efficiency and few mistakes. The fact that the data of electronic voting system is stored in the central database gives rise to the following problems: the voting data is not open and transparent enough, and it is easy to be tampered with and forged; the users’ private information faces the risk of being leaked; voters can not verify the voting results. Fortunately blockchain technology can make up for the shortcomings of the current voting system, making the voting process open and transparent, preventing fraudulent votes, enhancing the security of voting data and verifying the voting results. The application of blockchain electronic voting system has very important significance and prospects. In this paper, we first introduce the development process of electronic voting system at home and abroad, then introduce the development status of blockchain-based electronic voting system, finally we compare and summarize several typical blockchain-based electronic voting schemes.

With the rapid development of cloud computing, an increasing number of organizations and individuals store and share their data on untrusted clouds. Therefore, shared data auditing has become an important issue in the field of cloud storage, attracting the attention of researchers. However, the state-of-the-art schemes can not fully meet the performance and security requirements. Therefore, in this paper we propose a public audit shared data protocol for cloud storage by using blockchain and Rank-based Merkle AVL tree (RB-MHT) to achieve privacy preserving and batch auditing to reduce system overhead as well as keeping the security of modification record in this blockchain-based scheme. For privacy-perserving, the auditing signature is only related to group management during the audit process and data will be blind by a random value. Furthermore, we prove the security of our scheme and evaluate the performance of it through implementation. The results demonstrate that the proposed scheme is provably secure and efficient.

Blockchain voting can bring many practical benefits. It is said that blockchain technology represents a revolution in security and transparency that makes electronic voting possible. It will undoubtedly have an unexpected and far-reaching impact on future democracy. Electronic voting can accelerate, simplify and reduce the cost of elections, and even lead to more participation and development into stronger democracies. Firstly, this paper analyses the problems existing in the current blockchain voting system, then introduces the concept and principle of Conflux consensus mechanism. Based on blockchain technology and ring signature, a large-scale voting electronic voting scheme integrating the advantages of Conflux consensus mechanism with blockchain voting system is proposed, which is decentralized, self-managed, non-interactive and free of charge.

Solar-driven carbon-based fuels production is a promising way to store solar energy and alleviate the greenhouse effect. However, current approaches face a lot of challenges, such as poor selectivity, high overpotential, and the requirement of external electrical bias. In this study, based on the photoelectrochemical and bioelectrochemical technologies, we reported a novel self-biased hybrid solar-microbial device, which was capable of converting solar energy into methane without external electrical bias. Owing to the self-generated bias (~0.47 V) from the bioanode and the low overpotential (

Artificial photosynthesis is a promising technology to convert CO2 to fuels using solar energy, but it faces significant challenges, such as low Faradaic efficiency, poor selectivity, and the requirement of external electrical energy input. Here, we coupled a TiO2/CdS composite photoanode with a CH4-producing biocathode to construct a visible-light responsive hybrid microbial photoelectrochemical system for CO2-to-CH4 conversion. Owing to the low onset potential of the TiO2/CdS photoanode and the high selectivity and low overpotential of the biocathode, we successfully demonstrated efficient methane production with a high Faradaic efficiency up to 94.4% without any external electrical bias. The visible-light responsive hybrid system yielded a high solar-to-fuel conversion efficiency (SCE) up to 1.28%, which is around 6 times of that of global natural photosynthesis. The successful demonstration of such a visible-light responsive hybrid system provides new opportunities for artificial photosynthesis to produce solar fuels.

Mutation of p53 tumor suppressor gene represents one of the early molecular events in tumor initiation and progression. Although molecular computing holds tremendous potential with important applications in diagnosis, prognosis and treatment of human diseases at the molecular level, designing molecular logic gates to implement cascade amplification via operating autonomously for the detection of point mutations still remains challenging. In this contribution, we developed a three concatenated logic gates (TCLG) to perform multiple strand displacement amplification (m-SDA) for screening the cancer-related point mutations only via designing an innovative molecular beacon (MB). Specifically, using p53 gene as model target, extending the two ends of a MB via adding two fragments with the same sequence achieves two unique terminal single-stranded (ss) overhangs. After self-folding of MB into hairpin structure, the two overhangs exhibit a near inverted mirror image (IM) relationship if taking the base nature and direction into account. For this, the probe is called IM-MB. Because cascade SDAs can occur on IM-MB and promote each other, the target gene can be detected down to 10 pM. Along this line, the TCLG circuit was proposed, and two primers and target gene serve as the indispensable input signals. Utilizing this logic circuit, the point mutation or absence of target gene can be sensitively screened. Moreover, its potential application in the recognition of point mutations in complex biomatrix has been demonstrated via blind test. The proof-of-concept scheme is expected to provide new insight into the development of DNA-based molecular logic gates and their applications in basic research, medical diagnosis and precise treatment and treatment of genetic diseases.

Bioelectrochemical systems, including microbial fuel cells (MFCs), microbial electrolysis cells (MECs), and microbial electrosynthesis cells, are promising technologies for dealing with water pollution and the energy crisis. In these systems, electrochemically active bacteria attached on electrodes can degrade organic matter in wastewater while producing electricity, gas fuels, and other value-added chemicals. In this chapter, we review the current progress of MECs and microbial electrosynthesis cells, which are used to produce hydrogen and value-added chemicals (such as acetate, hydrogen peroxide, ethanol, and formic acid). However, the production of liquid value-added chemicals is still in its infancy, and there are many challenges to its application, such as low production rates, high internal resistance, and expensive electrode materials. Compared with liquid fuels, gaseous biofuels (e.g., hydrogen and methane) are much easier to separate and need less energy for further purification. Therefore, we mainly focus on H2 production from MECs and methane production from microbial electrosynthesis cells. This chapter reviews recent development of new electrode materials, configurations, electron transfer manners, microbial ecosystems, and applications for the two devices to promote a general understanding and identify future research directions for bioelectrochemical systems.

Extraordinary water-repelling properties of superhydrophobic surfaces make them novel candidates for a great variety of potential applications. A general approach to achieve superhydrophobicity requires low-energy coating on the surface and roughness on nano- and micrometre scale. However, typical construction of superhydrophobic surfaces with micro-nano structure through top-down fabrication is restricted by sophisticated fabrication techniques and limited choices of substrate materials. Micro-nanoscale topographies templated by conventional microparticles through surface coating may produce large variations in roughness and uncontrollable defects, resulting in poorly controlled surface morphology and wettability. In this work, micro-nanoscale hierarchical nanowire network was fabricated to construct self-cleaning coating using one-dimensional TiO 2 nanowires as microscale templates. Hierarchical structure with homogeneous morphology was achieved by branching ZnO nanowires on the TiO 2 nanowire backbones through hydrothermal reaction. The hierarchical nanowire network displayed homogeneous micro/nano-topography, in contrast to hierarchical structure templated by traditional microparticles. This hierarchical nanowire network film exhibited high repellency to both water and cell culture medium after functionalization with fluorinated organic molecules. The hierarchical structure templated by TiO 2 nanowire coating significantly increased the surface superhydrophobicity compared to vertical ZnO nanowires with nanotopography alone. Our results demonstrated a promising strategy of using nanowires as microscale templates for the rational design of hierarchical coatings with desired superhydrophobicity that can also be applied to various substrate materials.

With the continuous and rapid development of cloud computing, it becomes more popular for users to outsource large-scale data files to cloud servers for storage and computation. However, data outsourcing brings convenience to users while it also causes certain security problems. The integrity of outsourced data needs to be periodically checked by users to protect their data. Also, the secure transfer of cloud data can avoid data losses to users. Aiming at solving these problems in the data outsourcing process, a provable data transfer scheme based on provable data possession and deletion is recently proposed by Xue et al. However, we found a security flaw in Xue et al.’s scheme. Concretely, the block tags can be forged in their scheme. In this article, we first give a brief review of Xue et al.’s scheme and then a detailed attack is shown. To remove the security flaw, an improved scheme is proposed. Furthermore, we replace the integrity checking protocol of their proposal with a more efficient protocol to improve the efficiency of data integrity auditing.

With the scale of small and medium hydropower increasing gradually, it is difficult to establish a detailed model because the parameters of each generating unit can barely be obtained. To build a dynamic equivalent model of the hydropower generator group, this paper presents an estimation-based equivalent method, which will keep the dynamic responses and the transient stability consistent before and after the equivalence. A 3rd order generator and a parallel static characteristic ZIP load model are selected as the dynamic equivalent model of hydropower generator group. Based on phasor measurements in the tie line which connects to the modeled hydropower generator group, the self-adaptive control parameters modified differential evolution (SACPMDE) algorithm is used to obtain the parameters of equivalent model. The proposed method is verified in the small and medium hydropower generator group with simulation in an actual power grid of China. The results show that the proposed equivalent model has highly precision on the dynamic responses and the parameters identification method is stable. The proposed method can be used for modeling a group of small and medium hydropower generators whose structures and parameters are unknown.

Dispersion of hydrophilic particles in non-polar media has many important applications yet remains difficult. Surfactant or amphiphilic functionalization was conventionally applied to disperse particles but is highly dependent on the particle/solvent system and may induce unfavorable effects and impact particle hydrophilic nature. Recently 2 μm size polystyrene microbeads coated with ZnO nanospikes have been reported to display anomalous dispersity in phobic media without using surfactant or amphiphilic functionalization. However, due to the lack of understanding whether this phenomenon was applicable to a wider range of conditions, little application has been derived from it. Here the anomalous dispersity phenomenons of hydrophilic microparticles covered with nanospikes were systematically assessed at various conditions including different particle sizes, material compositions, particle morphologies, solvent hydrophobicities, and surface polar groups. Microparticles were functionalized with nanospikes through hydrothermal route, followed by dispersity test in hydrophobic media. The results suggest nanospikes consistently prevent particle aggregation in various particle or solvent conditions, indicating the universal applicability of the anomalous dispersion phenomenons. This work provides insight on the anomalous dispersity of hydrophilic particles in various systems and offers potential application to use this method for surfactant-free dispersions.