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ObjectiveThe role of informal social support in fostering active aging within the context of the “silver wave” is significant. This study investigated how such support influenced the mental health of older adults, with the goal of affirming its indispensable contribution to enhancing their psychological well-being.MethodsEmploying Principal Component Analysis (PCA) to construct the informal social support variable, this study rigorously analyzed the effects and underlying mechanisms of informal social support on mental health in older adults, utilizing data from the 2018 China Longitudinal Aging Social Survey (CLASS).ResultsInformal social support exerted a substantial positive influence on the mental health of older adults, particularly among younger, non-agricultural older adult populations who preferred cohabitation with their children. This form of support significantly enhanced mental well-being by elevating life satisfaction, improving access to medical services, and fostering active social engagement.ConclusionThis study elucidates the role of informal social support in bolstering the mental health of older adults. Future efforts should focus on fostering a supportive environment that enhances older adult care experiences, reforming the healthcare system to better meet the needs of the aging population, and promoting avenues for social engagement, thereby achieving a balanced integration of their emotional and physical care.

Laser powder bed fusion (L-PBF) has been proposed as a potential manufacturing process of high-entropy alloys involving rapid cooling rate and compositional element tuning. It, to some extent, compensates for the lack of strength of face-centered cubic (FCC) CoCrFeNi alloy by introducing high-density dislocations and generating hierarchical structures. In this study, the CoCrFeNi-based alloy was manufactured by L-PBF with the minor addition of B4C micro-particles and their properties and microstructure were evaluated. Nano-sized precipitates consisting of the boride and varying carbides were found in the form of a core-shell structure. An in-site transformation of carbides appeared around the core of the precipitate due to a large temperature gradient in the melt pool during manufacturing. The tensile yield and ultimate strength of CoCrFeNi–B4C alloy (1249.5 MPa and 1421.0 MPa) are double that of CoCrFeNi matrix (624.5 MPa and 691.1 MPa) at room temperature with competitive ductility. The exceptional mechanical properties can be mainly ascribed to precipitate hardening, dislocation hardening and grain refinement, as well as the particle-dislocation interaction.

This paper investigates the average peak age-of-information (APAoI) in a cooperative wireless sensor network (WSN), which deploys non-orthogonal multiple access (NOMA) and simultaneous wireless information and power transfer (SWIPT) techniques. To assist the poor source–destination direct link, the relay can utilize the harvested energy to decode the superposition-coded signal sent by the source and send its decoded information to the remote destination. With the aim of minimizing APAoI for long-term transmission, we formulate an energy allocation policy problem to trade off rate, energy, and time under certain constraints. To overcome the difficulties caused by time-varying parameters and non-convexity constraints, we perform a quasi-static transformation to obtain a simplified optimization model and some energy allocation criteria. Based on this work, we propose a heuristic APAoI real-time adaptive optimization (APRAO) algorithm that decomposes the original problem into multiple sub-problems for each transmission. During the sub-problem solving process, we introduce the static energy allocation criteria, which let the obtained solutions help our APRAO algorithm track the optimal solution as the transmission number increases. Finally, we evaluate and verify the performance of the proposed algorithm through numerical experiments.

Dislocation is the primary carrier for accommodating plastic deformation in metals. It is generally envisaged that metals with low initial dislocation density have high strain-to-failure and good formability, and vice versa. However, contrary to most metals, body-centered-cubic pure tungsten becomes brittle after reducing its dislocation density by recrystallization, while its formability increases after heavy deformation. To elucidate the mechanism of this counterintuitive mechanical behavior, by combining ex-situ indentation tests and dislocation reconstruction techniques, we find that tungsten’s deformation and failure processes are accompanied by the formation of a specific dislocation pattern. Dislocation networks are governed by a mechanism similar to the weaving process of the spider’s orb web. After heavy deformation, subgrains are generated due to the weaving process. The recurring weaving of dislocations reduces the mean free path for crack propagation, which is considered as the main reason for the increased formability of tungsten after deformation.

Intensive vegetable production has been characterized by high nitrogen (N) fertilizer input in southwest China. Optimizing the N fertilizer rate is the basis for the optimal management of regional N fertilizer. A two-year field experiment with five N fertilizer rates was conducted during 2019–2021 in southwest China, and the aim of this study was to identify the effects of different N application rates on yield, dry matter biomass (DMB), N uptake, N use efficiency (NUE) and soil mineral N (Nmin) residues for Chinese cabbage (Brassica chinensis L.) and further determine the critical plant N concentration and root-zone soil Nmin residues required to reach the maximum DMB of Chinese cabbage. Five N treatments were established: control without N input (CK); optimal N fertilizer rate decreased by 30% (70% OPT, 175 kg N ha−1), optimized N fertilizer rate (OPT, 250 kg N ha−1), optimal N fertilizer rate increased by 30% (130% OPT, 325 kg N ha−1) and farmers’ N fertilizer practice (FP, 450 kg N ha−1). The N source in all treatments was conventional urea (N ≥ 46.2%). The results showed that the total yield of Chinese cabbage followed a “linear-plateau” trend with an increasing N fertilizer rate. There was no significant difference in yield between the OPT, 130% OPT and FP treatments. The aboveground plant DMB and N uptake showed a ‘slow-fast-slow’ pattern with the growth period. There was no significant difference in aboveground plant DMB and N uptake between the OPT, 130% OPT and FP treatments. Moreover, the OPT treatment significantly increased the aboveground plant DMB and N accumulation by 29.6% and 40.5%, respectively, compared with the 70% OPT treatment. The OPT treatment significantly increased the NUE by 23.8%, 31.2% and 43.1% compared with that in the 70% OPT, 130% OPT and FP treatments, respectively. The linear-plateau model provided the best fit for the relationship among aboveground DMB of Chinese cabbage, plant N concentration and root-zone soil Nmin content. The critical root-zone soil Nmin and plant N concentrations were 94.1, 63.4 and 68.3 kg ha−1 and 34.4, 33.5 and 32.9 g kg−1 during the rosette, heading and harvest periods, respectively. In summary, compared to the FP treatment, the optimized N fertilizer rate (250 kg N ha−1) could significantly reduce the N application rate, maintain yield, increase aboveground plant DMB and N uptake, and improve NUE. Moreover, the study has great significance for guiding the green utilization of vegetable N fertilizer in southwest China.

Intra‐abdominal hypertension (IAH) has gained increasing attention worldwide because of its prevalence and high mortality rate among intensive care unit (ICU) patients. Most current approaches of measuring intra‐abdominal pressure (IAP) involve the use of sensors inside or attached to the body, which may, however, make daily monitoring inconvenient. This paper proposes a noninvasive and contactless system to learn the relationship between the passive mechanical behavior of the abdominal wall with millimeter‐wave (mm‐wave) frequency‐modulated continuous wave (FMCW) radar and an IAP sensor via a deep learning approach. We correlated the IAP variance with the mobility measures of the abdominal wall and proposed Pearson‐coefficient‐guided domain adversarial neural network (PCG‐DANN) to learn the mapping relationship. To validate the efficacy of our proposed method, a stable intra‐abdominal hypertension/abdominal compartment syndrome (IAH/ACS) model using swine was established to evaluate the mobility of the abdominal wall under different intra‐abdominal pressures with multichannel mm‐wave FMCW radar. The superiority of the proposed method is demonstrated by comparing with other neural network structures and mostly adopted sensor‐based methods. These preliminary results confirm that the new methodology for evaluating IAP nonlinearity is promising and that it can serve as an important diagnostic and treatment reference for patients with IAH.

Conductor galloping seriously threatens the safe operation of power systems and may lead to various damages such as wire fractures or tower collapses and large-scale grid breakdowns. Real-time galloping data are important in the mechanism and effect analysis of conductor dancing prevention; moreover, they are critical for verifying anti-galloping designs and developing galloping prevention plans. However, owing to the limitations of using sensors on cables, obtaining complete galloping data is an ill-posed and challenging problem. In this study, a novel curve reconstruction method using a conditional generative adversarial network (GAN), CR-CGAN, is proposed for fully synthesizing transmission line galloping curves. We use the modeling capabilities of the recently introduced GAN by imposing additional constraints to achieve full reconstruction of the galloping curves. Moreover, we introduce a novel design in the generator-discriminator pair for improved results and a new refined loss function to enhance details. The generator uses an autoencoder with skip connections, and the inception module is used to capture different scales of spatiotemporal correlation. The discriminator is designed to use global information to determine the reliability and smoothness of the reconstructed curve. The refined loss function is aimed at reducing artifacts introduced by the GAN and ensures better reconstruction quality. A single-degree-of-freedom model is constructed to verify the effectiveness and feasibility of the proposed method. Simulation results demonstrate that the proposed method can accurately reconstruct galloping curves with limited use of sensors, thus meeting the energy efficiency demands of the monitoring system.

In this paper, a co-caliber structure for dual-polarized dual-band (DPDB) radiation is presented through cross-polarized modes manipulation. After introducing slots and a connection branch into a typical patch antenna, two orthogonal radiation modes with different electrical-length achieved a meandered current mode at the lower frequency and a patch radiation mode at the higher frequency. The radiation patterns at both frequencies are patch-like, benefitting from certain feeding designs. The dual frequencies can be manipulated independently since their working modes are independent. In addition, compared with the traditional patch, the proposed antenna performs a higher aperture efficiency with a miniaturized antenna dimension. The antenna is finally fabricated and measured. The measured results showed that the antenna is evidently cross-polarized working at 10.38 GHz and 14.2 GHz and the gains are 5.57 dB and 6.82 dB, respectively. With the advantages of being compact, easily fabricated, and integrated, the proposed antenna can be potentially utilized in antenna research, polarization manipulation, multichannel communication system, and so on.

Person re-identification (re-ID) is an important and challenging topic in video surveillance and public security. Re-ID aims to retrieve persons from different cameras. Despite the developments in recent years, re-ID still faces many challenges due to different camera views, changeable person posture, complex background, and occlusion. To exploit more discriminative image similarity descriptor, we propose a novel method in this paper. First, we design a body partition extraction network to extract three body regions with efficient alignment. Second, we propose a multi-stream contribution framework to fuse feature distance with different contributions and generate the final image similarity descriptor. In addition, we combine re-ID and semantic segmentation. A mask feature is introduced to the proposed framework and we design a contribution feedback module to generate contribution coefficients dynamically. Third, in order to improve re-ID performance, we propose a fragment learning method to optimize the contribution feedback module. Fourth and last, we propose a k-distribution re-ranking strategy to further improve performance. Our method achieves competitive results on two popular datasets, CUHK03, and Market1501, with rank-1 accuracy of 93.5% and 85.7%. The proposed re-ranking method achieves 2.3% and 2.8% performance boost. The data demonstrate the effectiveness of the proposed multi-stream contribution framework and the k-distribution re-ranking strategy.

We present theoretical studies for the third-order elastic constants of Mg, Be, Ti, Zn, Zr, and Cd with a hexagonal-close-packed (HCP) structure. The method of homogeneous deformation combined with first-principles total-energy calculations is employed. The deformation gradient Fij is applied to the crystal lattice vectors ri, and the elastic strain energy can be obtained from the first-principles calculation. The second- and third-order elastic constants are extracted by a polynomial fit to the calculated energy-strain results. In order to assure the accuracy of our method, we calculated the complete set of the equilibrium lattice parameters and second-order elastic constants for Mg, Be, Ti, Zn, Zr, and Cd, and our results provide better agreement with the previous calculated and experimental values. Besides, we have calculated the pressure derivatives of SOECs related to third-order elastic constants, and high-pressure effects on elastic anisotropy, ductile-to-brittle criterion, and Vickers hardness are also investigated. The results show that the hardness model Hv=1.877k2G0.585 is more appropriate than Hv=2k2G0.585−3 for HCP metals under high pressure.

Satellite communication is expected to play a vital role in realizing Internet of Remote Things (IoRT) applications. This article considers an intelligent reflecting surface (IRS)-assisted downlink low Earth orbit (LEO) satellite communication network, where IRS provides additional reflective links to enhance the intended signal power. We aim to maximize the sum-rate of all the terrestrial users by jointly optimizing the satellite’s precoding matrix and IRS’s phase shifts. However, it is difficult to directly acquire the instantaneous channel state information (CSI) and optimal phase shifts of IRS due to the high mobility of LEO and the passive nature of reflective elements. Moreover, most conventional solution algorithms suffer from high computational complexity and are not applicable to these dynamic scenarios. A robust beamforming design based on graph attention networks (RBF-GAT) is proposed to establish a direct mapping from the received pilots and dynamic network topology to the satellite and IRS’s beamforming, which is trained offline using the unsupervised learning approach. The simulation results corroborate that the proposed RBF-GAT approach can achieve more than 95% of the performance provided by the upper bound with low complexity.

With the development of modern industry and scientific technology, production equipment plays an increasingly important role in military and industrial production, and the fault detection signal of gears and bearings state in transmission equipment becomes very important. Therefore, this paper proposes a gear-bearing composite fault signal decomposition and reconstruction method, which combines the marine predator algorithm (MPA) and variational mode decomposition (VMD) technologies. For the parameters’ selection of VMD, the optimization algorithm allows us to quickly and accurately obtain the results with the best kurtosis correlation index after signal decomposition and reconstruction. The experiments demonstrate the excellent performance of our method in the field of separation and denoising mixed gear-bearing fault signals.

In this paper, a reconfigurable sensing platform based on an asymmetrical metal-insulator-metal stacked structure integrating an indium tin oxide (ITO) ultrathin film is proposed and investigated numerically. The epsilon-near-zero (ENZ) mode and antisymmetric mode can be resonantly excited, generating near-perfect absorption of over 99.7% at 1144 and 1404 nm, respectively. The absorptivity for the ENZ mode can be modulated from 90.2% to 98.0% by varying the ENZ wavelength of ITO by applying different voltages. To obtain a highly sensitive biosensor, we show that the proposed structure has a full-width at half-maximum (FWHM) of 8.65 nm and a figure-of-merit (FOM) of 24.7 with a sensitivity of 213.3 nm/RI (refractive index) for the glucose solution. Our proposed device has potential for developing tunable biosensors for real-time health monitoring.

Herein, we propose an approach for sensitivity improvement of dual-axis strain sensing using the property of a metasurface (MS) that the phase response shifts sharply with the MS deformation. A feasible approach for phase measurement is first demonstrated by calculating multi-polarized reception when the incident electromagnetic (EM) wave has anisotropic phase values. A flexible MS consisting of periodically arranged lantern-shaped elements is designed and fabricated for dual-axis strain sensing and evaluation based on the proposed method. The simulation and measurement results demonstrated a high sensitivity of the proposed MS for strain sensing in the microwave band. The method can be used potentially in both pressure and tensile sensing. Moreover, the operational frequency can be extended to the THz range and even to the optical band.

This paper presents a novel compact dual-band and dual-polarized complementary split-ring resonator (CSRR)-fed substrate-integrated waveguide (SIW) cavity-backed fractal patch antenna for wireless energy harvesting and communication. The proposed antenna is composed of a Giuseppe Peano fractal radiation patch with a backed SIW cavity. To enhance the bandwidth and minimize the dimensions, the CSRR structure is designed to feed the Giuseppe Peano fractal patch orthogonally. A prototype of the proposed antenna is simulated, fabricated and measured. The proposed antenna exhibits good directionality and high cross-polarization level with especially compact size.

A novel dual‐band bandpass filter (BPF) based on a single triple‐mode ring resonator is proposed. The proposed BPF could provide three transmission poles for each passband to improve operating bandwidth. Meanwhile, seven transmission zeros are achieved at the stopband to improve the selectivity. The proposed dual‐band BPF was designed, fabricated and tested. The measured results are in good agreement with the simulated values.

A high performance metamaterial device for electromagnetic energy harvesting is presented. The unit cell of the metamaterial device consists of four identical omega ring resonators arranged in rotational symmetry, and each omega ring is loaded with a 50 Ω resistor that mimics the input impedance of a rectifier circuit. A proof-of-concept prototype is designed for operation at the frequency of 5.8 GHz. Here, the efficient energy harvesting is validated by the energy dissipated in each resistor. Based on the full absorption concept, the metamaterial device achieves a harvesting efficiency up to 93.1% under normal incidence. In addition, the energy harvester shows polarization independent and wide-angle incident frequency responses with good harvesting characteristics over the entire operating range. The surface current distribution is analyzed to gain an insight into the energy harvesting mechanism. Moreover, the harvester prototype is manufactured and measured, and the simulated and measured results are in good agreement. Due to the enhanced electromagnetic energy harvesting efficiency, the proposed device is a good candidate for microwave power transmission.

The triboelectric nanogenerator (TENG) and its application as a sensor is a popular research subject. There is demand for self-powered, flexible sensors with high sensitivity and high power-output for the next generation of consumer electronics. In this study, a 300 mm × 300 mm carbon nanotube (CNT)-doped porous PDMS film was successfully fabricated wherein the CNT influenced the micropore structure. A self-powered TENG tactile sensor was established according to triboelectric theory. The CNT-doped porous TENG showed a voltage output seven times higher than undoped porous TENG and 16 times higher than TENG with pure PDMS, respectively. The TENG successfully acquired human motion signals, breath signals, and heartbeat signals during a sleep monitoring experiment. The results presented here may provide an effective approach for fabricating large-scale and low-cost flexible TENG sensors.

In this paper, the problem of two-dimensional (2D) direction-of-arrival (DOA) estimation with parallel linear arrays is addressed. Two array manifold matching (AMM) approaches, in this work, are developed for the incoherent and coherent signals, respectively. The proposed AMM methods estimate the azimuth angle only with the assumption that the elevation angles are known or estimated. The proposed methods are time efficient since they do not require eigenvalue decomposition (EVD) or peak searching. In addition, the complexity analysis shows the proposed AMM approaches have lower computational complexity than many current state-of-the-art algorithms. The estimated azimuth angles produced by the AMM approaches are automatically paired with the elevation angles. More importantly, for estimating the azimuth angles of coherent signals, the aperture loss issue is avoided since a decorrelation procedure is not required for the proposed AMM method. Numerical studies demonstrate the effectiveness of the proposed approaches.