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Solar thermochemical hydrogen production with energy level upgraded from solar thermal to chemical energy shows great potential. By integrating mid-and-low temperature solar thermochemistry and solid oxide fuel cells, in this paper, a new distributed energy system combining power, cooling, and heating is proposed and analyzed from thermodynamic, energy and exergy viewpoints. Different from the high temperature solar thermochemistry (above 1073.15 K), the mid-and-low temperature solar thermochemistry utilizes concentrated solar thermal (473.15–573.15 K) to drive methanol decomposition reaction, reducing irreversible heat collection loss. The produced hydrogen-rich fuel is converted into power through solid oxide fuel cells and micro gas turbines successively, realizing the cascaded utilization of fuel and solar energy. Numerical simulation is conducted to investigate the system thermodynamic performances under design and off-design conditions. Promising results reveal that solar-to-hydrogen and net solar-to-electricity efficiencies reach 66.26% and 40.93%, respectively. With the solar thermochemical conversion and hydrogen-rich fuel cascade utilization, the system exergy and overall energy efficiencies reach 59.76% and 80.74%, respectively. This research may provide a pathway for efficient hydrogen-rich fuel production and power generation.

The controllable preparation and rational utilization of carbon species produced in flame process is a meaningful research direction. Herein, a CQDs/TiO2 C heterostructure coupling with multi-carbon species was developed in flame process. In the millisecond-level reaction process, part of the residual carbon formed by the incomplete combustion of ethanol penetrates the lattice of TiO2, forming interstitial C (Ci) and substituent C (Cs), and the remaining amorphous carbon quantum dots (CQDs) are adsorbed on the surface of TiO2. In-situ temperature-programmed X-ray photoelectron spectroscopy (In-situ TPXPS) combined with various characterizations proved that the CQDs/TiO2 C heterostructure was successfully constructed in the flame process (the atomic ratio of the two C species was close to 1:1). The carbon species lead to the reduction of the band gap of the targeted material from 2.8 eV to 2.73 eV, meanwhile, the reduction ability is increased by 21.3%. The synergistic effect enhances the separation efficiency of photogenerated electrons by 7 times, achieving a conversion efficiency of 46.21 µmol g−1 h−1 and nearly 100% CO2-to-CO selectivity. Furthermore, the systematic theoretical calculation results visualize this kind of novel electron transfer channel from C to O to CQDs (C O-CQDs).

In order to predict the demand for airport charging facilities/piles, a demand prediction model was proposed for airports, which includes airside and landside of airports. The airside prediction model was calculated according to air traffic volume and vehicle pile ratio. The landside prediction model was calculated according to the electric vehicle flow and charging probability. Results showed that the number of charging piles in China mainland airports would reach 536000, including 26000 charging piles on the airside and 510000 on the landside in 2035. The relevant policy suggestions from the aspects of investment, operation management, and technical standards were put forward and the “new infrastructure” technology was suggested to be applied in airport’s intelligent charging facility network building.

Water pollution has changed the physical and mechanical properties of Xiashu loess, which has become an important factor in the frequent occurrence of Xiashu loess landslides. In order to understand the mechanism of Xiashu loess landslide in acid or alkali environment, a large number of Xiashu loess samples were collected in Nanjing City, Jiangsu Province. X-ray diffraction, energy-dispersive analysis of X-ray, compression test, direct shear test, and scanning electron microscope test (SEM) were used to analyze physical properties, mechanical properties, and microstructure of acid–alkali-contaminated Xiashu loess. The results show that the newly formed insoluble (slightly soluble) substances in the alkalization Xiashu loess increase its density and decrease the void ratio and water content. In sulfuric acid solution, the minerals in Xiashu loess mainly suffer dissolution reactions, which leads to decrease in soil density and increase in void ratio and water content. In the SEM image, the surface of acidified Xiashu loess soil particles is rough and uneven, while the surface of alkalized Xiashu loess soil particles is smooth and flat. This is an important reason that the internal friction angle of acidified Xiashu loess is significantly higher than that of alkalized Xiashu loess.

Based on two considerations of making full use of the residual heat of vanadium slag and exploring a novel green vanadium extraction process, this article employs vanadium slag with high MgO content as raw material, blowing oxygen into the molten vanadium slag and using the residual heat of the vanadium slag to carry out high-temperature roasting experiments. XRD and SEM/EDS were used to characterize the phase evolution and morphology of vanadium slag with high MgO content during oxidation. The results show that at a high temperature of 1723 K, the trivalent vanadium in vanadium slag can be partly transformed into acid-soluble pentavalent vanadium. Titanium-bearing spinel was oxidized into a large amount of strip pseudobrookite Fe2TiO5. After oxidation, vanadium existed in the form of the solid solution of magnesium pyrovanadate (Mg, Mn, Ca)2V2O7. The leaching rate of roasted vanadium slag with high MgO content is significantly higher than that of industrial vanadium slag. With the increase of oxygen blowing time from 10 to 30 minutes, the leaching rate of roasted vanadium slag with high MgO content increases from 23.19 to 53.69 pct.

In secret key generation of physical layer security technology, it is challenging to achieve high key capacity and low bit inconsistency rate. This paper investigates intelligent reflecting surface (IRS)-assisted secret key generation, which aims to maximize the secret key capacity by adjusting the placement of the IRS units. Specifically, we first analyze and deduce the key capacity expression of the IRS-assisted system from the perspective of information theory. Then we investigate how to use the channel state information (CSI) to place the IRS units effectively so as to maximize the secret key capacity. Simulation results show that our scheme could improve the quality of secret key generation significantly.

The requirement of hydrogen adsorption Gibbs free energy (ΔGH*) approximating to 0 eV limits the hydrogen evolution reaction (HER) activity of most electrocatalysts in alkaline media. The construction of interface and defects engineering is an effective strategy to obtain the optimal ΔGH*. Ni3N exhibits poor HER activity due to its undesirable ΔGH*. By cooperating with Nb2O5, the d-band center of Ni3N was reduced, improving its catalytic performance. The optimized Nb2O5–Ni3N displays an overpotential of 80 mV at 10 mA cm−2 and superior activity than the benchmark Pt/C catalyst when the current density is greater than 125 mA cm−2. Experimental and density functional theory results demonstrate that the improved catalytic activity is because the electronic interaction between Ni and Nb changes the coordination numbers of these two atoms, resulting in oxygen vacancies at the interface. Under the synergistic effect of Nb2O5 and Ni3N, the catalyst exhibits optimal ΔGH* and water adsorption energy.

Graph embedding models are widely used in knowledge graph completion (KGC) task. However, most models are based on the assumption that knowledge is completely certain, and this is inconsistent with real-world situations. Although there are multiple studies on uncertain knowledge embedding tasks, they often use knowledge confidence to learn embedding and cannot make full use the structural and uncertain information of knowledge. This paper presents a new embedding model named Structural and Uncertain Knowledge Embedding (SUKE), which comprises two components: an evaluator and a confidence generator. For unknown triples, the evaluator learns the structural and uncertain information to evaluate its rationality and obtain a candidate set. The confidence generator then determines the confidence of the candidate set to achieve KGC. To verify the effectiveness of the proposed model, confidence prediction, triple evaluation, and fact classification tasks are performed on three data sets. Experimental results show that SUKE performs better than mainstream embedding methods. The model proposed in this paper can help advance the research on the embedding of uncertain knowledge graphs.

This article investigated the saturated solubility of MgO in converter vanadium slag and its influencing factors. The experimental results of MgO dissolution equilibrium are consistent with the theoretical calculation results. The results show that in MgO saturated vanadium slag, MgO mainly exists in MgV2O4 and MgSiO3. The increase of V2O3 content or the decrease of the FeO/SiO2 ratio is beneficial to increasing the saturated solubility of MgO in the FeO-SiO2-V2O3 slag system. The saturated solubility of MgO in vanadium slag increases from 7.5 to 8.0 wt.% when the temperature increases from 1633 to 1753 K. In addition, the solubility of MgO also increases with the increase of TiO2 and Al2O3 content and decreases with the increase of MnO content.

This study deals with the irregular linear quadratic control problem governed by continuous time system with time delay. Linear quadratic (LQ) control for irregular Riccati equation with time delay remains challenging since the controller could not be solved from the equilibrium condition directly. The merit of this paper is that based on a new approach of ‘two-layer optimization’, the controller entries of irregular case with time delay are deduced from two equilibrium conditions in two different layers, which is fundamentally different from the classical regular LQ control. The authors prove that the irregular LQ with time delay is essentially different from the regular case. Specifically, the predictive controller bases on the feedback gain matrix and the state is given in the last part. The presented conclusions are completely new to our best knowledge. Examples is presented to show the effectiveness of the proposed approach.

The microstructure, mechanical properties and corrosion resistance of Zr-30%Ta and Zr-25%Ta-5%Ti alloy prepared by spark plasma sintering (SPS) technology were investigated. The experimental results showed that the Zr-Ta-Ti alloys made by the SPS processing have a low level of porosity with the relative density of 96%–98%. The analyses of XRD and TEM revealed that the Zr-30Ta alloy consists of α+β phase, and the Zr-25Ta-5Ti alloy belongs to the near β type alloy containing a small amount of α and ω phases. With the addition of Ti, the elastic modulus of the alloys was decreased from (99.5±7.2) GPa for Zr-30Ta alloy to (73.6±6.3) GPa for Zr-25Ta-5Ti alloy. Furthermore, it is shown that, in comparison to CP-Ti and Ti-6Al-4V alloy, the Zr-Ta-Ti alloy produced in this work offers an improved corrosion resistance due to the more stable ZrO2 and Ta2O5 generated in the passivation film on the surface of the alloys. This study demonstrates that Zr-Ta-Ti alloys are a promising candidate of novel metallic biomaterials.

In order to resist eavesdropper collusion attack in wireless multi-user network, the authors propose a distributed physical layer encryption (DPLE) scheme with energy-efficient design. The encryption is embedded into rateless coding at both user nodes and relay node. Meanwhile, data frame permutation is added at the relay for increasing randomness. It is noteworthy that the secret key is used as the seed of random number generator, which controls the encoding process and permutation. At receiver, the decryption is united with decoding process without any extra cost, which makes DPLE special in the field of lightweight security. There are two cases considered in security analysis for resisting collusion attack: without error and with error. Typical results are time complexity and attack success probability, respectively. Furthermore, the evaluation for algorithm implementation is investigated. The theoretic result and simulation show that the proposed scheme can combat colluding eavesdroppers by high complexity and very low attack success probability. Moreover, lower computation cost is achieved.

Electrical capacitance tomography (ECT) is a potential measurement technology for industrial process monitoring, but its applicability is generally limited by low-quality tomographic images. Boosting the performance of inverse computing imaging algorithms is the key to improving the reconstruction quality (RQ). Common regularization iteration imaging methods with analytical prior regularizers are less flexible in dealing with actual reconstruction tasks, leading to large reconstruction errors. To address the challenge, this study proposes a new imaging method, including reconstruction model and optimizer. The data-driven regularizer from a new ensemble learning model and the analytical prior regularizer with the focus on the sparsity of imaging objects are combined into a new optimization model for imaging. In the proposed ensemble learning model, the generalized low rank approximations of matrices (GLRAM) method is used to carry out the dimensionality reduction for decreasing the redundancy of the input data and improving the diversity, the extreme learning machine (ELM) serves as a base learner and the nuclear norm based matrix regression (NNMR) method is developed to aggregate the ensemble of solutions. The singular value thresholding method (SVTM) and the fast iterative shrinkage-thresholding algorithm (FISTA) are inserted into the split Bregman method (SBM) to generate a powerful optimizer for the built computational model. Its comparison to other competing methods through numerical experiments on typical imaging targets demonstrates that the developed algorithm reduces reconstruction error and achieves much more improvement in imaging quality and robustness.

Sparse code multiple access (SCMA) is one of the non-orthogonal multiple access schemes to meet the demands of massive connection and high spectral efficiency in the 5G communications. Since the sparsity of the codebook, the message passing algorithm (MPA) can be utilised for multi-user detection. However, the high computational complexity of MPA hinders the practical application of SCMA. The extended Max-Log MPA (EML-MPA) and the channel-adaptive extended Max-Log MPA (CAD-EML-MPA) help to reduce the complexity of conventional Log-MPA with trellis representation. On this basis, the authors propose a dynamic trellis based MPA (DT-MPA) in this study. DT-MPA selects symbols dynamically according to a specific threshold τ in each iteration of MPA. The impact of the threshold on the complexity and convergence behaviour is analysed. Simulation results show that the DT-MPA with variable τ which is related to bit signal-to-noise can achieve better bit error rate performance and lower complexity than EML-MPA and CAD-EML-MPA.

The paper considers the nonlinear optimal vibration control problem for systems with multiple delays, i.e. control delay, state delay, and measurement delay, under reference input. The time-delay s...

This article studies the issue of modeling and tracking control for wheeled mobile robot systems with control delay. The kinematics wheeled mobile robot (WMR) is modeled under the nonholonomic cons...

In this letter, we propose an efficient encoding scheme for 3GPP Raptor codes. When encoding numerous information blocks with the same size, conventional encoder is similar to matrix multiplication in the first stage of the encoding. The main idea of the proposed method is to utilize the potential redundancy in the multiplication. A series of ordered operation instructions, stored in a variable called ${\it\text { Index}}$ , are established to achieve the goal. To construct ${\it\text { Index}}$ , two schemes are introduced in this letter. Analysis demonstrates that the proposed schemes have less complexity than the conventional one. Furthermore, the simulation results show that both of them take less than 1/3 the encoding time of the original method.

Temporal knowledge graph (TKG) embedding has received increasing attention in the academia. However, most existing methods are extensions of traditional translation models. Due to their intrinsic limitations, it is often difficult for such methods to effectively model essential characteristics of TKG, namely three basic relation patterns including symmetry/antisymmetry, inversion, and composition. In this paper, a new 3-Dimensional Rotation Temporal Embedding (3DRTE) method is proposed. Firstly, we selectively fuse temporal and relational features of fact triples by taking advantages of self-attention mechanism in processing sequential information. Then, entities are modelled as points in three-dimensional space, and the relations are interpreted as two isoclinic rotations between entities with Quaternion. Experimental results on several public datasets show that our method obtains state-of-the-art results.

The kinetics of formic acid oxidation (FAO) on Pd(111) in 0.1 mol/L H2SO4+0.1 mol/L HCOOH with and without addition of Na2SO4 is studied using cyclic voltammetry and potential step method, which is compared with that in 0.1 mol/L HClO4. It is found that adsorbed sulfate has significant inhibition effect on FAO kinetics. After addition of 0.05 mol/L or 0.1 mol/L Na2SO4, FAO current in the negative-going scan is found to be significantly smaller than that at the same potential in the positive-going scan. We speculate that at potentials positive of the phase transition potential for the (SO4ad*)m+[(H2O)n-H3O+] or (SO4ad*)m+[Na+(H2O)n-H3O+] adlayer, the adlayer structure probably becomes denser and more stable with the increase of potential or with the addition of Na2SO4. The formation of connected adlayer network greatly enhance the stability of the adlayer, and the insertion of positive-charged H+ or Na+ into the adlayer network further reduces the electrostatic repulsion between partially charged sulfates. As a result, the destruction/desorption of compact sulfate adlayer becomes more difficult, which leaves much less free sites on the surface for FAO, and thus FAO kinetics at higher potentials and in the subsequent negative-going potential scan is significantly inhibited.

Summary Conformal prediction is a general method that converts almost any point predictor to a prediction set. The resulting set retains the good statistical properties of the original estimator under standard assumptions, and guarantees valid average coverage even when the model is mis-specified. A main challenge in applying conformal prediction in modern applications is efficient computation, as it generally requires an exhaustive search over the entire output space. In this paper we develop an exact and computationally efficient conformalization of the lasso and elastic net. The method makes use of a novel piecewise linear homotopy of the lasso solution under perturbation of a single input sample point. As a by-product, we provide a simpler and better-justified online lasso algorithm, which may be of independent interest. Our derivation also reveals an interesting accuracy-stability trade-off in conformal inference, which is analogous to the bias-variance trade-off in traditional parameter estimation. The practical performance of the new algorithm is demonstrated in both synthetic and real data examples.

Electrical capacitance tomography (ECT) is a potent image-based measurement technology for monitoring industrial processes, but low-quality images generally limit its application scope and measurement reliability. To increase the precision of reconstruction, in this study, a data-driven plug-and-play prior abstracted by a deep convolutional neural network (DCNN) and the sparseness prior of imaging objects, in form of regularizers, are jointly leveraged to generate a potent imaging model, in which the L1 norm of the mismatch error acts as a data fidelity term (DFT) to weaken the sensitivity of estimation result to noisy input data. The DCNN is embedded into the split Bregman (SB) technique to generate a powerful computing scheme for solving the built imaging model and the fast iterative shrinkage-thresholding algorithm (FISTA) is applied to solve the sub-problems efficiently. Extensive numerical results verify that the proposed imaging technique has competitive reconstruction ability and better robustness in comparison with the state-of-the-art methods. This study demonstrates the validity and efficacy of the proposed algorithm in reducing reconstruction error. Most importantly, the research outcomes verify that the data-driven plug-and-play prior and the sparseness prior can be jointly embedded into the imaging model, leading to a remarkable decline in reconstruction error.

The problem of optimal vibration control for active vehicle suspension systems with actuator delay is considered. Based on the model transformation, the quarter-car suspension system with a...

Storage in the form of chemical energy is crucial for efficient utilisation of solar energy. In recent years, solar photon-induced molecular isomerization energy storage, in which solar energy can be directly converted and stored as chemical energy through internal molecular isomerization reactions, has received increasing interest. It is a closed cycle without any CO2 emission. However, the absorption of reactants cannot cover the full spectrum of solar radiation, and only the ultraviolet and a portion of the visible spectrum of solar energy can be stored. Moreover, some absorbed photons are dissipated as heat, leading to an increase in the reaction temperature and a decrease in the solar photochemical efficiency. To address these problems, a new energy storage system which integrates the photochemical process with thermochemical process has been proposed to convert the full spectrum of solar energy into chemical energy. Concentrated sunlight enters the photochemical device. Norbornadiene derivatives present in the photochemical devices can be isomerized to the related quadricyclanes by absorbing the ultraviolet-visible light photons. Some absorbed photons are simultaneously stored in the chemical bonds of the quadricyclanes. The unabsorbed photons corresponding to the visible-infrared spectrum are transmitted to thermochemical reactors, providing heat for methanol decomposition. This portion of the solar energy is stored in the form of chemical energy of the products (H2 and CO). The heat dissipated in the photochemical process is transferred to the thermochemical reactors for methanol decomposition, resulting in a higher solar chemical efficiency. Results show that the average solar chemical efficiencies corresponding to the design condition and off-design condition are 75.38% and 49.78%, respectively. The results of comparison of the thermochemical performances verify that the proposed system is superior to both the single photochemical system and the single thermochemical system.

In this study, a multiple access scheme called low density signature isotropic orthogonal transfer algorithm (LDS-IOTA) is proposed for overloading transmissions, and an analytical model for the performance limitations of this system is developed. LDS-IOTA utilises a low density signature structure for spreading the symbols in frequency domain, and applies such technique to IOTA-based filter bank multicarrier system. The input-output mutual information of LDS-IOTA is analysed for the case of finite size modulation, and LDS-IOTA is compared with OFDM as well as LDS-OFDM over multipath fadding channels.

Human hair, flue gas and fly ash from a municipal solid waste incinerator (MSWI) in south China were collected and analyzed for polychlorinated dibenzo-p-dioxin (PCDD) and polychlorinated dibenzofuran (PCDF). The ΣPCDD/F level in hair from male workers were higher than those from residents. The Principal Component Analysis (PCA) suggested that ΣPCDD/F in flue gas is an external source of male workers' hair ΣPCDD/F. Results of daily intake of ΣPCDD/F by inhaling flue gas suggested that the inhalation exposure of ΣPCDD/F was at a slight health risk. For the male workers directly exposed to the MSWI power plant, ΣPCDD/F levels in their hair were significantly higher than those who were non-directly exposed. Moreover, a significantly positive relationship was obtained between ΣPCDD/F levels in male workers' hair and the working time. The result of correlation analysis suggested that 1,2,3,4,6,7,8-HpCDD and OCDD could be level indicator congeners to estimate ΣPCDD/F levels. In addition, 2,3,7,8-TCDD could be applied as TEQ indicator congener to characterize the hair of MSWI male workers.

Lanthanide doped upconversion nanocrystals are widely applied in biological imaging, photonics, photovoltaics and therapeutics. Highly monodispersed and uniform products with controllable optical modulation of upconversion fluorescence really matters their promising applications. Here, Er3+ doped Ba2YbF7 nanocrystals with phase transformation, controllable morphology and tunable upconversion emission color is investigated via varying the concentration of La3+. Accompanied with tetragonal Ba2YbF7 transformed to be cubic phase, nanocubes appear instead of nanorods, and a distinct upconversion color changing from yellow to green is obtained. Crystal structure management of Ba2YbF7 contributing to a suppressive back energy transfer process, which facilitates a controllable upconversion color in monodispersed nanocrystals with a uniform morphology, is demonstrated.

Cloud computing is a novel kind of information technology that users can enjoy sundry cloud services from the shared configurable computing resources. Compared with traditional local storage, cloud storage is a more economical choice because the remote data center can replace users for data management and maintenance, which can save time and money on the series of work. However, delivering data to an unknown Cloud Service Provider (CSP) makes the integrity of data become a potential vulnerability. To solve this problem, we propose a secure identity based aggregate signatures (SIBAS) as the data integrity checking scheme which resorts Trusted Execution Environment (TEE) as the auditor to check the outsourced data in the local side. SIBAS can not only check the integrity of outsourced data, but also achieve the secure key management in TEE through Shamir’s ( t , n ) threshold scheme. To prove the security, security analysis in the random oracle model under the computational Diffie–Hellman assumption shows that SIBAS can resist attacks from the adversary that chooses its messages and target identities, experimental results also show that our solution is viable and efficient in practice.

Defects in layered semiconductors cause large variation of electric and catalysis properties, and exploiting defect-involved reaction can deeply excavate unearthed characteristics with significant performances. Mo-terminated defects of MoS2 spontaneously guide the oriented growths of ultrasmall Au nanocrystals on specific sites of liquid-exfoliated (LE) nanosheets, which are experimentally and theoretically performed with programmable heterostructures. The conjugated construction of Au plasmonics and MoS2 semiconductors is manipulated with the aim of the optimal synergistic activity. Additionally, with photonic irradiation, hot electrons excited from attached plasmonic nanostructures are injected into MoS2 semiconductors, which remarkably increases the carrier density of catalyst to match the energy level of hydrogen evolution reaction (HER). Obeying the principle of proximity, localized MoS2 defect-adjacent Au plasmonics exhibit a more valid pathway, transferring hot electrons from donators to receptors of catalytic sites, in comparison to planar Au decoration. Meanwhile, Au nanostructures located at basal planes are essential for accelerated electron transport rates between catalysts and electrodes, and high stabilities in plasmonic-motivated electrocatalytic performances are guaranteed. The dual function of location-discriminated Au nanostructures accounts for superior electrocatalytic HER performances with photonic excitation, which imparts high inspiration in expanded heterostructures and integrated plasmonic techniques for catalysis and devices.

A new solar-biomass gasification polygeneration system is developed to efficiently utilize renewable energy in this work, with the production of liquid fuel methanol and electricity. In the system, the collected high-temperature concentrated solar energy with a beam-down optical configuration is used to drive biomass gasification, the cotton stalk is selected as feedstock, and the produced syngas is fed into the reactor for methanol synthesis. The un-reacted syngas and the system waste heat are efficiently utilized via the combined cycle to generate electricity. The designed biomass consumption rate and power capacities are 100 ktons/year and 32.7 MWe, respectively. The thermodynamic and economic performances of this polygeneration system are investigated, and the on-design energy efficiency and the exergy efficiency of the system reach to 51.89% and 51.23%, respectively. According to the off-design evaluation within a typical year, the annual production of methanol and electricity are 54.80 ktons and 50.85 GW·h, respectively. Compared with the reference system which consists of a typical methanol synthesis system with biomass-steam gasification and a solar tower power generation system, the annual averaged efficiency of the proposed solar-biomass polygeneration system is increased to 48.35% from 41.09% of the reference system, and the monthly averaged efficiency is varying in the range of 46.65%–49.05%. In addition, the specific biomass consumption rate is reduced by 27.33%, and the levelized cost of methanol is 361.88 $/ton with reasonable economic competitiveness. The polygeneration system achieves competitive thermodynamic and economic potential, and provides an alternative and promising way for efficiently utilizing abundant solar energy and biomass resources.

Sparse code multiple access (SCMA) is a promising air interface candidate technique for next generation mobile networks. By introducing the Tent map in the Chaos theory, we propose a novel physical layer transmission scheme with codeword level interleaving at the transmitter in this letter, which is termed as interleaver-based SCMA (I-SCMA). Simulation results and analysis show that I-SCMA can provide high security performance without any loss in performance and transmission rate, thus constitutes a viable solution for the next generation wireless networks to provide secure communications.

This paper proposes a new solar hybrid clean fuel-fired distributed energy system to increase the system thermodynamic efficiency and save fossil fuel, in which solar energy is upgraded into high-level chemical energy of syngas (H2 and CO) by integrating solar-driven methanol decomposition based thermochemical conversion. Solar energy, in the form of chemical energy of the generated syngas, is steadily stored and utilized to drive the distributed energy system to generate power, heat and cooling. The double-axis tracking parabolic trough solar collector is deployed to the proposed system to reduce the cosine loss of solar energy. The incorporation of the solar thermochemistry and double-axis solar concentrator technologies leads to a significant improvement in the solar energy utilization efficiency and the off-design performances under varying solar irradiations. With the integration of solar energy utilization and tri-generation, the proposed system achieves a high net solar-to-electric efficiency, 24.66%, and results in high primary energy ratio, 83.86%, exergy efficiency, 38.81%, and carbon emission saving rate, 51.43%. The proposed system is deployed to an office building to study the operation strategies and annual thermo-economy performances, and competitive off-design performances and economy performances are achieved. The research findings open up a new avenue towards the efficient utilization modes of clean fuel and solar energy.

It is important to accurately measure the solar flux distribution on the heated surface for the utilization of solar energy. To this end, in this paper a new measurement system was proposed to measure the solar flux distribution of the absorber tube surface by taking advantage of the end loss effect. The new measurement system does not disturb the collected lights path and influence the operation of the solar collector. The solar flux distribution at different angles can be measured with a few number of heat flux gage by rotating the proposed solar flux measurement system. Compared with existing measurement techniques, the proposed solar flux measurement system has distinct advantages such as simple structure, flexible and reliable operation and easy application. An experimental platform was designed and constructed, and the solar flux distributions on the outer surface of the absorber under different conditions are measured. The feasibility and effectiveness of the proposed measurement method are validated by comparing the experiment results and the numerical simulation results.

A novel solar-assisted combined cooling, heating and power (CCHP) system is developed for improving the energy conversion efficiency in this work. Solar thermal energy (250-350℃) collected by the parabolic trough solar collector is used to drive a thermochemical reaction of methanol decomposition, then the generated solar fuel of syngas is fed into an internal combustion engine (ICE) to generate electricity. The high-temperature exhaust gas released from the ICE is used to produce cooling and heating energies via a double-effect LiBr-H2O absorption refrigerator and heat exchangers. The introduced solar energy is converted to chemical form of syngas and replaces a part of fossil fuel. The numerical simulation of the novel CCHP system is carried out, and the system energy efficiency and exergy efficiency at the designate condition are 77.69% and 55.94%, respectively. The system off-design performances are investigated by deploying it to a shopping center building, and the system annual efficiency reaches to 49.29% with the solar fraction of 11.58%. As compared with the typical CCHP systems with direct methanol combustion, the annual methanol consumption of the proposed system decreases to 895.15 tons, with the fuel saving ratio of 6.11%. The research findings provide a promising way for the cascade utilization of solar energy, and broaden its applications in distributed energy systems.

The solar energy driven Rankine cycle with CO2-H2O binary mixture as a working fluid driven by solar energy is proposed to increase the pressure ratio and specific work in this work. As compared with CO2 working fluid, the condensing temperature increases with the increment of water fraction, and the working fluid with lower pressure is condensed into liquid at ambient temperature. As compared with supercritical CO2 (S-CO2) cycles, the pressure ratio of the proposed cycle is improved by reducing the outlet pressure of turbine, and the consumption work of compression is reduced by compressing the liquid working fluid. As a result, the specific work of the proposed cycle is higher than that of S-CO2 cycle The characteristics of working fluid and parameters optimization are performed with different pressures and compositions of working fluid, and the energy and exergy balances at the design point are conducted to analyze the performances of the system. Theoretical results show that there is an optimal value of cycle efficiency when the mole fraction of water is increased. The solar-to-electric efficiency on the nominal condition reaches to 29.36%, which is higher than existing solar tower systems. Research findings introduce a promising approach for the efficient utilization of the abundant solar resources.

The image reconstruction is an important step in the electrical capacitance tomography (ECT) technology, and its performance directly impacts the reconstruction precision (RP). Beyond existing optimization-based imaging techniques, in this study the data-dependent reference image abstracted by the regularized random vector functional link network (RVFLN) and the domain expertise about imaging targets (ITs) are simultaneously encapsulated as regularizers to form a more effective imaging model. The three-operator splitting (TOS) technique is developed to solve the proposed imaging model more effectively, which extends the flexibility of the TOS method with the improvement in the utilization of image priors. Numerical validation results indicate that the proposed imaging technique achieves better reconstructions as compared with the state-of-the-art methods.

Researches on 5th generation mobile communication networks (5G) are emerging to meet the demands of rapidly developing communications applications. The reliability and security of data have become key factors of its development, and thus 5G has put forward higher requirements for new coding and encryption technologies. In this paper, a physical layer encryption algorithm based on polarization codes and chaotic sequences is proposed to improve the reliability and confidentiality of transmission. In our scheme, chaotic sequences are allocated in the frozen bits of polar codes. Therefore, error correction and encryption can be performed simultaneously. Since the frozen bits are unknown to the eavesdroppers, it is difficult for them to decode the transmitted bits without the knowledge of the chaotic sequences. To further improve the security, we propose to generate the chaotic sequences by using the channel state information. Besides, the chain effects of delayed feedback are applied to increase the decrypted complexity of the eavesdroppers in this paper. Theoretic analysis and simulation results both show that the proposed algorithms can achieve high security without any error rate performance loss.

In this paper, we propose new serial decoding of Luby transform (LT) codes over additive white Gaussian noise channels. LT encoder generates a potentially limitless number of encoded packets, and the decoder incrementally collects the packets to ensure successful recovery of the information. In the proposed algorithm, the newly coming code nodes are the first to pass the messages, and it is their neighboring source nodes that will receive these input messages and update their output messages; then, the next neighboring code nodes that have not been covered are to be included in the updating group; in this greedy way, the message propagation is conducted from neighbors to neighbors. The analysis demonstrates that the proposed algorithm has a faster convergence speed than the conventional ones, and simulation shows that it has an effective bit error rate performance.

Multi interfaces Al-TiAlN nanocomposite films were deposited on AZ91D magnesium alloy with ion source hybrid magnetron sputtering. Relationship between microstructure evolution and corrosion resistance of the films was investigated. The results show that the column structure is interrupted by multi interfaces. The nanocomposite films are consisted of nanocrystal TiN and amorphous AlN phase. The highest hardness of 31.3 GPa and lowest corrosion current density of 9.37 × 10−8 A/cm2 can be obtained by tuning the interface period. The deflection effect of multi interfaces is the key for the improved corrosion resistance, and the failure mechanism is related to pitting and filiform corrosion.

Channel coding and security are important in a communication system. The 5th generation (5G) mobile communication networks call for higher requirements of new coding technologies and encryption technologies. As an efficient coding method, polar codes have attracted more attention in recent years. Besides, the peak-to-average-power ratio (PAPR) is a major problem of the orthogonal frequency-division multiplexing (OFDM) system, which will significantly affect the performance of the OFDM system. In this paper, joint physical-layer encryption and PAPR reduction scheme is proposed, aiming to solve the PAPR problem and achieve high security of the transmission system. In this scheme, we utilize the key generation technology of wireless channels to get the initial value of chaotic sequences. Then, the chaotic sequences can be used to encrypt the information and reduce PAPR simultaneously. Moreover, we use the best information bits of polar codes to store the serial number index of chaotic sequences. The theoretic analysis and simulation results show that the proposed scheme can not only achieve high security in the physical layer but also reduce PAPR in the OFDM system without increasing system complexity and latency.

Curcumin has been reported to exert protective effects on inflammation-related diseases, including spinal cord injury (SCI). Numerous evidence have suggested miRNAs are one of the important targets for curcumin during its anti-inflammatory function. However, little is known about the contribution of miRNAs on the role of curcumin in SCI. Thus, the objective of this study is to determine the role of miRNA (miR)-137-3p during curcumin treatment after SCI. Expression of miR-137-3p and NeuroD1 was detected using RT-qPCR and western blot assay. Inflammation and oxidative stress were measured with the protein expression levels of tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and inducible nitric oxide synthase (iNOS). The target binding between miR-137-3p and NeuroD1 was confirmed via the luciferase reporter assay and RNA immunoprecipitation. LPS induced a higher expression of TNF-α, IL-1β, and iNOS in mouse microglia BV2 cells, which was attenuated by curcumin. miR-137-3p was downregulated and NeuroD1 was upregulated under LPS challenge. Curcumin also alleviated LPS-induced regulation on miR-137-3p and NeuroD1. The knockdown of miR-137-3p and ectopic expression of NeuroD1 could individually abolish the curcumin-mediated downregulation of TNF-α, IL-1β, and iNOS in LPS-challenged BV2 cells. Besides, NeuroD1 was inversely regulated by miR-137-3p via direct binding. Silencing of NeuroD1 reversed the miR-137-3p downregulation-mediated promoting effect on inflammation and oxidative stress in the presence of LPS and curcumin. Downregulation of miR-137-3p abolishes curcumin-mediated protection on LPS-induced inflammation and oxidative stress in mouse microglial BV2 cells depending on the direct upregulation of NeuroD1.

Multiple-input multiple-output (MIMO) and sparse code multiple access (SCMA) are two effective techniques supporting high spectral efficiency and massive connectivity, respectively. Although the combination of these two techniques, namely MIMO-SCMA, can further improve the spectral efficiency, it deteriorates the error performance and greatly increases the computational costs. In this letter, in order to enhance the error performance and reduce the receiver complexity of the uplink MIMO-SCMA system, we propose a new scheme named spatial modulation sparse code multiple access (SM-SCMA). At the receiver, a low complexity joint message passing algorithm based on the principle of the maximum a posterior probability and the simplified factor graph is proposed. Simulation results show that the SM-SCMA can achieve a better bit-error-rate performance while significantly reducing the receiver complexity compared with the conventional MIMO-SCMA.

Security is always an important issue in wireless communications. Physical layer encryption (PLE) is an effective way to enhance wireless communication security and prevent eavesdropping. Rather than replacing cryptography at higher layers, PLE's benefit is to enable using lightweight cryptosystems or provide enhanced security at the signal level. The upper cryptography is faced with a noise-free channel, and the processing object is bit data. In PLE, the effects of channel and noise can be exploited to enhance security and prevent deciphering. In addition, since the processing object is complex vector signals, there are more operational functions to select and design for PLE. The mathematical models, design frameworks, and cryptographic primitives of PLE are established. Two design frameworks are proposed: stream PLE and block PLE. For stream PLE, a new 3D security constellation mapping is derived. For block PLE, two types of sub-transforms are defined: isometry transformations and stochastic transformations. Furthermore, a practical system operation mode PLE-block chaining (PBC) is proposed to enhance the practical system security. The proposed PLE framework can resist known plaintext attacks and chosen-plaintext attacks. The simulation shows that the proposed isometry transformation method has good performances in terms of bit error ratio (BER) penalty and confusion degree.

Significance Growth typically involves differentiation of cells from progenitors into more specialized descendants, often involving lineages of pure and transitional cells to achieve final form. Recent technology has enabled estimation of gene expression profiles of single cells and these profiles theoretically differentiate pure cell types. What is missing from the analytical toolbox is an efficient technique to classify pure and transitional cells from their profiles. Here we propose semisoft clustering with pure cells (SOUP). This algorithm performs well in the hard-clustering problem for pure cell types and excels at identifying transitional cells with soft memberships. Moreover, SOUP provides an estimate of the developmental trajectories based on the estimated cell type membership that naturally adapts to cells in transition., Motivated by the dynamics of development, in which cells of recognizable types, or pure cell types, transition into other types over time, we propose a method of semisoft clustering that can classify both pure and intermediate cell types from data on gene expression from individual cells. Called semisoft clustering with pure cells (SOUP), this algorithm reveals the clustering structure for both pure cells and transitional cells with soft memberships. SOUP involves a two-step process: Identify the set of pure cells and then estimate a membership matrix. To find pure cells, SOUP uses the special block structure in the expression similarity matrix. Once pure cells are identified, they provide the key information from which the membership matrix can be computed. By modeling cells as a continuous mixture of K discrete types we obtain more parsimonious results than obtained with standard clustering algorithms. Moreover, using soft membership estimates of cell type cluster centers leads to better estimates of developmental trajectories. The strong performance of SOUP is documented via simulation studies, which show its robustness to violations of modeling assumptions. The advantages of SOUP are illustrated by analyses of two independent datasets of gene expression from a large number of cells from fetal brain.

A new distributed energy system integrating a solar thermochemical process with a double-axis tracking parabolic trough collector is proposed to address the challenges on large seasonal variations of solar-to-fuel efficiency and insufficient utilization of solar energy in exiting distributed energy systems. Low-energy level discontinuous solar energy is upgraded into the chemical energy of syngas via the solar thermochemical process, which is easy to be stored. The double-axis tracking parabolic trough collector is deployed to the solar thermochemical process to eliminate the cosine loss completely to increase the annual thermodynamic efficiency. With the consideration of the variation of solar energy, the coupling between user’s loads and energy outputs in the proposed system is investigated, and the favorable on-design and off-design thermochemical performances are numerically validated. Results indicate that the solar fuel production and the solar power production in the proposed system increase approximately 27% annually as compared with the reference system.

A series of Sb2S3/Sb2O3/TiO2 (SS/SO/T) composites with different reactant concentrations were synthesized via anodic oxidation and a one-pot hydrothermal method. The chemical compositions, morphologies, and optical absorption properties of prepared samples were characterized by X-ray diffraction, scanning electron microscopy, X-ray photoelectron spectroscopy, energy disperse spectroscopy, elemental mapping and ultraviolet–visible diffuse reflectance spectroscopy. Photocathodic protection performances of these samples were studied using time-dependent open circuit potential, time-dependent photoinduced current density, and photoinduced volt-ampere characteristic. The SS/SO/T composite with a 48 mmol/L antimony source exhibited optimal performance for 304 stainless steel (304SS). This excellent performance origins from the synergistic effect of the ternary system. The narrow band gap Sb2S3 promoted visible light harvesting. The p-n junction between p-type Sb2S3 and n-type SO/T provides a driving force for the separation and transfer of carriers. Well crystallized Sb2O3 rods offer a direct pathway for the carriers migration.

It is of the significant importance to achieve facile and on-site detection of heavy metal ions due to the serious harm to environment and human health. Herein, a facile and portable strategy was developed for detection of Hg2+ via portable pressure meter. Biotinylated DNA1 was conjugated on the surface of streptavidin-coated magnetic beads (MBs) to form MBs-DNA1 complex. In the presence of Hg2+, MBs-DNA1 can hybridize with platinum nanoparticles (PtNPs)-functionalized DNA2 (DNA2-PtNPs) via T-Hg2+-T binding. Then, PtNPs effectively catalyzed the decomposition of H2O2 to generate oxygen, leading to an increase in pressure of sealed well of 96-well plate. The gas pressure was linearly related with the concentration of Hg2+ in the range between 10 pM and 100 nM with a detection limit of 2.79 pM, which is more sensitive than most of the previous reports. The specific T-Hg2+-T binding made it easy to selectively detect Hg2+ even when other metal ions co-existed with Hg2+. Therefore, it offers a cost-effective, rapid, facile and portable way to detect Hg2+ by combining gas-generation reaction with T-Hg2+-T binding, which holds great potential for detecting Hg2+ in water sample.

First-person-view (FPV) cameras are finding wide use in daily life to record activities and sports. In this paper, we propose a succinct and robust 3D convolutional neural network (CNN) architecture accompanied with an ensemble-learning network for activity recognition with FPV videos. The proposed 3D CNN is trained on low-resolution (32 × 32) sparse optical flows using FPV video datasets consisting of daily activities. According to the experimental results, our network achieves an average accuracy of 90%.

In order to accurately identify the behavior of dairy goats in the image, a multi-model fusion convolutional neural network (CNN) method based on the image of dairy goats is proposed. At first, the AlexNet, ResNet50 and Vgg16 models are trained respectively, and the best recognition results of each model are obtained. Then, the attention weight of each model is calculated by feature stitching and other operations. Finally,The feature information of AlexNet, ResNet50 and Vgg16 is combined with attention mechanism to re-weight,and the parameters of the fused multi-model convolutional neural networks are adjusted to obtain the best recognition results of fusion models. Experimental results show that compared with single model and multi-model, the ARV fusion model we proposed achieves higher recognition accuracy, and the average accuracy of each dairy goat behavior is as high as 98.50%.

The conventional beamforming optimization method cannot meet the requirements of constant beamwidth of spare array in different frequency and different beam pointing angles. In this paper, a frequency and steering invariant beamforming method based on compressed sensing (CSFSIB) is proposed. First, the array elements are extended virtually, the sparse signal obtained by virtual array is reconstructed by compressed sensing (CS) recovery algorithm. Then the Second-order cone programming (SOCP) method is used to calculate the weighted vector and optimize the steering invariant beamforming (SIB). Finally, frequency invariant beamforming (FIB) is designed based on inverse Fourier transform (IFT). Simulation results indicate that the proposed method can reduce the sidelobe level and save the number of array elements while keeping the mainlobe width constant.

In this paper, a high-sensitivity optical fiber temperature sensor based on a dual-loop optoelectronic oscillator (OEO) with the Vernier effect has been proposed and experimentally demonstrated. Different from the traditional dual-loop OEOs which comprise a very long loop and a short loop to achieve low-phase noise and single-mode selection, the proposed OEO scheme has two loops with slightly different lengths and does not use any RF filters. A part of the fiber in one of the loops is used as a temperature sensing element as well as the delaying component. An obvious Vernier effect has been generated in the frequency response of the OEO. By detecting the frequency shift of the envelope peak of the measured frequency response curve, the temperature sensing interrogation of the dual-loop OEO based sensor is conducted. The experimental results show that the sensitivity of the proposed dual-loop OEO based temperature sensor can be improved from 6.625 KHz/°C for a single-loop OEO to 210.25KHz/°C by employing the Vernier effect.