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This paper presents a localization method for an underwater multitonal source by using a vertically distributed system in deep water. The system is composed of two kinds of nodes. One is a node at large depth, and the other is a node covering most of the water column. The former and latter are utilized to estimate the source range and depth, respectively. Specifically, the proposed method estimates the source range by matching the spatial arrival angle measured by the first kind of node with the replicas calculated by the acoustic model. Based on the estimation value of the source range, the second kind of node is utilized to estimate the source depth by using an incoherent time reversal method. The effectiveness of the proposed method is demonstrated through numerical simulations. The effects of the measurement error and the sound speed profile mismatch on the performance of the proposed method are also analyzed.

Efficient hydrogen storage and transportation are crucial for the sustainable development of human society. Ammonia, with a hydrogen storage density of up to 17.6 wt%, is considered an ideal energy carrier for large-scale hydrogen storage and has great potential for development and application in the “hydrogen economy”. However, achieving ammonia decomposition to hydrogen under mild conditions is challenging, and therefore, the development of suitable catalysts is essential. Metal oxide-based catalysts are commonly used in the industry. This paper presents a comprehensive review of single and composite metal oxide catalysts for ammonia decomposition catalysis. The focus is on analyzing the conformational relationships and interactions between metal oxide carriers and active metal sites. The aim is to develop new and efficient metal oxide-based catalysts for large-scale green ammonia decomposition.

The spline teeth fracture of separator plates in wet multi-plate clutches compromises driving safety and the vehicle’s lifespan. Tooth fracture is mainly caused by stress concentration at the tooth root and uneven circumferential load distribution. This paper considers parameters such as torque, teeth count, tooth profile, and misalignment errors, establishing the corresponding finite element (FE) model to analyze the impact of the above-mentioned parameters on the strength of the separator plates. Analysis under even and biased load circumstances demonstrated that an optimum tooth count and profile can significantly increase the strength of the separator plates, offering advice for the optimized design of wet multi-plate clutch separator plates.

The reduction of friction-induced noise is a crucial research area for enhancing vehicle comfort, and this paper proposes a method based on circular pit texture to achieve this goal. We conducted a long-term sliding friction test using a pin-on-disc friction and a wear test bench to verify the validity of this method. To compare the friction noise of different surfaces, texture units with varying line densities were machined on the surface of friction disk samples. The resulting friction-wear and noise characteristics of the samples were analyzed in conjunction with the microscopic morphology of the worn surfaces. The results indicate that surfaces with textures can delay the onset of squeal noise, and the pattern of its development differs from that of smooth surfaces. The noise reduction effect is most evident due to the proper distribution of textures that can form furrow-like wear marks at the wear interface. The finite element results demonstrate that this morphology can improve pressure distribution at the leading point and reduce the tendency of system instability.

As we conclude this Special Edition of “Energy Converter: Anaerobic Digestion”, a lingering sense of both achievement and anticipation accompanies us [...]

The development of high-precision satellites has increased the demand for ultraprecision three-degrees-of-freedom (3-DOF) angle measurements for detecting structural deformation. The required instrument should simultaneously measure pitch, yaw, and roll angles using a single reference point. This paper proposes a 3-DOF angle measurement method based on the wavefront interference principle, and a mathematical model and its decoupling algorithm were built. Then, an angle-sensing probe with an extremely simple structure was designed and constructed. Finally, a series of experiments were performed to verify the method’s feasibility. The experiment results showed that the roll, pitch, and yaw measurement resolution of the probe was better than 10, 1, and 1 μrad, respectively, providing a high-performance 3-DOF angle measurement with a single probe. The short-term stabilities of roll, pitch, and yaw were better than 22, 1.7, and 2.0 μrad, respectively.

Forest fires have a significant impact on terrestrial ecosystems, leading to harm to biodiversity and environment. To mitigate the ecological damage caused by forest fires, it was necessary to develop prediction models of fire risk. In this study, by evolving the optimal architecture and parameters using the particle swarm optimization (PSO) algorithm, a convolutional neural network (CNN) deep learning model was proposed to predict forest fire risk on a national scale. Utilizing fire data and fire risk factors from 2001 to 2020 in China, the PSO-CNN-based deep learning model (PSO-CNN) was utilized and tested. Compared to logistic regression, random forest, support vector machine, k-nearest neighbors, and CNN models, the PSO-CNN model exhibited superior performance with an accuracy of 82.2% and an AUC value of 0.92. These results clearly highlighted the effectiveness of the PSO-CNN model in enhancing the accuracy of forest fire prediction. Furthermore, the forest fire risk prediction level estimated by the proposed model on a national scale for the entire country was mostly consistent with actual fire data distribution, indicating its potential to be used as an important direction for deep learning in forest fire prediction research.

Severe erosion wear is found on valve spools, which threatens the safety and reliability of these units. The use of the plasma beam spraying surfacing method can significantly improve the corrosion resistance and sealing performance of hydraulic valve spools, reduce material waste, and reduce maintenance costs. The effects of the co-addition of CeO2 and SiC particles on the morphology, surface cracks, microstructure, precipitated phases, and wear property of plasma-beam-sprayed Fe55-based coatings on 1025 steel were investigated using OM, EDS, ultra-deep field microscopy, and a wet sand rubber wheel friction tester, respectively. The dendrite exhibited a directional growth pattern perpendicular to the substrate and the transitional states of the microstructure with the co-addition of CeO2 and SiC particles. CeO2 or SiC reduced the liquid phase diffusion coefficient DL of Cr and C and resulted in a decrease in the G/R ratio. The dendrites changed into equiaxed grains. The main phase composition of the Fe55 welding layer was Cr7C3, γ-Fe. The martensite in the surfacing layer and the carbides formed Cr7C3, which can improve the hardness of the surfacing layer. The grain boundaries consisted mainly of a reticular eutectic structure. The uniform distribution of the Cr7C3 hard phase in the Fe55+1.5 wt% SiC+0.01 wt% CeO2 resulted in a uniformly worn surface. The sub-wear mechanisms during the friction process were micro-ploughing and micro-cutting. The hardness and toughness of Fe55+1.5 wt% SiC+0.01 wt% CeO2 were well-matched, avoiding excessive micro-cutting and microplastic deformation. A low content of CeO2 could lead to the formation of equiaxed grain and effectively improve the uniformity of the microstructure. The wear-resistant layer of Fe55+1.5 wt% SiC+0.01 wt% CeO2 can effectively improve the service life and long-term sealing performance of the valve spools.

This paper proposes a two-dimensional precision level for real-time measurement using a zoom fast Fourier transform (zoom FFT)-based decoupling algorithm that was developed and integrated in an FPGA. This algorithm solves the contradiction between obtaining high resolution and obtaining high measurement speed, and achieves both high angle-resolution measurement and real-time measurement. The proposed level adopts a silicone-oil surface as the angle-sensitive interface and combines the principle of homodyne interference. By analyzing the frequency of the interference fringes, the angle variation can be determined. The zoom-FFT-based decoupling algorithm improves the system’s frequency resolution of the interference fringes, thereby significantly enhancing the angle resolution. Furthermore, this algorithm improves the efficiency of angle decoupling, while the angle decoupling process can also be transplanted to the board to realize real-time measurement of the level. Finally, a prototype based on the level principle was tested to validate the effectiveness of the proposed method. The principle analysis and test results showed that the angle resolution of the prototype improved from 9 arcsec to about 0.1 arcsec using this angle-solution method. At the same time, the measurement repeatability of the prototype was approximately ±0.2 arcsec. In comparison with a commercial autocollimator, the angle measurement accuracy reached ±0.6 arcsec.

Understanding the infiltration and solidification processes of liquid 5083Al alloy into Al2O3 three-dimensional reticulated porous ceramic (Al2O3(3D) RPC) is essential for optimizing the microstructure and properties of Al2O3(3D)/5083Al interpenetrating phase composites (IPCs) prepared by low-pressure infiltration process (LPIP). This study employs ProCAST software to simulate the infiltration and solidification processes of liquid 5083Al with pouring velocities (PV) of 0.4 m/s infiltrating into Al2O3(3D) RPC preforms with varying porosities at different pouring temperatures (PT) to prepare Al2O3(3D)/5083Al IPCs using LPIP. The results demonstrate that pore diameter of Al2O3(3D) RPC preforms and PT of liquid 5083Al significantly influence the of the infiltration. Solidification process analysis reveals that the Al2O3(3D) RPC preform with smaller pore diameters allows the lower pouring velocity of 5083Al to solidify faster compared to the preform with larger pore diameters. Al2O3(3D)/5083Al IPCs were prepared successfully from Al2O3(3D) RPC porosity of 15 PPI with liquid 5083Al at PV 0.4 m/s and PT 800 °C using LPIP, resulting in nearly fully dense composites, where both Al2O3(3D) RPCs and 5083Al interpenetrate throughout the microstructure. The infiltration and solidification defects were reduced under air pressure of 0.3 MPa (corresponding to PV of 0.4 m/s) during LPIP. Finite volume method simulations are in good agreement with experimental data, validating the suitability of the simplified model for Al2O3(3D) RPCs in the infiltration simulation.

The plant architecture of higher plants is regulated through environmental and genetic factors, as well as phytohormones. Phytohormones play a critical role in regulating shoot branching. We determined the branching phenotype of D16 and N99-6, the content of strigolactones, the genetic expression level, and the interaction between auxin and strigolactones. We found that the branching development of the two soybean varieties under shading was significantly slower than that under normal light. The average branch length of N99-6 decreased by 40.9% after shading; however, the branch length of D16 was not significantly affected. Meanwhile, the branch formation rate in D16 was significantly higher than in N99-6. In addition, after shading treatment, the content of strigolactones in D16 and N99-6 axillary buds increased significantly, and the expression of phytochrome genes, PhyA and PhyB, showed opposite changes. However, strigolactone synthesis gene GmMAX4 and signal transduction gene GmMAX2 expression levels of D16 were lower than those of N99-6 after 24 h of shading. In addition, the application of strigolactone inhibitor TIS108 and auxin inhibitor NPA to soybean had no significant effect on the branch phenotype. The expression of the GmMAX2 gene was significantly up-regulated after the external application of the auxin analog, and the expression of auxin transporter gene GmPINI was significantly down-regulated after external application of the strigolactone analog under shade. In this study, we investigated the adverse effect of shade on soybean branching development, which may be due to the interaction of strigolactones with auxins.

We present a straightforward approach to develop a high-detectivity silicon (Si) sub-bandgap near-infrared (NIR) photodetector (PD) based on textured Si/Au nanoparticle (NP) Schottky junctions coated with graphene film. This is a photovoltaic-type PD that operates at 0 V bias. The texturing of Si is to trap light for NIR absorption enhancement, and Schottky junctions facilitate sub-bandgap NIR absorption and internal photoemission. Both Au NPs and the texturing of Si were made in self-organized processes. Graphene offers additional pathways for hot electron transport and to increase photocurrent. Under 1319 nm illumination at room temperature, a responsivity of 3.9 mA/W and detectivity of 7.2 × 1010 cm × (Hz)1/2/W were obtained. Additionally, at −60 °C, the detectivity increased to 1.5 × 1011 cm × (Hz)1/2/W, with the dark current density reduced and responsivity unchanged. The result of this work demonstrates a facile method to create high-performance Si sub-bandgap NIR PDs for promising applications at ambient temperatures.

Evidence theory is widely used to deal with the fusion of uncertain information, but the fusion of conflicting evidence remains an open question. To solve the problem of conflicting evidence fusion in single target recognition, we proposed a novel evidence combination method based on an improved pignistic probability function. Firstly, the improved pignistic probability function could redistribute the probability of multi-subset proposition according to the weight of single subset propositions in a basic probability assignment (BPA), which reduces the computational complexity and information loss in the conversion process. The combination of the Manhattan distance and evidence angle measurements is proposed to extract evidence certainty and obtain mutual support information between each piece of evidence; then, entropy is used to calculate the uncertainty of the evidence and the weighted average method is used to correct and update the original evidence. Finally, the Dempster combination rule is used to fuse the updated evidence. Verified by the analysis results of single-subset proposition and multi-subset proposition highly conflicting evidence examples, compared to the Jousselme distance method, the Lance distance and reliability entropy combination method, and the Jousselme distance and uncertainty measure combination method, our approach achieved better convergence and the average accuracy was improved by 0.51% and 2.43%.

The popup data communication beacon (PDCB) can send data to the shore and ships through the BeiDou navigation satellite system (BDS) when it surfaces. The data can be collected by a deep-sea landing vehicle (DSLV) and transmitted using a magnetic induction coil. PDCBs can reduce the cost of DSLV recovery and redeployment. Whether the data can be successfully sent mainly depends on the outlet height and roll angle of the PDCB. Thus, accurately assessing the effect of the roll angle on data transmission is crucial. In this study, first, the differential equation of roll motion was preliminarily established using the small-amplitude wave theory along with the shape characteristics of the PDCB. Next, the nonlinear term of the recovery moment was processed using the Linz Ted Poincaré method. Then, the wave current force was analyzed using the Morrison theoretical formula along with an additional inertia moment calculation formula that is suitable for slender cylindrical small buoys. Finally, the theoretical calculation results were verified using the computational fluid dynamics (CFD) method and pool test. The roll angle error of the theoretical calculation was within 5%. Thus, the heave and roll response of PDCBs can be evaluated using theoretical calculation methods. The proposed calculation formula of additional inertia moment has guiding significance for the further optimization of the structure.

Metal nanoparticles are widely used in catalysis. Loading metal nanoparticles into polymer brushes has aroused wide attention, but regulation of catalytic performance still needs to be improved. The novel diblock polymer brushes, polystyrene@sodium polystyrene sulfonate-b-poly (N-isopropylacrylamide) (PSV@PSS-b-PNIPA) and PSV@PNIPA-b-PSS with reversed block sequence, were prepared by surface initiated photoiniferter-mediated polymerization (SI-PIMP) and used as nanoreactors to load silver nanoparticles (AgNPs). The block sequence caused the difference of conformation and further affected the catalytic performance. PSV@PNIPA-b-PSS@Ag was found to be able to control the amount of AgNPs exposed to external reactant of 4-nitrophenol at different temperatures to achieve regulation of the reaction rate due to the hydrogen bonds and further physical crosslinking between PNIPA and PSS.

Artificial intelligence and distributed algorithms have been widely used in mechanical fault diagnosis with the explosive growth of diagnostic data. A novel intelligent fault diagnosis system framework that allows intelligent terminals to offload computational tasks to Mobile edge computing (MEC) servers is provided in this paper, which can effectively address the problems of task processing delays and enhanced computational complexity. As the resources at the MEC and intelligent terminals are limited, performing reasonable resource allocation optimization can improve the performance, especially for a multi-terminals offloading system. In this study, to minimize the task computation delay, we jointly optimize the local content splitting ratio, the transmission/computation power allocation, and the MEC server selection under a dynamic environment with stochastic task arrivals. The challenging dynamic joint optimization problem is formulated as a reinforcement learning (RL) problem, which is designed as the computational offloading policies to minimize the long-term average delay cost. Two deep RL strategies, deep Q-learning network (DQN) and deep deterministic policy gradient (DDPG), are adopted to learn the computational offloading policies adaptively and efficiently. The proposed DQN strategy takes the MEC selection as a unique action while using the convex optimization approach to obtain the local content splitting ratio and the transmission/computation power allocation. Simultaneously, the actions of the DDPG strategy are selected as all dynamic variables, including the local content splitting ratio, the transmission/computation power allocation, and the MEC server selection. Numerical results demonstrate that both proposed strategies perform better than the traditional non-learning schemes. The DDPG strategy outperforms the DQN strategy in all simulation cases exhibiting minimal task computation delay due to its ability to learn all variables online.

To overcome major limiting factors of microbial processes in anaerobic digestion (AD), metal and metal ions have been extensively studied. However, there is confusion about the effects of metals and metal ions on biomethane productivity in previous research. In this study, Zn and Zn2+ were selected as representatives of metals and metal ions, respectively, to investigate the effects on biomethane productivity. After the metals and metal ions at different concentrations were added to the batch AD experiments under the same mesophilic conditions, a Zn dose of 1 g/L and a Zn2+ dose of 4 mg/L were found to cause the highest biomethane production, respectively. The results indicate that metal (Zn) and metal ion (Zn2+) have different mechanisms to improve AD performance. There may be two possible explanations. To act as conductive materials in interspecies electron transfer (IET), relatively high doses of metals (e.g., 1 g/L of Zn, 10 g/L of Fe) are needed to bridge the electron transfer from syntrophic bacteria to methanogenic archaea in the AD process. As essential mineral nutrients, the AD system requires relatively low doses of metal ions (e.g., 4 mg/L of Zn2+, 5 mg/L of Fe2+) to supplement the component of various enzymes that catalyze anaerobic reactions and transformations. This research will provide clear insight for selecting appropriate amounts of metals or metal ions to enhance biomethane productivity for industrial AD processes.

Steel fiber-reinforced ultra-high-performance concrete (UHPC) is becoming an important type of concrete reinforcement. After mixing with the reinforced steel fibers, the UHPC has perfect flex resistance, shear strength, crack resistance, shock resistance, and anti-seepage. In this study, the influence of straight, corrugated, and hooked brass-coated steel fibers (BCSFs) on the microstructure, mechanical properties, and crack expansion mechanism of ultra-high-performance concrete (UHPC) with varying content of 1–6 wt.% under different curing times were investigated. Field emission scanning electron microscopy and energy dispersive X-ray spectrometry were employed to characterize the microstructure of the BCSF-reinforced UHPC mix specimens. X-ray computed tomography was employed to determine the porosity of the BCSF-reinforced UHPC mix specimens. The obtained results indicate the flexural strength and compressive strength of BCSF-reinforced UHPC mix specimens are enhanced, along with increasing the content of BCSFs reinforcement with different shapes (straight, corrugated, and hooked). The embedded BCSFs play a major role in the adhesive property and stress transfer of the BCSFs–UHPC matrix interface. Different from many studies, the flexural strength of mix UHPC with straight BCSFs is higher than those with corrugated and hooked BCSFs. However, the compressive strength of UHPC with corrugated BCSFs is higher than those with straight and hooked BCSFs. The flexural strength of mix UHPC with 6 wt.% straight BCSFs at 28 days reaches the maximum value of 26.2 MPa, and the compressive strength of UHPC with 6 wt.% corrugated BCSFs at 28 days reaches the maximum value of 142.3 MPa. With the increase in straight BCSF content from 1 wt.% to 6 wt.%, the porosity in mix UHPC reduces gradually from 18.4% to 8.3%. The length of average crack spacing is dependent on the straight BCSF content. With the increase in straight BCSF content from 1 wt.% to 6 wt.%, the average crack length reduces gradually from 34.2 mm to 12.1 mm, and the average crack width reduces gradually from 0.78 mm to less than 0.1 mm. During crack extension, part of the energy in the UHPC mixture specimen with the 6 wt.% BCSF content flows into the crack tip region converted into the work dissipated during the bridging process. The crack propagation resistance of the UHPC mixture with straight BCSFs was improved compared with those with corrugated and hooked BCSFs. The bond strength between the BCSFs and UHPC matrix was enhanced by using vibrational mixing, and the brass film coated on the BCSFs contributes to increase the flexural and compressive strength of the UHPC mixture.

The spring steel for automotive stabilizer bars has a great responsibility in that its quality directly affects the stability, safety, and comfort of vehicle operation. The isothermal thermal compression behavior of a novel lean Si spring steel that was used to manufacture an anti-roll bar was investigated with a DIL805A/D quenching thermal dilatometer in this research. A hyperbolic sine type of constitutive model was established, and hot processing maps were produced to evaluate the experimental steel’s hot workability properties. The experimental results suggest that dynamic recrystallization (DRX) preferentially occurs at a low strain rate and high thermal processing temperature, while the processing maps of the experimental steel are susceptible to strain. The instability regions increase as the strain increases. The processing maps’ stable and instable domains should be decided upon comprehensive analysis of the instability criterion, power dissipation efficiency, and strain rate sensitivity index. The optimum parameters of hot processing for the experimental steel at various strains are that the deformation temperature of 1000–1150 °C and the strain rate of 0.1, approximately.

In this study, an Al2O33D/5083 Al composite was fabricated by infiltrating a molten 5083 Al alloy into a three-dimensional alumina reticulated porosity ceramics skeleton preform (Al2O33D) using a pressureless infiltration method. The corrosion resistance of 5083 Al alloy and Al2O33D/5083 Al in NaCl solution were compared via electrochemical impedance spectroscopy (EIS), dynamic polarization potential (PDP), and neutral salt spray (NSS) tests. The microstructure of the two materials were investigated by 3D X-ray microscope and scanning electron microscopy aiming at understanding the corrosion mechanisms. Results show that an Al2O33D/5083 Al composite consists of interpenetrating structure of 3D-continuous matrices of continuous networks 5083 Al alloy and Al2O33D phase. A large area of strong interfaces of 5083 Al and Al2O33D exist in the Al2O33D/5083 Al composite. The corrosion development process can be divided into the initial period, the development period, and the stability period. Al2O33D used as reinforcement in Al2O33D/5083 Al composite improves the corrosion resistance of Al2O33D/5083 Al composite via electrochemistry tests. Thus, the corrosion resistance of Al2O33D/5083 Al is higher than that of 5083 Al alloy. The NSS test results indicate that the corrosion resistance of Al2O33D/5083 Al was lower than that of 5083 Al alloy during the initial period, higher than that of 5083 Al alloy during the development period, and there was no obvious difference in corrosion resistance during the stability period. It is considered that the elements in 5083 Al alloy infiltrated into the Al2O33D/5083 Al composite are segregated, and the uniform distribution of the segregated elements leads to galvanic corrosion during the corrosion initial period. The perfect combination of interfaces of Al2O33D and the 5083 Al alloy matrix promotes excellent corrosion resistance during the stability period.

The regulation of high sea fishing would not be successful without cooperation among the states in the current international society, without a world government. However, the ongoing quest for cooperation in the field of fishery governance focuses too much on the unilateral responsibility of a state to cooperate with a RFMO, overlooking the responsibility of state parties of an RFMO or the state seeking to regulate IUU fishing. This essay reveals that the equitable consideration of fishery governance is sometimes prejudiced in the name of conservation. Fishery governance involves food security, employment, free trade, and the environment. An ideal regime of high sea fishing is expected to balance the conflicting values and bring an end to the fragmentation of international law. The systemic interpretation approach, which is based on Article 31, paragraph 3(c) of the Vienna Convention on the Law of Treaties, contributes to a fairer governance of high sea fishing. Such an approach revives the obligation of the state to cooperate in the fishery sector by referring to external legal sources, including human rights laws, WTO laws, and environmental laws.

The remaining useful life (RUL) of bearings based on deep learning methods has been increasingly used. However, there are still two obstacles in deep learning RUL prediction: (1) the training process of the deep learning model requires enough data, but run-to-failure data are limited in the actual industry; (2) the mutual dependence between RUL predictions at different time instants are commonly ignored in existing RUL prediction methods. To overcome these problems, a RUL prediction method combining the data augmentation strategy and Wiener–LSTM network is proposed. First, the Sobol sampling strategy is implemented to augment run-to-failure data based on the degradation model. Then, the Wiener–LSTM model is developed for the RUL prediction of bearings. Different from the existing LSTM-based bearing RUL methods, the Wiener–LSTM model utilizes the Wiener process to represent the mutual dependence between the predicted RUL results at different time instants and embeds the Wiener process into the LSTM to control the uncertainty of the result. A joint optimization strategy is applied in the construction of the loss function. The efficacy and superiority of the proposed method are verified on a rolling bearing dataset obtained from the PRONOSTIA platform. Compared with the conventional bearing RUL prediction methods, the proposed method can effectively augment the bearing run-to-failure data and, thus, improve the prediction results. Meanwhile, fluctuations of the bearing RUL prediction result are significantly suppressed by the proposed method, and the prediction errors of the proposed method are much lower than other comparative methods.

The relationship between clutch thermodynamic characteristics and contact states of friction components is explored numerically and experimentally. The clutch thermodynamic numerical model is developed with consideration of the contact state and oil film between friction pairs. The clutch bench test is conducted to verify the variation of the clutch thermodynamic characteristics from the uniform contact (UCS) to the intermittent contact (ICS). The results show that the oil film decreases gradually with increasing temperature; the lubrication state finally changes from hydrodynamic lubrication to dry friction, where the friction coefficient shows an increasing trend before a decrease. Thus, the friction torque in UCS gradually increases after the applied pressure stabilizes. When the contact state changes to ICS, the contact pressure increases suddenly and the oil film decreases rapidly in the local contact area, bringing about a sharp increase in friction torque; subsequently, the circumferential and radial temperature differences of friction components expand dramatically. However, if the contact zone is already in the dry friction state, friction torque declines directly, resulting in clutch failure. The conclusions can potentially be used for online monitoring and fault diagnosis of the clutch.

Cavity-enhanced electro-optic comb generators (CEEOCGs) can provide optical frequency combs with excellent stability and configurability. The existing methods for CEEOCGs spectrum characterization, however, are based on approximations and have suffered from either iterative calculations or limited applicable conditions. In this paper, we show a spectrum characterization method by accumulating the optical electrical field with respect to the count of the round-trip propagation inside of CEEOCGs. The identity transformation and complete analysis of the intracavity phase delay were conducted to eliminate approximations and be applicable to arbitrary conditions, respectively. The calculation efficiency was improved by the noniterative matrix operations. Setting the maximum propagation count as 1000, the spectrum of the center ±300 comb modes can be characterized with merely the truncation error of floating-point numbers within 1.2 s. More importantly, the effects of all CEEOCG parameters were comprehensively characterized for the first time. Accordingly, not only the exact working condition of CEEOCG can be identified for further optimization, but also the power of each comb mode can be predicted accurately and efficiently for applications in optical communications and waveform synthesis.

Dielectric capacitors have received increasing attention due to their high power density. The Bi-based Aurivillius phase compound Bi3.25La0.75Ti3O12 (BLT) is considered a potential material in the field of energy storage due to its excellent ferroelectric properties and good fatigue resistance, and temperature stability. In this paper, 0.4Bi0.5Na0.5TiO3-0.6Bi3.25La0.75Ti3O12 (0.4NBT4BNT-0.6BLT)-thin films were prepared on Pt/Ti/SiO2/Si substrates with the sol-gel method. The addition of BNT destroys the long-range ferroelectric order of BLT and forms nanodomains. By increasing the BNT content, the BLT is transformed from a ferroelectric state to a relaxed state, and its application in the field of energy storage is realized. The recoverable energy density is 42.41 J/cm3, and the recoverable energy storage density is relatively stable in the range of 25–200 °C with good thermal stability. The energy storage efficiency is 75.32% at ~2663 kV/cm. The leakage current density at 300 kV/cm is 1.06 × 10−9 A/cm2.

Identifying disease-related miRNAs can improve the understanding of complex diseases. However, experimentally finding the association between miRNAs and diseases is expensive in terms of time and resources. The computational screening of reliable miRNA–disease associations has thus become a necessary tool to guide biological experiments. “Similar miRNAs will be associated with the same disease” is the assumption on which most current miRNA–disease association prediction methods rely; however, biased prior knowledge, and incomplete and inaccurate miRNA similarity data and disease similarity data limit the performance of the model. Here, we propose heuristic learning based on graph neural networks to predict microRNA–disease associations (HLGNN-MDA). We learn the local graph topology features of the predicted miRNA–disease node pairs using graph neural networks. In particular, our improvements to the graph convolution layer of the graph neural network enable it to learn information among homogeneous nodes and among heterogeneous nodes. We illustrate the performance of HLGNN-MDA by performing tenfold cross-validation against excellent baseline models. The results show that we have promising performance in multiple metrics. We also focus on the role of the improvements to the graph convolution layer in the model. The case studies are supported by evidence on breast cancer, hepatocellular carcinoma and renal cell carcinoma. Given the above, the experiments demonstrate that HLGNN-MDA can serve as a reliable method to identify novel miRNA–disease associations.

An accurate flux density calculation is essential for optimizing and designing solar tower systems. Most of the existing methods introduce multiple assumptions, and the accuracy and scope of the application are limited. This paper proposes an integration model used to calculate the flux density distribution after only applying the Gaussian model for solar brightness distribution. It is the first time that multiple reflections and the influence of the optical error transferred from different planes of the glass mirror are considered in order to build an optical model for the flux density of a heliostat. The reflection from two surfaces of the glass mirror used to form three main parts of beams was considered in the present model, and Fresnel’s equations were applied to calculate the energy of the three parts of reflected rays. An elliptic Gaussian model was applied for the optical error distribution of the heliostat. The model error was evaluated using the experimental data of ten heliostats, and the applicability and accuracy of the model were verified through flux distribution and an intercept factor. The average relative prediction error of the present model from the experimental data was only 2.83%, which is less than SolTrace and other models.

In this paper, considering the simultaneous influence of multi-source disturbances, system modeling uncertainties and input–output constraints, an adaptive robust attitude tracking control scheme is proposed for near space vehicles (NSVs) which is expressed as a stochastic nonlinear system. A multi-dimensional Taylor polynomial network (MTPN) is utilized to handle the system uncertainties, and the nonlinear disturbance observer (NDO) based on MTPN is designed to estimate the external disturbances. Furthermore, by constructing the auxiliary system to tackle the input saturation and introducing the Tan-type barrier Lyapunov function (TBLF) to solve the output constraint, the constrained control strategy can be obtained. Combining with backstepping control (BC) technique and stochastic control method, an adaptive robust stochastic control scheme is developed based on NDO, MTPN, and auxiliary system, and the closed-loop system stability in the sense of probability is analyzed based on stochastic Lyapunov stability theory. Finally, numerical simulations further demonstrate the feasibility of the proposed tracking control scheme.

The propagation of infrasound in the atmosphere is influenced by atmospheric environmental parameters, which affect the precise localization of the infrasound source. Therefore, it has become crucial to quantify the influence of atmospheric environmental parameters on infrasound propagation. First, in this paper, the tau-p model is chosen as the physical model of infrasound propagation in a non-uniform moving medium. The atmospheric environmental parameters affecting infrasound propagation are determined. Secondly, the atmospheric environmental parameter distribution data are generated using the Sobol sampling method. Third, the generated atmospheric data are incorporated into the physical model of infrasound propagation to solve the output. Finally, Sobol sensitivity analysis is performed for each parameter, and the atmospheric parameter with the largest Sobol index is identified as the one with the most significant influence on infrasound propagation.

The clutch temperature rise characteristics in successive shifting conditions are crucial to its thermal stability and thermal safety. In the present paper, a comprehensive numerical model is proposed to investigate the temperature change of separator discs during successive shifting with the consideration of convection heat transfer in disengaged friction pair gaps, which is validated by repeated shifting experiments on the SAE#2 test bench. Since the second separator disc near the piston has the widest disengaged gaps and double-sided heat input, its temperature rise and temperature drop are the highest. The temperature rise gradually equals the temperature drop with the increasing working cycle, then the maximum clutch temperature no longer increases. The longer the shifting interval, the better the heat dissipation is, thus the lower the accumulated temperature rise. Moreover, the increasing lubrication oil temperature reduces the convection heat transfer and increases the temperature rise in an engaging process, but the accumulated temperature rise does not increase due to the widened friction pair gaps. This paper can obtain the temperature rise characteristics of a wet multi-disc clutch concerning its disengaged gaps during successive shifting, which is a promising candidate for investigating its overall performance.

CuInP2S6 (CIPS) is a novel two-dimensional (2D) van der Waals (vdW) ferroelectric layered material with a Curie temperature of TC~315 K, making it promising for great potential applications in electronic and photoelectric devices. Herein, the ferroelectric and electric properties of CIPS at different thicknesses are carefully evaluated by scanning probe microscopy techniques. Some defects in some local regions due to Cu deficiency lead to a CuInP2S6–In4/3P2S6 (CIPS–IPS) paraelectric phase coexisting with the CIPS ferroelectric phase. An electrochemical strain microscopy (ESM) study reveals that the relaxation times corresponding to the Cu ions and the IPS ionospheres are not the same, with a significant difference in their response to DC voltage, related to the rectification effect of the ferroelectric tunnel junction (FTJ). The electric properties of the FTJ indicate Cu+ ion migration and propose that the current flow and device performance are dynamically controlled by an interfacial Schottky barrier. The addition of the ferroelectricity of CIPS opens up applications in memories and sensors, actuators, and even spin-orbit devices based on 2D vdW heterostructures.

The precise localization of the infrasound source is important for infrasound event monitoring. The localization of infrasound sources is influenced by the atmospheric propagation environment and infrasound measurement equipment in the large-scale global distribution of infrasound arrays. A distributed infrasound source localization method based on sparse Bayesian learning (SBL) and Bayesian information fusion is proposed to reduce the localization error. First, the arrival azimuth of the infrasound source is obtained based on the SBL algorithm. Then, the infrasound source localization result is obtained by the Bayesian information fusion algorithm. The localization error of the infrasound source can be reduced by this infrasound source method, which incorporates the uncertainty of the infrasound propagation environment and infrasound measurement equipment into the infrasound source localization results. The effectiveness of the proposed algorithm was validated using rocket motor explosion data from the Utah Test and Training Range (UTTR). The experimental results show that the arrival azimuth estimation error can be within 2° and the localization distance error is 3.5 km.

To study the friction and wear performance of carbon fiber reinforced friction materials under different working conditions, paper-based friction materials with different fibers were prepared. Experiments on the SAE#2 test bench were conducted to study the infectors including friction torques, surface temperature, coefficient of friction (COF), and surface morphologies. The results were analyzed, which indicated that the carbon fiber reinforced friction material could provide a higher friction torque and a lower temperature rising rate under the applied high pressure and high rotating speed conditions. As the pressure increased from 1 MPa to 2.5 MPa, the friction torque of plant fiber reinforced material increased by 150%, the friction torque of carbon fiber reinforced material increased by 400%, and the maximum temperature of plant fiber reinforced and carbon fiber reinforced material reached the highest value at 1.5 MPa. Thus, carbon fibers not only improved the COF and friction torque performance but also had advantages in avoiding thermal failure. Meanwhile, carbon fiber reinforced friction materials can provide a more stable COF as its variable coefficient (α) only rose from 38.18 to 264.62, from 1 MPa to 2.5 MPa, which was much lower than the natural fiber reinforced friction materials. Simultaneously, due to the good dispersion and excellent mechanical properties of PAN chopped carbon fibers, fewer pores formed on the initial surface, which improved the high wear resistance, especially in the intermedia disc.

This paper investigates the effects of disc deformation on the tilting-induced vibration of a splined spinning disc with axial-fixed boundaries.The purpose is to provide an intuitive interpretation of the vibration variance of the wet clutch system with different deformed discs. First, tilting models of flat and deformed discs are derived by introducing distinctive shape functions. Additionally, the inner spline interface is chosen as the friction boundary. Then, an impact model between friction pairs and the rigid boundary is established by adopting Hertz’s contact theory. Finally, the dynamic equations are solved via numerical methods, and the responses are analyzed in both time and frequency domains. The deformation can increase the nonlinearity of the dynamic response of the spinning disc. Moreover, the effects of increasing the impulse force and reducing the boundary distance are quite similar; they both increase the motion intensity.

Dihydrouridine (D) is an abundant post-transcriptional modification present in transfer RNA from eukaryotes, bacteria, and archaea. D has contributed to treatments for cancerous diseases. Therefore, the precise detection of D modification sites can enable further understanding of its functional roles. Traditional experimental techniques to identify D are laborious and time-consuming. In addition, there are few computational tools for such analysis. In this study, we utilized eleven sequence-derived feature extraction methods and implemented five popular machine algorithms to identify an optimal model. During data preprocessing, data were partitioned for training and testing. Oversampling was also adopted to reduce the effect of the imbalance between positive and negative samples. The best-performing model was obtained through a combination of random forest and nucleotide chemical property modeling. The optimized model presented high sensitivity and specificity values of 0.9688 and 0.9706 in independent tests, respectively. Our proposed model surpassed published tools in independent tests. Furthermore, a series of validations across several aspects was conducted in order to demonstrate the robustness and reliability of our model.

Rolling bearings are critical to the normal operation of mechanical systems, which often undergo time-varying working conditions. When the local defects appear on a rolling bearing, the transient impulses will generate and be covered by the strong background noise. Therefore, extracting the rolling bearing weak fault feature with time-varying speed is critical to mechanical system diagnosis. A weak fault feature extraction strategy of rolling bearing under time-varying working conditions is proposed. Firstly, the order-frequency spectral correlation (OFSC) is computed for transferring the measured signal into a higher dimensional space. Then, the joint sparsity and low-rankness constraint is imposed on OFSC to detect the time-varying faulty characteristics. An algorithm in the alternating direction method of multipliers (ADMM) framework is derived. Finally, the enhanced envelope order spectrum (EEOS) is applied to further detect the defective features, which can make the fault features more obvious. The feasibility of the proposed method is confirmed by simulations and an experimental case.

To study the influence of nano-additives on the friction-wear characteristics of friction materials, the nano-sized silicon carbide particles which have excellent chemical and physical properties are considered to add in composite to form the modified friction material. The influence of the silicon carbide nanoparticles (SCN) on the friction-wear characteristics of copper-based friction materials (CBFM) is investigated via the SAE#2 (made in Hangzhou, China) clutch bench test with the applied pressure, rotating speed, and automatic transmission fluid (ATF) temperature taken into account. Moreover, the variations of friction torque and temperature are considered to evaluate the friction performance, and the variable coefficient is employed to describe the friction stability. The wear characteristics of friction materials are investigated by the disc changes in thickness and micro-morphology. The results show that the CBFM with SCN can provide a higher friction torque, which increased by 30% to 50% compared with CBFM. The variable coefficient of CBFM with SCN changes from 674 to 52 with the rotating speed raised from 600 rpm to 3000 rpm, which shows that the friction stability is relatively worse. Furthermore, the micromorphology shows that the CBFM with SCN has lower porosity and surface roughness, which increases the microscopic contact area and the coefficient of friction (COF). Simultaneously, the reduction in porosity also leads to a decrease in the cooling quality, bringing about a rapid temperature rise. Thus, the wear amount of CBFM with SCN increases significantly, especially for the friction disc in the axial middle position.

Underground coal mining inevitably causes ground fissures, especially permanent cracks that cannot be closed at the boundary of the working face. Studying the underground three-dimensional morphology of the permanent cracks allows one to accurately constrain the formation and development of the ground fissures. This information will contribute to reducing mine disasters and is also a prerequisites to avoid environmental pollution. We selected the Zhangjiamao coal mine (China), which is situated in a collapsible loess area, as a case study for deciphering the formation of permanent cracks. After injecting gypsum slurry into the mine, a three-dimensional model of the ground fissures is obtained by three-dimensional (3D) laser scanner technology that records the 3D underground morphology. Integrating the geological context of a collapsible loess area, the characteristics and main processes of the ground fissure development are constrained: (1) The width of the ground fissure decreases to 0 with increasing depth and is strongly affected by the soil composition. (2) Along the vertical extension direction, the ground fissures are generally inclined to the inner-side of the working face, but the direction remains uncertain at different depths. (3) The transverse propagation direction of the ground fissure becomes more complex with increasing depth. (4) Under the influence of soil texture and water, loose soil fills the bottom of the ground fissure, thus affecting the underground 3D morphology.

Overcoming obstacles to commercialization of algal-based processes for biofuels and co-products requires not just piecemeal incremental improvements, but rather a comprehensive and fundamental re-consideration starting with the selected algae and its associated cultivation, harvesting, biomass conversion, and refinement. A novel two-stage process designed to address challenges of mass outdoor microalgal cultivation for biofuels and co-products was previously demonstrated using an oleaginous, haloalkaline-tolerant, and multi-trophic green Chlorella vulgaris. ALP2 from a soda lake. This involved cultivating the microalgae in a fermenter heterotrophically or photobioreactor mixotrophically (first-stage) to rapidly obtain high cell densities and inoculate an open-pond phototrophic culture (second-stage) featuring high levels of NaHCO3, pH, and salinity. An improved two-stage cultivation that instead sustainably used as more cheap and sustainable inputs the organic carbon, nitrogen, and phosphorous from fractionation of waste was here demonstrated in a small-scale biorefinery process. The first cultivation stage consisted of two simultaneous batch flask cultures featuring (1) mixotrophic cell productivity of 7.25 × 107 cells mL−1 day−1 on BG-110 medium supplemented with 1.587 g L−1 urea and an enzymatic hydrolysate of pre-treated (torrefaction + grinding + ozonolysis + soaking ammonia) wheat-straw that corresponded to 10 g L−1 glucose, and (2) mixotrophic cell productivity of 2.25 × 107 cells mL−1 day−1 on BG-110 medium supplemented with 1.587 g L−1 urea and a purified and de-toxified condensate of pre-treated (torrefaction + grinding) wheat straw that corresponded to 0.350 g L−1 of potassium acetate. The second cultivation stage featured 1H NMR-determined phototrophic lipid productivity of 0.045 g triacylglycerides (TAG) L−1 day−1 on BG-110 medium supplemented with 16.8 g L−1 NaHCO3 and fed batch-added 22% (v/v) anaerobically digested food waste effluent at HCl-mediated pH 9.

Interface problems and the destruction of the continuity of the oxide film in the Al matrix usually reduce the corrosion resistance of the material. In this paper, the corrosion resistance of Al matrix composites (AMCs) was improved by introducing the silicon carbide skeletons (SiC3D) obtained with polymer replica technology. SiC3D/6061Al was fabricated by infiltrating molten 6061Al alloy in the oxidized SiC3D using the low-pressure casting method. The corrosion resistance performances of 6061Al and SiC3D/6061Al in NaCl solution were studied by electrochemical, neutral salt spray corrosion (NSS), and salt leaching (SL) tests. Results show corrosion resistance of SiC3D/6061Al is higher than that of 6061Al alloys by open circuit potential (OCP), potentio-dynamic polarization (PDP), and electrochemical impedance spectroscopy (EIS) tests. However, NSS and SL tests show the corrosion resistance of SiC3D/6061Al is lower than that of 6061Al alloy. The reason is a corrosion resistant and anti-oxidation network macrostructure with large interface recombination, few concentrated interfaces, and a small specific area that formed in SiC3D/6061Al. SiC3D cannot damage the continuity of the Al2O3 passivating film, and the network macrostructure greatly improves the corrosion resistance performance.

Clutch disengaging dynamic characteristics, including the disengaging duration and the variations of friction pair gaps and friction torque, are crucial to the shifting control of an automatic transmission. In the present paper, the influence of lubrication oil (ATF) temperature on disengaging dynamic characteristics is investigated through a comprehensive numerical model for the clutch disengaging process, which considers the hydrodynamic lubrication, the asperity contact, the heat transfer, the spline resistance, and the impact between the piston and clutch hub. Moreover, the non-uniformity coefficient (NUC) is proposed to characterize the disengaging uniformity of friction pairs. As the ATF temperature increases from 60 °C to 140 °C, the clutch disengaging duration shortens remarkably (shortened by 55.1%); besides, the NUC sees a decreasing trend before a slight increase. When the ATF temperature is 80 °C, the distribution of friction pair gaps is most uniform. During the disengaging process, the increase of ATF temperature not only accelerates the change of the lubrication status between friction pairs but also contributes to the decrease of contact torque and hydrodynamic torque. This research demonstrates for the first time, evidence for clutch disengaging dynamic characteristics with the consideration of ATF temperature.

As an essential part of the transmission, the life of the clutch directly affects the stability of the transmission. In this paper, a finite element model and a thermodynamic numerical model of a multi-disc clutch are established to investigate the influence of material parameters on the contact pressure distribution. The pressure distribution index (PDI) is firstly proposed to evaluate the pressure difference among friction pairs. Moreover, the correctness of the numerical model is verified by the clutch static pressure experiment. The results show that increasing the elastic modulus and Poisson’s ratio of the backplate can effectively improve the uniformity of the contact pressure. However, the variations in material parameters of other clutch components can not easily smooth the pressure difference. Therefore, optimized material parameters for the clutch are proposed, where the maximum pressure and temperature differences are reduced by about 27.2% and 10.3%, respectively.

SARS-CoV-2 infection has caused a global pandemic that has severely damaged both public health and the economy. The nucleocapsid protein of SARS-CoV-2 is multifunctional and plays an important role in ribonucleocapsid formation and viral genome replication. In order to elucidate its functions, interaction partners of the SARS-CoV-2 N protein in human cells were identified via affinity purification and mass spectrometry. We identified 160 cellular proteins as interaction partners of the SARS-CoV-2 N protein in HEK293T and/or Calu-3 cells. Functional analysis revealed strong enrichment for ribosome biogenesis and RNA-associated processes, including ribonucleoprotein complex biogenesis, ribosomal large and small subunits biogenesis, RNA binding, catalysis, translation and transcription. Proteins related to virus defence responses, including MOV10, EIF2AK2, TRIM25, G3BP1, ZC3HAV1 and ZCCHC3 were also identified in the N protein interactome. This study comprehensively profiled the viral–host interactome of the SARS-CoV-2 N protein in human cells, and the findings provide the basis for further studies on the pathogenesis and antiviral strategies for this emerging infection.

The zone refining method is a physical method for effectively purifying metals. Increasing yield and reducing impurity content have always been the focus of its research. This article systematically summarizes the relevant research on the production of high-purity metals by zone refining, including mechanisms, parameter optimization, zone refining types, analysis methods, limitations, and future development directions, and it provides relevant theoretical foundations for the production of high-purity metals as well.

α-l-arabinofuranosidase is a subfamily of glycosidases involved in the hydrolysis of l-arabinofuranosidic bonds, especially in those of the terminal non-reducing arabinofuranosyl residues of glycosides, from which efficient glycoside hydrolases can be screened for the transformation of ginsenosides. In this study, the ginsenoside Rc-hydrolyzing α-l-arabinofuranosidase gene, BsAbfA, was cloned from Bacilus subtilis, and its codons were optimized for efficient expression in E. coli BL21 (DE3). The recombinant protein BsAbfA fused with an N-terminal His-tag was overexpressed and purified, and then subjected to enzymatic characterization. Site-directed mutagenesis of BsAbfA was performed to verify the catalytic site, and the molecular mechanism of BsAbfA catalyzing ginsenoside Rc was analyzed by molecular docking, using the homology model of sequence alignment with other β-glycosidases. The results show that the purified BsAbfA had a specific activity of 32.6 U/mg. Under optimal conditions (pH 5, 40 °C), the kinetic parameters Km of BsAbfA for pNP-α-Araf and ginsenoside Rc were 0.6 mM and 0.4 mM, while the Kcat/Km were 181.5 s−1 mM−1 and 197.8 s−1 mM−1, respectively. More than 90% of ginsenoside Rc could be transformed by 12 U/mL purified BsAbfA at 40 °C and pH 5 in 24 h. The results of molecular docking and site-directed mutagenesis suggested that the E173 and E292 variants for BsAbfA are important in recognizing ginsenoside Rc effectively, and to make it enter the active pocket to hydrolyze the outer arabinofuranosyl moieties at C20 position. These remarkable properties and the catalytic mechanism of BsAbfA provide a good alternative for the effective biotransformation of the major ginsenoside Rc into Rd.

Beamforming technology is an essential method in acoustic imaging or reconstruction, which has been widely used in sound source localization and noise reduction. The beamforming algorithm can be described as all microphones in a plane simultaneously recording the source signal. The source position is then localized by maximizing the result of the beamformer. Evidence has shown that the accuracy of the sound source localization in a 2D plane can be improved by the non-synchronous measurements of moving the microphone array. In this paper, non-synchronous measurements are applied to 3D beamforming, in which the measurement array envelops the 3D sound source space to improve the resolution of the 3D space. The entire radiated object is covered better by a virtualized large or high-density microphone array, and the range of beamforming frequency is also expanded. The 3D imaging results are achieved in different ways: the conventional beamforming with a planar array, the non-synchronous measurements with orthogonal moving arrays, and the non-synchronous measurements with non-orthogonal moving arrays. The imaging results of the non-synchronous measurements are compared with the synchronous measurements and analyzed in detail. The number of microphones required for measurement is reduced compared with the synchronous measurement. The non-synchronous measurements with non-orthogonal moving arrays also have a good resolution in 3D source localization. The proposed approach is validated with a simulation and experiment.

Seed germination is one of the most important stages during plant life cycle, and DOG1 (Delay of germination1) plays a pivotal regulatory role in seed dormancy and germination. In this study, we have identified the DOG1-Like (DOG1L) family in soybean (Glycine max), a staple oil crop worldwide, and investigated their chromosomal distribution, structure and expression patterns. The results showed that the GmDOG1L family is composed of 40 members, which can be divided into six subgroups, according to their evolutionary relationship with other known DOG1-Like genes. These GmDOG1Ls are distributed on 18 of 20 chromosomes in the soybean genome and the number of exons for all the 40 GmDOG1Ls varied greatly. Members of the different subgroups possess a similar motif structure composition. qRT-PCR assay showed that the expression patterns of different GmDOG1Ls were significantly altered in various tissues, and some GmDOG1Ls expressed primarily in soybean seeds. Gibberellic acid (GA) remarkably inhibited the expression of most of GmDOG1Ls, whereas Abscisic acid (ABA) inhibited some of the GmDOG1Ls expression while promoting others. It is speculated that some GmDOG1Ls regulate seed dormancy and germination by directly or indirectly relating to ABA and GA pathways, with complex interaction networks. This study provides an important theoretical basis for further investigation about the regulatory roles of GmDOG1L family on soybean seed germination.

Some drugs can be used to treat multiple diseases, suggesting potential patterns in drug treatment. Determination of drug treatment patterns can improve our understanding of the mechanisms of drug action, enabling drug repurposing. A drug can be associated with a multilayer tissue-specific protein–protein interaction (TSPPI) network for the diseases it is used to treat. Proteins usually interact with other proteins to achieve functions that cause diseases. Hence, studying drug treatment patterns is similar to studying common module structures in multilayer TSPPI networks. Therefore, we propose a network-based model to study the treatment patterns of drugs. The method was designated SDTP (studying drug treatment pattern) and was based on drug effects and a multilayer network model. To demonstrate the application of the SDTP method, we focused on analysis of trichostatin A (TSA) in leukemia, breast cancer, and prostate cancer. We constructed a TSPPI multilayer network and obtained candidate drug-target modules from the network. Gene ontology analysis provided insights into the significance of the drug-target modules and co-expression networks. Finally, two modules were obtained as potential treatment patterns for TSA. Through analysis of the significance, composition, and functions of the selected drug-target modules, we validated the feasibility and rationality of our proposed SDTP method for identifying drug treatment patterns. In summary, our novel approach used a multilayer network model to overcome the shortcomings of single-layer networks and combined the network with information on drug activity. Based on the discovered drug treatment patterns, we can predict the potential diseases that the drug can treat. That is, if a disease-related protein module has a similar structure, then the drug is likely to be a potential drug for the treatment of the disease.

Cavitation failure often occurs in centrifugal pumps, resulting in severe harm to their performance and life-span. Nowadays, it has become crucial to detect incipient cavitation ahead of cavitation failure. However, most envelope demodulation methods suffer from strong noise and repetitive impacts. This paper proposes an adaptive Autogram approach based on the Constant False Alarm Rate (CFAR). A cyclic amplitude model (CAM) is presented to reveal the cyclostationarity and autocorrelation-periodicity of pump cavitation-caused signals. The Autogram method is improved for envelope demodulation and cyclic feature extraction by introducing the character to noise ratio (CNR) and CFAR threshold. To achieve a high detection rate, CNR parameters are introduced to represent the cavitation intensity in the combined square-envelope spectrum. To maintain a low false alarm, the CFAR detector is combined with the CNR parameter to obtain adaptive thresholds for different data along with sensor positions. By carrying out various experiments of a centrifugal water pump from Status 1 to 10 at different flow rates, the proposed approach is capable of cavitation feature extraction with respect to the CAM model, and can achieve more than a 90% detection rate of incipient cavitation and maintain a 5% false alarm rate. This paper offers an alternative solution for the predictive maintenance of pump cavitation.

Neochlorogenic acid (nCGA) is a phenolic compound isolated from mulberry leaf (Morus alba L.), which possesses multiple pharmacological activities containing antioxidant and anti-inflammatory effects. However, the role of nCGA in the treatment of acute pneumonia and the underlying molecular mechanism are still unclear. Hence, the aim of study is to investigate the anti-inflammatory properties of nCGA on LPS-stimulated inflammation in A549 cells. In the present study, results reported that nCGA without cytotoxicity significantly reduced the production of TNF-α, IL-6, and NO, and further suppressed the proteins of iNOS, COX2, TNF-α, IL-6 expression. Furthermore, nCGA also inhibited NF-κB activation and blocked MAPKs signaling pathway phosphorylation. In addition, we found nCGA significantly increased the expression of HO-1 via activating the AMPK/Nrf2 signaling pathway to attenuate the inflammatory response, whereas this protective effect of nCGA was reversed by pre-treatment with compound C (C.C, an AMPK inhibitor). Therefore, all these results indicated that nCGA might act as a natural anti-inflammatory agent for the treatment of acute pneumonia.