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This paper studies the distributed convex optimization of bipartite containment control problem for a class of higher order nonlinear multi-agent systems with uncertain states. For the optimization problem, the penalty function is constructed by summing the local objective function of each agent and combining the penalty term formed by the adjacency matrix. For the unknown nonlinear function and unpredictable states in the system, this paper construct radial basis function Neural-networks and state observer for approaching, respectively. In order to avoid "explosion of complexity," under the framework of Lyapunov function theory, we propose the dynamic surface control (DSC) technology and design the distributed adaptive backstepping neural network controller to ensure all the signals remain semi-global uniformly ultimately bounded in the closed-loop system and all agents can converge to the convex hull containing each boundary trajectory as well as its opposite trajectory different in sign. Simulation results confirm the feasibility of the proposed control method. [ABSTRACT FROM AUTHOR]

In the context of carbon peaking and carbon neutrality goals, the integration of a large number of renewable energy sources may trigger significant tidal changes, leading to transmission congestion, wind and light abandonment, power oscillation, voltage and frequency fluctuations, etc. A phase-shifting transformer is a cost-effective and reliable power flow control equipment, but its key parameters lack systematic design methods. Based on the equivalent model of phase-shifting transformers, detailed design principles and methods have been proposed, and the configuration method of winding turns has been improved to facilitate calculation and control strategy formulation. The regulation effect of the phase-shifting transformer designed through simulation of power flow regulation in a typical 500 kV network is simulated. By adjusting the phase-shifting transformer, the power flow of heavy load lines can be transferred to light load lines, optimizing the power flow distribution and improving the transmission capacity of the cross-section. [ABSTRACT FROM AUTHOR]

Installing a three-phase saturated core fault current limiter (TSFCL) is an effective method to limit the increasing short-circuit current in high-voltage alternating current (HVAC) systems. However, the traditional TSFCL uses silicon steels as its working material for the iron core, resulting in poor current-limiting effects, requiring a large DC excitation current, and having a slow response speed. Nanocrystalline alloys have advantages such as a lower saturation point, higher permeability in the unsaturated zone, and a steep B–H curve, making them highly suitable for TSFCL's applications. However, their poor capability which withstands fault hindered their large-scale commercialization. Therefore, this paper proposes a novel hybrid magnetic material based on TSFCL (HMTFCL), where the materials of the working limbs are replaced by nanocrystalline alloys. Compared to TSFCL, the DC excitation current of HMTFCL decreases by 60.5%. And, the HMTFCL reduces the peak short-circuit current by 23%. Last, the magnetic flux intensity inside the working limb of HMTFCL is reduced to zero more quickly. [ABSTRACT FROM AUTHOR]

Valve reactors (VR) with multiple magnetic cores are important electrical components in ultra-high voltage direct current systems. The impact current and high-order harmonics during their operation can lead to additional losses and temperature rise in the valve reactors, posing a threat to insulation aging, and even causing serious incidents such as combustion and explosions. Therefore, it is necessary to accurately quantify and analyze the loss characteristics of valve reactors under different magnetic materials. This article first theoretically analyzes the electromagnetic and temperature characteristics during the actual operation of VR; then, it analyzes and calculates the magnetic field distribution and electromagnetic losses of a single magnetic core. Finally, it establishes a three-dimensional equivalent model of VR and conducts transient electromagnetic-thermal coupled finite element simulation to reveal the magnitude and spatial distribution of VR temperature changes. [ABSTRACT FROM AUTHOR]

Developing high-performance hydrogen evolution reaction (HER) electrocatalysts working at a high current density is essential because of the increasing demand for clean and renewable hydrogen energy. Herein, we have developed Ir nanocluster-decorated macroporous NiCo foam (Ir-nc@m-NiCo) to overcome the sluggish HER kinetics for enhanced hydrogen production. Ir-nc@m-NiCo can be fabricated by a corrosion engineering method. In the mechanism of electron transfer from Ni and Co to Ir at the interface between the NiCo foam and Ir cluster, the electrons accumulated on Ir favor optimal adsorption of H* for the HER. Therefore, Ir-nc@m-NiCo exhibits excellent HER activity, reaching current densities of 500 and 1000 mA cm−2 at low overpotentials of 101 and 146 mV, respectively, in 1.0 M KOH electrolyte. Moreover, Ir-nc@m-NiCo possesses remarkable HER activity in simulated alkaline seawater electrolytes with 1000 mA cm−2 at 178 mV and demonstrates long-term durability with a slight potential increase after 10 hours testing under 500 mA cm−2. [ABSTRACT FROM AUTHOR]

This paper investigates the distributed optimization problem (DOP) for fractional high-order nonstrict-feedback multiagent systems (MASs) where each agent is multiple-input–multiple-output (MIMO) dynamic and contains uncertain dynamics. Based on the penalty-function method, the consensus constraint is eliminated and the global objective function is reconstructed. Different from the existing literatures, where the DOPs are addressed for linear MASs, this paper deals with the DOP through using radial basis function neural networks (RBFNNs) to approximate the unknown nonlinear functions for high-order MASs. To reduce transmitting and computational costs, event-triggered scheme and quantized control technology are combined to propose an adaptive backstepping neural network (NN) control protocol. By applying the Lyapunov stability theory, the optimal consensus error is proved to be bounded and all signals remain semi-global uniformly ultimately bounded. Simulation shows that all agents reach consensus and errors between agents' outputs and the optimal solution is close to zero with low computational costs. [ABSTRACT FROM AUTHOR]

Investigating the spatiotemporal variation characteristics of aerosol optical depth (AOD) and its driving factors is essential for assessing atmospheric environmental quality and alleviating air pollution. Based on a 22-year high-resolution AOD dataset, the spatiotemporal variations of AOD in mainland China and ten national urban agglomerations were explored based on the Mann–Kendall trend test and Theil–Sen median method. Random forest (RF) and multiscale geographically weighted regression (MGWR) were combined to identify the main driving factors of AOD in urban agglomerations and to reveal the spatial heterogeneity of influencing factors. The results showed that areas with high annual average AOD concentrations were mainly concentrated in the Chengdu–Chongqing, Central Plains, Shandong Peninsula, and Middle Yangtze River urban agglomerations. Southern Beijing–Tianjin–Hebei and its surrounding areas revealed the highest AOD pollution during summer, whereas the worst pollution during the remaining three seasons occurred in the Chengdu–Chongqing urban agglomeration. Temporally, except for the Ha-Chang and Mid-Southern Liaoning urban agglomerations, where the average annual AOD increased, the other urban agglomerations showed a decreasing trend. Among them, the Central Plains, Middle Yangtze River, Guanzhong Plain, and Yangtze River Delta urban agglomerations all exhibited a decline greater than 20%. According to the spatial trends, most urban agglomerations encompassed much larger areas of decreasing AOD values than areas of increasing AOD values, indicating that the air quality in most areas has recently improved. RF analysis revealed that PM2.5 was the dominant factor in most urban clusters, followed by meteorological factors. MGWR results show that the influencing factors have different spatial scale effects on AOD in urban agglomerations. The socioeconomic factors and PM2.5 showed strong spatial non-stationarity with regard to the spatial distribution of AOD. This study can provide a comprehensive understanding of AOD differences among urban agglomerations, and it has important theoretical and practical implications for improving the ecological environment and promoting sustainable development. [ABSTRACT FROM AUTHOR]

In response to the limitations of traditional double rice cropping models, this study constructed five typical rice planting models in the middle reaches of the Yangtze River, namely "Chinese milk vetch-early rice-late rice (CK/CRR), Chinese milk vetch—early rice—sweet potato || late soybean (CRI), rapeseed—early rice—late rice (RRR), rapeseed—early rice—sweet potato || late soybean (RRI) and potato—early rice—late rice (PRR)" to study the annual emission characteristics of greenhouse gases under different planting models. The results showed the following: (1) From the perspective of total yield in two years, the CRI treatment reached its maximum, which was significantly higher than that of other treatments by 9.30~20.29% in 2019 (p < 0.05); in 2020, except for the treatment of RRI, it was significantly higher than other treatments by 20.46~30.23% (p < 0.05). (2) The cumulative emission of CH4 in the double rice treatment is generally higher than that in paddy-upland rotation treatment, while the cumulative emission of N2O in the paddy-upland rotation treatment is higher than that in the double rice treatment, but the total amount is much lower than the cumulative emission of CH4. Therefore, CH4 emissions from rice fields still occupy most of the GHGs. (3) The global warming potential (GWP) and greenhouse gas emission intensity (GHGI) of different planting patterns in rice fields in 2020 were higher than those in 2019, and the GWP and GHGI of double rice cropping treatment is higher than that of paddy-upland rotation treatments. During the two years, the GWP of CRR treatment reached its maximum and was significantly higher than that of other treatments by 48.28~448.90% and 34.43~278.33% (p < 0.05). The GHGI of CRR was significantly higher than that of CRI and RRI by 3.57~5.4 and 1.4~3.5 times (p < 0.05). Based on the comprehensive performance of greenhouse gas emissions over the two experimental years, RRI and CRI have shown good emission reduction effects, which can significantly reduce greenhouse gas emissions from paddy fields, are conducive to reducing global warming potential and greenhouse gas emission intensity and conform to the development trend of "carbon neutrality". Therefore, considering high-yield, low-temperature chamber gas emissions, the Chinese milk vetch—early rice—sweet potato || late soybean model performs well and has the best comprehensive benefits. It is of great significance for optimizing the rice field planting mode in the middle reaches of the Yangtze River. [ABSTRACT FROM AUTHOR]

EDI is a hot topic in the research of multimodal transportation informatization, which determines the exchange level of intermodal transportation information. However, its high cost, large system coupling degree and low performance threshold cannot adapt to mass data exchange in high concurrent environment. Therefore, a decentralized, scalable, distributed and efficient data exchange system is formed. It plays a key role in realizing the comprehensive sharing of interdepartmental intermodal information in the cloud environment. In order to solve the problem of mismatching between application load and computing resource capacity and realize on-demand resource allocation and low carbon emission, this paper proposes to build an Extensible EDI system (XEDI) based on MSA and studies the scaling mechanism in container environment. Based on the resource scheduling characteristics of container cloud and considering the distribution and heterogeneity of intermodal cloud computing platform from the perspective of resource allocation, the automatic scaling mechanism of XEDI is established, the scaling model is established, and the automatic scaling algorithm is proposed. For Dominant Resource Fairness for XEDI (XDRF) resource allocation algorithm and Dominant Resource Fairness for XEDI (CXDRF) based on carbon considering energy consumption, the CXDRF algorithm is proved by quantitative experiments to achieve system performance optimization on the basis of ensuring system reliability and effectively reducing energy consumption. XEDI can not only meet the demand of dynamic load and improve service quality, but also reduce resource occupation and save energy by releasing virtual resources when resource utilization rate is low. It has great research significance and practical value for mass data application under low energy consumption conditions., Author(s): Qiang Huang [1]; Lin Sun [1]; Furong Jia [1]; Jiaxin Yuan [1]; Yao Wu [1]; Jinshan Pan (corresponding author) [2] 1. Introduction Multimodal transportation is recognized as the most [...]

Mitochondrial dysfunction of neurons is the core pathogenesis of incurable Parkinson's disease (PD). It is crucial to ameliorate the mitochondrial dysfunction of neurons for boosting the therapy of PD. Herein, the remarkable promotion of mitochondrial biogenesis to ameliorate mitochondrial dysfunction of neurons and improve the treatment of PD by using mitochondria‐targeted biomimetic nanoparticles, which are Cu2‐xSe‐based nanoparticles functionalized with curcumin and wrapped with DSPE‐PEG2000‐TPP‐modified macrophage membrane (denoted as CSCCT NPs), is reported. These nanoparticles can efficiently target mitochondria of damaged neurons in an inflammatory environment, and mediate the signaling pathway of NAD+/SIRT1/PGC‐1α/PPARγ/NRF1/TFAM to alleviate 1‐methyl‐4‐phenylpyridinium (MPP+)‐induced neuronal toxicity. They can reduce the mitochondrial reactive oxygen species, restore mitochondrial membrane potential (MMP), protect the integrity of mitochondrial respiratory chain, and ameliorate mitochondrial dysfunction via promoting mitochondrial biogenesis, which synergistically improve the motor disorders and anxiety behavior of 1‐methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine (MPTP)‐induced PD mice. This study demonstrates that targeting mitochondrial biogenesis to ameliorate mitochondrial dysfunction has a great potential in the treatment of PD and mitochondria‐related diseases. [ABSTRACT FROM AUTHOR]

Nonsyndromic monogenic obesity (NSMO) is a class of individual obesity that is independent of the environment and caused by a single gene mutation. It is mostly caused by mutations in LEP, LEPR, PCSK1, as well as some rare mutations in UCP3, NR0B2, and PPARG. Among 30 obesity patients, five patients are identified with positive gene detection. For the first time, the c.624C>T mutation associated with PCSK1, and the c.50G>A and c.293_301delinsAC mutations associated with NR0B2, as well as the obesity phenotype mutation (c.284A>G) associated with PPARG is confirmed. Following this, the genotype‐clinical phenotype, mutation hotspots, and mutation distributions of each gene are summarized, and the genetic characteristics of NSMO are analyzed. The locations of mutation c.50G>A, and c.284A>G are highly conserved according to the sequencing alignment. According to the findings, the c.624C>T mutation in PCSK1 is a newly discovered synonymous mutation, but it can result in significant early‐onset obesity. Additionally, the mutation of c.284A>G(PPARG) can lead to a variety of clinical phenotypes and the mutation of UCP3 and NR0B2 may increase the risk of type 2 diabetes mellitus. This study enriches the human NSMO gene mutation database and provides a scientific basis for clinically accurate diagnosis and treatment. [ABSTRACT FROM AUTHOR]

In this paper, the containment control problem of a class of fractional-order nonlinear multi-agent systems is studied, in which the multi-agent system contains unmeasured states and system nonlinearity. An adaptive neural network backstepping controller combined with event-triggered mechanism is proposed to ensure all followers can converge to the convex hull spanned by the leaders. The command filter is introduced into the proposed fractional-order control system to obtain fractional derivatives for virtual control functions continuously and avoid "explosion of complexity." From the Lyapunov stability theory, all the signals can remain semi-global uniformly ultimately bounded in the closed-loop system. Numerical example and simulation results confirm the feasibility of the proposed control method. [ABSTRACT FROM AUTHOR]

In recent years, major large ports in China have realized the business informatization of rail-water intermodal transportation. However, the overall development level of intermodal transportation informatization has been restricted to a great extent due to the unbalanced development of intermodal transportation informatization in different regions, the rigid system architecture, the low degree of information sharing, and the lack of data management and analysis methods. Combined with the structure and business characteristics of intermodal transportation information systems, adopting cloud computing and Big Data technology, we propose an intermodal transportation information process with waybill as the information carrier and FPMS as the service fulcrum in this paper. Illustrated by the example of China's container export process, this paper explores a series of key technical issues in the cloud environment, such as application management, business information sharing, and Big Data processing, at different levels of the construction of the rail water transport cloud platform, combined with its business characteristics, and makes experimental analysis on the relevant models to verify the feasibility of the reconstruction of the rail water transport cloud platform. It can provide theoretical and practical support for the development of rail water intermodal informatization in China., Author(s): Furong Jia [1]; Lin Sun [1]; Jiaxin Yuan [1]; Yongping Li [1]; Qiang Huang (corresponding author) [1] 1. Introduction At present, the information construction of railway-river transportation in China [...]

Multiple inclined hollow pipes were combined to form a self‐priming jet (SPJ) impeller. The hydrodynamic and mixing characteristics in the tank were studied by numerical simulation. The feasibility of the numerical simulation model was verified by particle distribution experiments. The results showed that the turbulence intensity and vorticity were affected by the installation height and diameter of the impeller; the mixing performance was improved with increasing diameter and installation angle. The study on the enhanced mixing mechanism showed that the self‐priming was generated in the lower part of the impeller, the flow was accelerated in the empty pipe, and the jet was generated in the upper part of the impeller. Self‐priming and jet caused multiple axial internal circulation flows in the SPJ tank. [ABSTRACT FROM AUTHOR]