With the rapid development of the internet of things (IoT), traditional industries are setting off a massive wave of digitization. In the era of the Internet of Everything, millions of devices and ...links in IoT pose more significant challenges to data management. Most existing solutions employ centralized systems to control IoT devices, which brings about the privacy and security issues in IoT data management. Recently, blockchain has attracted much attention in the field of IoT due to its decentralization, traceability, and non-tamperability. However, it is non-trivial to apply the current blockchain techniques to IoT due to the lack of scalability and high resource costs. Different blockchain platforms have their particular advantages in the scenario of IoT data management. In this paper, we propose a cross-chain framework to integrate multiple blockchains for efficient and secure IoT data management. Our solution builds an interactive decentralized access model which employs a consortium blockchain as the control station. Other blockchain platforms customized for specific IoT scenarios run as the backbone of all IoT devices. It is equivalent to opening the off-chain channels on the consortium blockchain. Our model merges transactions in these channels for confirmation based on the notary mechanism. Finally, we implement a prototype of the proposed model based on hyperledge Fabric and IOTA Tangle. We evaluate the performance of our method through extensive experiments. The results demonstrate the effectiveness and efficiency of our framework.
State of health is a critical state which evaluates the degradation level of batteries. However, it cannot be measured directly but requires estimation. While accurate state of health estimation has ...progressed markedly, the time- and resource-consuming degradation experiments to generate target battery labels hinder the development of state of health estimation methods. In this article, we design a deep-learning framework to enable the estimation of battery state of health in the absence of target battery labels. This framework integrates a swarm of deep neural networks equipped with domain adaptation to produce accurate estimation. We employ 65 commercial batteries from 5 different manufacturers to generate 71,588 samples for cross-validation. The validation results indicate that the proposed framework can ensure absolute errors of less than 3% for 89.4% of samples (less than 5% for 98.9% of samples), with a maximum absolute error of less than 8.87% in the absence of target labels. This work emphasizes the power of deep learning in precluding degradation experiments and highlights the promise of rapid development of battery management algorithms for new-generation batteries using only previous experimental data.
We report a versatile strategy based on the use of multifunctional mussel-inspired polydopamine for constructing well-defined single-nanoparticle@metal–organic framework (MOF) core–shell nanohybrids. ...The capability of polydopamine to form a robust conformal coating on colloidal substrates of any composition and to direct the heterogeneous nucleation and growth of MOFs makes it possible for customized structural integration of a broad range of inorganic/organic nanoparticles and functional MOFs. Furthermore, the unique redox activity of polydopamine adds additional possibilities to tailor the functionalities of the nanohybrids by sandwiching plasmonic/catalytic metal nanostructures between the core and shell via localized reduction. The core–shell nanohybrids, with the molecular sieving effect of the MOF shell complementing the intrinsic properties of nanoparticle cores, represent a unique class of nanomaterials of considerable current interest for catalysis, sensing, and nanomedicine.
Application layer distributed denial of service (DDoS) attacks have become a severe threat to the security of web servers. These attacks evade most intrusion prevention systems by sending numerous ...benign HTTP requests. Since most of these attacks are launched abruptly and severely, a fast intrusion prevention system is desirable to detect and mitigate these attacks as soon as possible. In this paper, we propose an effective defense system, named SkyShield, which leverages the sketch data structure to quickly detect and mitigate application layer DDoS attacks. First, we propose a novel calculation of the divergence between two sketches, which alleviates the impact of network dynamics and improves the detection accuracy. Second, we utilize the abnormal sketch to facilitate the identification of malicious hosts of an ongoing attack. This improves the efficiency of SkyShield by avoiding the reverse calculation of malicious hosts. We have developed a prototype of SkyShield and carefully evaluated its effectiveness using real attack data collected from a large-scale web cluster. The experimental results show that SkyShield can quickly reduce malicious requests, while posing a limited impact on normal users.
With the rapid development of energy storage devices, aqueous battery with noncombustion properties and instinct safe features has received great attentions and Zn anode is investigated intensively ...due to its high theoretical capacity (820 mAh g−1), and low negative potential (−0.762 V vs SHE). However, the unavoidable gas evolution hinders the cyclability and the application in the commercial field. Herein, the atomic layer deposition of TiO2 coating is first demonstrated as the protection layer of metallic zinc anode. The corrosion of zinc plate is significantly suppressed, leading to less gas evolution and Zn(OH)2 byproduct formation. The reduced gas generation on the outer surface of the zinc plate will maintain the effective contact area between the electrolyte and anode and leads to an improved coulombic efficiency. In this way, the Zn anode with 100 ALD cycles TiO2 protection shows reduced overpotential (72.5 mV) at 1 mA cm−2 for Zn–Zn symmetrical battery and additionally, the protection of TiO2 extended the Zn–MnO2 battery cycling performance up to 1000 cycles with the capacity retention of 85% at current density of 3 mA cm−2. The novel design of atomic layer deposition protected metal zinc anode brings in new opportunities to the realization of the ultrasafe aqueous zinc metal batteries.
In order to address the cyclability of zinc anode, the authors report the atomic layer deposition of TiO2 coating as the protection layer of metallic zinc anode for aqueous zinc ion batteries. By protecting zinc plate with the ultrathin TiO2 layer, the corrosion of zinc plate is significantly suppressed, leading to less gas evolution and Zn(OH)2 byproduct formation, thus, increasing the cyclability and coulombic efficiency.
An accurate noise power spectral density (PSD) tracker is an indispensable component of a single-channel speech enhancement system. Bayesian-motivated minimum mean-square error (MMSE)-based noise PSD ...estimators have been the most prominent in recent time. However, they lack the ability to track highly non-stationary noise sources due to current methods of a priori signal-to-noise (SNR) estimation. This is caused by the underlying assumption that the noise signal changes at a slower rate than the speech signal. As a result, MMSE-based noise PSD trackers exhibit a large tracking delay and produce noise PSD estimates that require bias compensation. Motivated by this, we propose an MMSE-based noise PSD tracker that employs a temporal convolutional network (TCN) a priori SNR estimator. The proposed noise PSD tracker, called DeepMMSE makes no assumptions about the characteristics of the noise or the speech, exhibits no tracking delay, and produces an accurate estimate that requires no bias correction. Our extensive experimental investigation shows that the proposed DeepMMSE method outperforms state-of-the-art noise PSD trackers and demonstrates the ability to track abrupt changes in the noise level. Furthermore, when employed in a speech enhancement framework, the proposed DeepMMSE method is able to outperform state-of-the-art noise PSD trackers, as well as multiple deep learning approaches to speech enhancement. Availability: DeepMMSE is available at: https://github.com/anicolson/DeepXi.
A series of poly(pentadecafluorooctyl methacrylate)-block-polyhydroxystyrene (PPDFMA-b-PHS) block copolymers (BCPs) were synthesized via reversible addition–fragmentation chain-transfer ...polymerization and subsequent deprotection. Because of the high incompatibility between hydroxyl groups and fluoro groups, the interaction parameter (χ) of these BCPs, determined by temperature-resolved small-angle X-ray scattering (SAXS), was extremely high. The χ value of PPDFMA-b-PHS was 0.48 at 150 °C, 16× larger than the χ of polystyrene-block-poly(methyl methacrylate). The microphase behavior of PPDFMA-b-PHS with various volume fractions of PHS block was determined by SAXS, yielding ordered lamellar morphologies with different sizes of domain spacing (d), and further confirmed by transmission electron microscopy. The minimum d obtained was 9.8 nm annealed at a mild temperature for a short time (80 °C for 1 min) by SAXS analysis, indicating the width of each lamellar domains was <5 nm.
We report a new strategy to synthesize core–shell metal nanoparticles with an interior, Raman tag-encoded nanogap by taking advantage of nanoparticle-templated self-assembly of amphiphilic block ...copolymers and localized metal precursor reduction by redox-active polymer brushes. Of particular interest for surface-enhanced Raman scattering (SERS) is that the nanogap size can be tailored flexibly, with the sub-2 nm nanogap leading to the highest SERS enhancement. Our results have further demonstrated that surface functionalization of the nanogapped Au nanoparticles with aptamer targeting ligands allows for specific recognition and ultrasensitive detection of cancer cells. The general applicability of this new synthetic strategy, coupled with recent advances in controlled wet-chemical synthesis of functional nanocrystals, opens new avenues to multifunctional core–shell nanoparticles with integrated optical, electronic, and magnetic properties.
•NiFe layered double hydroxide (LDH) is synthesized by flash nano-precipitation method.•La-doped NiFe LDH is prepared via a mechanical strategy.•La-NiFe LDH exhibited boosting water splitting with ...high HER and OER activity.
Electrolysis of water can directly produce hydrogen and oxygen, providing the possibility to expand the production of high purity hydrogen. It consists of two half reactions: anodic oxygen evolution reaction (OER) and cathodic hydrogen evolution reaction (HER). Developing electrocatalysts is an effective way to improve the efficiency of water splitting. Two-dimensional layered double hydroxides (LDHs), as abundant, cheap and bifunctional catalysts, have the similar electrocatalytic performance as precious metals, thereby receiving pretty much attention. Here, a facile flash nano-precipitation (FNP) synthetic strategy is presented to acquire NiFe LDH. Based on it, La-NiFe LDH is obtained by adding rare earth element lanthanum (La) with different contents using mechanical method. Owing to the synergistic effect between La and laminate metal, La-NiFe LDH shows an excellent water splitting performance, where the overpotential of OER activity is 340 mV and HER performance is 57 mV at the current density of 10 mA∙cm−2. Combined with characterization, performance and theoretical calculation, it is confirmed that the electronic structure of LDH laminates can be adjusted by La doping, reducing the Gibbs free energy in the reaction accordingly, which is beneficial to the water splitting reaction. In general, an easy-to-implement and rapid preparation method provides a convenient and green way to obtain water splitting catalyst with enhanced performance.
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Recyclable nanocatalysts of core–shell bimetallic nanocrystals are developed through polydopamine coating‐directed one‐step seeded growth, interfacial assembly, and substrate‐immobilization of Au@Ag ...core–shell nanocrystals. This strategy provides new opportunities to design and optimize heterogeneous nanocatalysts with tailored size, morphology, chemical configuration, and supporting substrates for metal‐catalyzed reactions.
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