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Device-to-device (D2D) communication enables direct data transmissions between devices, thereby filling in the blind zones of base stations (BSs) and alleviating their load pressures. In this work, we propose an adaptive single-hop and relay-selection-based double-hop D2D transmission scheme underlaying cellular networks with full-frequency reuse. When the communication distance between two D2D users is shorter than a threshold $d_{0}$, the single-hop D2D link can be established. However, when the distance between two D2D users is longer than $d_{0}$ but shorter than $2d_{0}$, and there exists at least one relay node in the overlapping coverage areas of both users, the double-hop D2D transmission is performed. Based on the stochastic geometry theory, we properly model the random distributions of D2D users, relay nodes, cellular users, and BSs, as well as the aggregate interference for each type of communication mode. We propose to divide the overlapping area of the coverage regions of two D2D users into small grids, and the relay selection priority is assigned to each grid according to the selection criterion. The griding of overlapping areas can greatly simplify the analysis of successful relaying by considering the possible locations of the selected relay. We also present two benchmark schemes, namely cellular only, cellular with D2D single-hop. Numerical results show that our proposed scheme can significantly improve the area throughput compared with the benchmark schemes.

In this letter, a wideband metantenna (MTA) based on the novel arrangement configuration of an artificial magnetic conductor (AMC) is proposed, and an ultrawideband (UWB) low-scattering beam scanning array is derived from it. The proposed multilayer AMC structure promotes the wide bandwidth of scattering cancellation. Synthesizing the different incidence angles of the linear polarized wave, the proposed MTA array can achieve the radar cross section (RCS) reduction of more than 3 dB in the range from 4 GHz to 47.5 GHz (11.9:1). The array composed of the MTA can achieve wideband (41.7%) low sidelobe copolarized radiation. Compared with the common checkerboard low-RCS MTA array, the MTA array with the optimized AMC configuration has higher aperture efficiency (77.7%) and smaller element spacing (0.8λ0), enabling beam scanning in the ±30° range.

Nonorthogonal multiple access (NOMA) can facilitate simultaneous data transmissions towards multiple users by using the superposition coding and successive interference cancelation techniques, which can greatly improve the spectrum efficiency. Cooperative relaying and space-time coding can promisingly improve the communication robustness of poor-quality links by achieving the space-diversity gain. Energy harvesting (EH) can prolong the lifetime of energy-limited terminals and make them work continuously. In order to enhance the spectrum efficiency as well as the communication quality, we enable a cluster of EH relays to assist the data transmissions from a base station (BS) to two far-users by using the Alamouti coding based cooperative NOMA strategy. The relays are capable of harvesting wireless energy from a power beacon as well as BS by using time-switching or power-splitting method. According to the energy status and the data decoding status, one relay is selected in a distributed manner according to either Max-min, Max-sum, or Random criterion. We analyze the transmission success probability and the system throughput performance. Extensive simulations are performed to compare the performance of different EH-based space-time coded cooperative NOMA with various relay selection schemes as well as the counterpart orthogonal transmission schemes.

Frequency noise of laser causes a broadening of spectral lineshape and introducing noise through external phase modulation can achieve spectrum broadening without destroying the stability of center frequency. Although the relationship between the frequency noise spectrum and lineshape has been studied, there is almost no analysis aiming at the impact on broadened lineshape for laser when phase noise is Gaussian white noise (GWN). In this paper, spectra with GWN phase modulation of different power spectral densities are numerically simulated and analyzed in frequency domain. The carrier suppression and broadening component increase with the improvement of GWN bandwidth and power. The circumstance of amplifier saturation is also taken into account. The external phase modulation system with bandwidth of 10 GHz is built based on electro-optic modulator (EOM) and tested in optical spectrum analyzer (OSA) and interferometric fiber optic gyroscope (IFOG). The intrinsic carrier with the linewidth of 0.1 pm is broadened to 44 pm. The lineshape of modulated spectra and performance of IFOG driven by modulated laser are consistent with the theory and simulation. In addition, the broadened-laser-driven IFOG realizes navigation-grade drift performance. This article provides guidance on phase modulation and spectral broadening in the field of laser.

This letter provides the design rule of the droop coefficient for the power synchronization loop (PSL) based grid-forming wind turbine (WT) considering the transient rotor speed constraints. The dynamic model for PSL-based WT is established first, and it is shown that the larger the droop coefficient, the larger the steady-state rotor speed deviation is. Accordingly, the maximum droop coefficient for ensuring the existence of equilibrium is derived. Finally, with the proper scaling of the transient rotor dynamic equation, the conservative evaluation of the maximum droop coefficient is obtained to make sure the WT does not touch the lower limit of the rotor speed during disturbance.

Thanks to its powerful ability to depict high-resolution anatomical information, magnetic resonance imaging (MRI) has become an essential non-invasive scanning technique in clinical practice. However, excessive acquisition time often leads to the degradation of image quality and psychological discomfort among subjects, hindering its further popularization. Besides reconstructing images from the undersampled protocol itself, multi-contrast MRI protocols bring promising solutions by leveraging additional morphological priors for the target modality. Nevertheless, previous multi-contrast techniques mainly adopt a simple fusion mechanism that inevitably ignores valuable knowledge. In this work, we propose a novel multi-contrast complementary information aggregation network named MCCA, aiming to exploit available complementary representations fully to reconstruct the undersampled modality. Specifically, a multi-scale feature fusion mechanism has been introduced to incorporate complementary-transferable knowledge into the target modality. Moreover, a hybrid convolution transformer block was developed to extract global-local context dependencies simultaneously, which combines the advantages of CNNs while maintaining the merits of Transformers. Compared to existing MRI reconstruction methods, the proposed method has demonstrated its superiority through extensive experiments on different datasets under different acceleration factors and undersampling patterns.

In recent years, the field of action recognition using spatio-temporal graph convolution models for human skeletal data has made significant progress. However, current methodologies tend to prioritize spatial graph convolution, which leads to an underutilization of valuable information present in skeletal data. It limits the model’s ability to effectively capture complex data patterns, especially in time-series data, ultimately impacting recognition accuracy significantly. To address the above issues, this article introduces an attention-based semantic-guided multistream graph convolution network (ASMGCN), which can extract the deep features in skeletal data more fully. Specifically, ASMGCN incorporates a novel temporal convolutional module featuring an attention mechanism and a multiscale residual network, which can dynamically adjust the weights between skeleton graphs at different time points, enabling better capture of relational features. In addition, semantic information is introduced into the loss function, enhancing the model’s ability to distinguish similar actions. Furthermore, the coordinate information of different joints within the same frame is explored to generate new relative position features known as centripetal and centrifugal streams based on the center of gravity. These features are integrated with the original position and motion features of skeleton, including joints and bones, enriching the inputs to the GCN. Experimental results on the NW-UCLA, NTU RGB + D (NTU60), and NTU RGB + D 120 (NTU120) datasets demonstrate that ASMGCN outperforms other state-of-the-art (SOTA) human action recognition (HAR) methods, signifying its potential in advancing the field of action recognition using skeletal data.

Integrating the advantages of coronary angiography (CAG) and intravascular ultrasound (IVUS) images can significantly enhance the effectiveness of diagnosing coronary artery disease. However, current techniques for aligning CAG and IVUS rely solely on the manual determination of IVUS. To address this issue, this article introduces an innovative 3-D intelligent reconstruction pipeline for coronary arteries based on CAG and IVUS. The pipeline introduces three main innovations. First, the introduction of a label-text-guided multitask network model for classification and segmentation. This model facilitates end-to-end detection of blood vessel bifurcation and vascular wall segmentation, enhancing segmentation accuracy and calculating bifurcation width information by determining the number of bifurcated blood vessel frames. Second, the proposal of an improved IVUS 3-D reconstruction algorithm that integrates dual-boundary extraction, dual-line segment patch area extraction, and the moving filter-based 3-D smoothing algorithm into the reconstruction processing flow. This method not only presents branch information in the 3-D reconstruction of blood vessels, but also highlights plaque areas, improving the visual impact of the reconstruction. Third, the introduction of a registration algorithm for key branches of blood vessels based on CAG and IVUS. This algorithm aligns CAG and IVUS using key branch information extracted from CAG, achieving intelligent alignment and reconstruction without manual intervention. Experimental results demonstrate that this algorithm effectively aligns CAG and IVUS, assisting doctors in intuitively assessing and locating vascular plaque information, thereby making a significant contribution to the auxiliary diagnosis of coronary heart disease.

Multimodal sensors, including vision sensors and wearable sensors, offer valuable complementary information for accurate recognition tasks. Nonetheless, the heterogeneity among sensor data from different modalities presents a formidable challenge in extracting robust multimodal information amidst noise. In this article, we propose an innovative approach, named semantic-aware multimodal transformer fusion decoupled knowledge distillation (SMTDKD) method, which guides video data recognition not only through the information interaction between different wearable-sensor data, but also through the information interaction between visual sensor data and wearable-sensor data, improving the robustness of the model. To preserve the temporal relationship within wearable-sensor data, the SMTDKD method converts them into 2-D image data. Furthermore, a transformer-based multimodal fusion module is designed to capture diverse feature information from distinct wearable-sensor modalities. To mitigate modality discrepancies and encourage similar semantic features, graph cross-view attention maps are constructed across various convolutional layers to facilitate feature alignment. Additionally, semantic information is exchanged among the teacher–student network, the student network, and bidirectional encoder representations from transformer (BERT)-encoded labels. To obtain more comprehensive knowledge transfer, the decoupled knowledge distillation loss is utilized, thus enhancing the generalization of the network. Experimental evaluations conducted on three multimodal datasets, namely, UTD-MHAD, Berkeley-MHAD, and MMAct, demonstrate the superior performance of the proposed SMTDKD method over the state-of-the-art action human recognition methods.

This paper investigates the large disturbance stability of single voltage source converter (VSC) connected to the infinite bus system through the transmission line. One conservative stable region is obtained via the direct method of Lyapunov. Based on the Poincaré Theorem, it is interesting to find there might exist limit cycle between the obtained stable boundary and the angle of unstable equilibrium point (UEP). Accordingly, the nonlinear damping effect on the system stability is defined, and one limit cycle exists when the positive and negative damping effect over one period is mutually balanced. A conservative existence condition of limit cycle is further derived by constructing a proper piece-wise curve to approximate one specified unstable system trajectory. The derived analytical existence condition can directly predict the limit cycle without numerical simulations. Finally, the paper also proves that the studied dynamic system has at most one limit cycle, and if it exists, it is unstable.

This letter indicates that initial transient local frequency deviation is composed of linear component and combination of $(n-1)$ electro-mechanical (EM) modes via solving the initial value problem of ordinary differential equations. It is proved that the linear component of each local frequency deviation is identical to the center of inertia (COI) frequency deviation within the first instants after disturbance. Based on this property, COI frequency and system power imbalance estimation (SPIE) can be fast obtained via least-squares fitting to extract the linear component of local frequency without remote communication. Numerical results of New England 39-bus system verify the correctness of the discovered property and the effectiveness of the proposed method.

Purpose: The Nuclear Receptor Coactivator (NCOA3, also known as SRC-3, AIB1, p/CIP, RAC3, ACTR, and TRAM1), acts as an oncogene in multiple tumors, but its biological function in thyroid cancer remains unclear. This study was designed to explore the role of NCOA3 in thyroid cancer. Methods: The study assessed NCOA3 expression in thyroid cancer and their matched non-cancerous thyroid tissues at mRNA and protein levels. Then we evaluated the effect of NCOA3 on malignant activities of thyroid cancer cells. To better understand the oncogenic role of NCOA3 in thyroid tumorigenesis, we tested the effect of NCOA3 on major proteins related to thyroid cancer. Results: Our data demonstrated that protein expression of NCOA3 was significantly upregulated in thyroid cancer tissues. NCOA3 knockdown inhibited cell proliferation and invasion, and induced cell cycle arrest and apoptosis in thyroid cancer. Conversely, ectopic expression of NCOA3 promoted cell proliferation and invasiveness in thyroid cancer. Mechanistically, NCOA3 could improve the survival and invasiveness of thyroid cancer cells through the modulation of the ErbB, AKT, ERK, and β-catenin pathways. Conclusion: Collectively, these findings suggest that NCOA3 is critical in the initiation and development of thyroid cancer, and might be a possible marker for prognosis and therapy.

Existing wind turbine (WT) control strategies realize damping support mainly by active power modulation, which may affect wind energy harvest. To improve energy efficiency and robustness, this article proposes a two-stage coordinated control of type-4 WT for damping support using the cost-effective WT resources, where the grid-forming control is applied. In the first stage, two reactive power-based dampers are designed using DC voltage synchronization control. The impacts of the dampers on stability are analytically evaluated. In this stage, the reactive power modulation, along with the partial DC capacitor energy, are jointly utilized for damping provision, while the WT is operated at maximum power point tracking (MPPT) mode. The second stage that seeks active power modulation is only activated when the DC voltage exceeds the threshold. An MPPT recovery process is further designed to eliminate the droop errors induced by the damper. The proposed scheme is validated under various contingencies compared with existing controls. Numerical results show it does not require a frequency estimator or the active power modulation for WT synchronization and grid-forming purposes; meanwhile is relatively energy-efficient and robust to provide strong damping support.

Dual-camera systems commonly employed in surveillance serve as the foundation for RGB-infrared (IR) cross-modality person re-identification (ReID). However, significant modality differences give rise to inferior performance compared to single-modality scenarios. Furthermore, most existing studies in this area rely on supervised training with meticulously labeled datasets. Labeling RGB-IR image pairs is more complex than labeling conventional image data, and deploying pretrained models on unlabeled datasets can lead to catastrophic performance degradation. In contrast to previous solutions that focus solely on cross-modality or domain adaptation issues, this article presents an end-to-end unsupervised domain adaptation (UDA) framework for the cross-modality person ReID, which can simultaneously address both of these challenges. This model employs source domain classes, target domain clusters, and unclustered instance samples for the training, maximizing the comprehensive use of the dataset. Moreover, it addresses the problem of mismatched clustering labels between the two modalities in the target domain by incorporating a label matching module that reassigns reliable clusters with labels, ensuring correspondence between different modality labels. We construct the loss function by incorporating distinctiveness loss and multiplicity loss, both of which are determined by the similarity of neighboring features in the predicted feature space and the difference between distant features. This approach enables efficient feature clustering and cluster class assignment to occur concurrently. Eight UDA cross-modality person ReID experiments are conducted on three real datasets and six synthetic datasets. The experimental results unequivocally demonstrate that the proposed model outperforms the existing state-of-the-art algorithms to a significant degree. Notably, in RegDB $\to $ RegDB_light, the Rank-1 accuracy exhibits a remarkable improvement of 8.24%.

Previous studies regards that the grid-forming (GFM) converter switches from the constant voltage control (CVC) to the current limiting control (CLC) at the point of intersection of the unsaturated and saturated power-angle curves, which might not be held in most situations. This article firstly derives the switching rule of GFM converter between two controls from the current limiting inequality. Accordingly, the conventional algebraic-variable switched model is transferred to the proposed state-variable switched model. Based on Lyapunov Theory, the stability of equilibrium points (EPs) is studied and the stable regions under two controls are further derived. In addition, one necessary stabilizing condition for the power synchronization loop based GFM (PSL-GFM) converter being locked in CLC is derived. As a result, one global stabilization on CVC is proposed by regulating the angle between the saturated current vector and d-axis. Finally, the maximum system boundary of the first swing can be obtained by placing stable equilibrium points (SEPs) under CLC on the right switching line.

The recognition performance of existing vision-based human action recognition (HAR) methods is greatly reduced in the case of low camera resolution or occlusion. Wearable sensors can provide complementary information to alleviate this problem. It is challenging to construct a robust HAR model using multimodal wearable-sensor data. In this paper, we propose a cross-Attention-based Multimodal fusion Wavelet Knowledge Distillation Network (MAWKDN) method to guide recognition from video data by acquiring complementary information from wearable sensors and reduce the noise effects through wavelet knowledge distillation, which improves the robustness of the model. A multi-attention dilated convolution kernel residual network including dilated convolution and an attention mechanism is constructed to extract features from various sensor modalities and fuse the various modal data through the cross-view attention method to acquire additional information from different modalities. To reduce the modal differences between different modalities of the teacher and student networks and acquire similar semantic knowledge, we learn the information between different modalities by constructing a graph structure of convolutional layer features, and computing the semantic preservation loss between the teacher and student networks. To reduce the influence of noise in the input data, we construct the loss of wavelet knowledge distillation, which transforms the image through the discrete wavelet transform and only retains the low frequency features to extract the useful information. The top-1 accuracy achieved on the UTD-MHAD (99.31%), Berkeley-MHAD (99.40%) and the F1-score on the MMAct (85.26% based on cross-session) dataset prove the superior performance of MAWKDN compared with the state-of-the-art HAR methods. Moreover, we demonstrate the robustness of the MAWKDN approach on the noise-added UTD-MHAD dataset.

A novel grooving method for eliminating the bending-induced collapse of hexagonal honeycombs has been proposed, which lies in determining the appropriate grooving parameters, including the grooving spacing, angle, and depth. To this end, a framework built upon the experiment-based, machine learning approach for grooving parameters prediction was presented. The continuously grooved honeycomb bending experiments with various radii, honeycomb types, and thicknesses were carried out, and then the deformation level of honeycombs at different grooving spacing was quantitatively evaluated. A criterion for determining the grooving spacing was proposed by setting an appropriate tolerance for the out-of-plane compression strength. It was found that as the curvature increases, the grooving spacing increases due to the deformation level of honeycombs being more severe at a smaller bending radius. Besides, the grooving spacing drops as the honeycomb thickness increases, and the cell size has a positive effect on the grooving spacing, while the relative density has a negative effect on the grooving spacing. Furthermore, the data-driven Gaussian Process (GP) was trained from the collected data to predict the grooving spacing efficiently. The grooving angle and depth were calculated using the geometrical relationship of honeycombs before and after bending. Finally, the grooving parameters design and verification of a honeycomb sandwich fairing part were conducted based on the proposed grooving method.

Incorporating the advantages of line commutated converters (LCCs) and voltage-source converters (VSCs), hybrid high voltage DC (HVDC) links have bright prospects in bulk power transmission. For this new technique, however, there is a risk of oscillatory instability in the DC link, and the mechanism behind the instability is still unclear. This paper derives analytical DC-side stabilizing conditions for hybrid HVDC links by using dominant frequency model reduction. The small-signal model of the LCC-VSC link is first truncated by reserving only the state variables highly relevant to the dominant mode so that the expression of the dominant oscillation frequency can be obtained. Dynamics of other state variables are reintroduced and then simplified while leaving their properties nearby the dominant frequency intact. Based on the reduced model, an analytical stability criterion is obtained, which reveals that the DC-side stability of hybrid HVDC links will deteriorate with reduced DC voltage operation, a heavy load, a small DC-link capacitor, slow inner loop dynamics, a small proportional and a large integral gain of the DC voltage regulator. In addition, simplified sufficient stabilizing conditions of hybrid HVDC links are further derived for control parameter design. Case studies validate the accuracy of dominant frequency model reduction and the derived stabilizing conditions.

In this article, it is interesting to find that the virtual synchronous generator (VSG) with sufficient damping can exhibit the global stability phenomenon, i.e., the grid-connected VSG keeps asymptotically stable irrespective of the fault clearing time. The expression of the dissipated energy induced by damping is first derived from the energy conservation law. The dissipated energy equals the damping factor $\boldsymbol{D}$ times the area in the phase plane encircled by the system trajectory and the x-axis. Accordingly, a simple approach to realizing global stabilization is proposed by tuning the damping of the grid-connected VSG. It is proved that once the constant potential energy decrement over every period is less than one minimal dissipated energy, the kinetic energy at the unstable equilibrium point (UEP) of each period drops gradually, and the global stability can be achieved. Furthermore, an equal energy surface composed by the potential energy of the UEP is constructed to estimate the minimal dissipated energy, yielding an analytical and conservative damping tuning rule of VSGs for global stability. Simulation studies based on PSCAD/EMTDC have validated the correctness of the proposed global stability condition and the effectiveness of the damping tuning method of VSGs.

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This paper proposes an improved contour-integral algorithm based on exact number counting inside the interesting region to calculate critical eigenvalues of large-scale power systems. Firstly, the difference between the eigenvalues inside and outside the region of the non-hermitian matrix is derived using trapezoidal integral. Based on this difference, a small matrix can be skillfully constructed with reasonable parameters so that the exact number of eigenvalues is precisely equal to the eigenvalue number of the small matrix whose real parts are larger than 0.5. Further, rational parameters can be adaptively adjusted to obtain exact results exploiting the minimum of eigenvalues of the constructed matrix. The exact eigenvalue number can help set the contour-integral algorithm's initial subspace. We automatically expand the space by comparing the results of each iteration with the exact number to ensure that all eigenvalues are obtained. Numerical experiments demonstrate the effectiveness and reliability of the precise number counting algorithm and the improved contour integral algorithm.

The robust stability of one single voltage source converter (VSC) connected to a bus via the line is studied in this letter. Considering arbitrary bounded perturbations from uncertainties, the perturbed system model is firstly proposed. Then, one switched system is constructed to investigate the stability of the perturbed system, and it is proved that the stability region of the switched system is the subset of that of the perturbed system. Finally, the stability region of the switched system is obtained by the inverse-time (backwards) integration starting from the unstable equilibrium point, which is also the conservative stability region of the perturbed system.

Limits of phase locked loop (PLL) are necessary to make sure the transient converter frequency bounded in a safety range. This leads to the grid-connected voltage source converter (VSC) with limits of PLL as one switched system. Stability of switched dynamic system is fully discussed in this paper. One conservative analytical stable region of the unbounded autonomous system is derived by Lyapunov method. It is proved that when bounds are touched, any trajectory of the studied switched system deviates from these bounds at two fixed switching Points. Moreover, the switched system energy is non-increasing when trajectories lie inside the derived analytical stable region. Based on these properties of switched system, it is proved that to ensure the globally asymptotically stability, the fixed switching Points should be placed inside the derived stable region of the unbounded autonomous system. Finally, stabilization method is proposed via placement of the fixed switching Points so that the globally asymptotically stability is ensured.

The stability of the grid-connected voltge source converter (VSC) with limits of phase locked loop (PLL) is investigated in this letter. The studied system is a nonlinear switched system that consists of three subsystems and a switching rule that connects switching between these subsystems. It is proved that the three subsystems share one common Lyapunov function, and the derivation of the constructed Lyapunov function for each subsystem with respect to time is negative. As a result, one conservative stability region for the studied switched system is derived, and the system can be asymptotically stable under arbitrary switching within the derived stability region. Numerical results show that implementing limits of PLL is one simple and effective approach to enhance the system stability of VSCs.

Existing sub-/super-synchronous (SSO) suppression methods for the direct-drive permanent magnet synchronous generators (D-PMSG) integrated power systems are mainly achieved by external devices or sub-synchronous resonance damping controller (SSRDC) at the converters, facing challenges of considerable control costs, complex parameters tuning, or inadaptability to various operating conditions. To address these problems, this paper proposes an adaptive SSRDC based on the phase-locked loop (PLL) for D-PMSG integrated power systems. Firstly, the PLL parameter is found critical to SSO suppression by a comprehensive sensitivity analysis on the dominant poles of the impedance closed-loop transfer function. Motivated by this finding, this paper then designs a PLL-based SSRDC, which features a simple structure, easy parameter tuning, and flexible adaptability to various operating modes. The simplicity in structure is guaranteed by the avoidance of phase compensation. Benefiting from the simple structure, only one key parameter needs to be tuned. Moreover, two principles of parameter tuning are proposed to enhance the efficiency, robustness, and adaptability of the proposed SSRDC. The controller-hardware-in-the-loop (CHIL) tests verify the validity of the proposed SSRDC under various operating conditions. Finally, some concerns about this method such as frequency estimation, computational efficiency and potential impacts on PLL are thoroughly analyzed and clarified.

Weak signal detection under strong noise is a common problem in many engineering fields. The research on the detection theory and method of stochastic resonance (SR) has very important theoretical significance and application value for the realization of early weak fault diagnosis. In order to further enhance the weak signal processing capability of SR, an improved novel composite multistable potential well model is proposed by combining the tristable model and the Woods–Saxon model. The switching mechanism of the novel model constructed with the fusion of the tristable model and the Woods–Saxon model between different steady states is studied, the output response performance of SR system with the novel composite multistable model is analyzed. The adaptive synchronization optimization method of multiple system parameters adopts the differential brainstorming algorithm to realize the adaptive selection of multiple parameters. Simulation experiments are carried out on single and multiple low-frequency periodic signals and single and multiple high-frequency periodic signals under the Gaussian noise environment, simulation results indicate that the novel composite multistable SR system performs better. On the basis of this model, the composite multistable SR system is applied to the fault detection of rolling bearings, which has a good detection effect.

As the population ages, the occurrence of diseases related to aging increases, often accompanied by comorbidities and complications affecting multiple systems. Extracting multi-target pharmacologically active compounds from natural foods with health promotion or disease prevention capabilities is an important approach to improving age-related diseases. Sesame lignans, constituting the primary bioactive compounds in sesame seeds, possess considerable nutritional and health benefits. They have been proven to have beneficial effects on improving neurodegenerative diseases, metabolic diseases, various tumors, cardiovascular diseases, and osteoporosis. However, it cannot be ignored that sesame and its products also have serious allergenicity, which can pose a threat to health. How to make rational use of sesame lignans to maximize benefits and avoid harm, is a direction that researchers need to focus on. Based on this, this review provides a systematic overview of how sesame lignans contribute to the enhancement of various age-related diseases and elucidates their associated mechanisms. It also substantiates their safety with pharmacokinetic data, with a particular focus on introducing the most recent desensitization approaches for their allergenic properties. In summary, as a component of functional foods, sesame lignans possess significant potential for advancement. The expectation is that the article will act as a beneficial resource for the creation and clinical application of novel functional foods sourced from nature.

500 °C and 800 °C served as key turning points for the properties of biochar.Bamboo age had a positive effect on thermal stability and chemical stability.There was no significant difference in properties between different parts (internodes and nodes) of bamboo.

ABSTRACTSulforaphane (SFP) treatment represses oxidative stress by activating NRF2. Meanwhile, SFP may also increase the production of nitric oxide (NO) and activate the signaling pathway of cyclic guanosine monophosphate (cGMP), which is involved in the pathogenesis of hypoxic vestibular vertigo (HVV). However, it remains unknown as whether SFP plays a therapeutic role in the treatment of HVV. A rat model of HVV was established to measure the levels of escape latency, malondialdehyde (MDA), glutathione (GSH) and superoxide dismutase (SOD) in the aorta tissues. Quantitative real-time PCR was performed to evaluate the expression of NRF2 mRNA, and Western blot and immunohistochemistry were carried out to analyze the expression of NRF2 protein. ELISA was used to examine the production of NO and cGMP. SFP treatment helped to maintain the escape latency and MDA, GSH, SOD concentrations in the brain of HVV rats, and recovered the expression of NRF2 inhibited in the brain of HVV rats. SFP treatment also elevated NO and cGMP production that was down-regulated in the brain of HVV rats. On the cellular level, SFP enhanced the expression of NRF2, reduced the concentrations of MDA, GSH and SOD, and promoted the production of NO and cGMP in a dose-dependent manner. In this study, we treated an animal model of HVV with SFP to investigate its effect on NO production and oxidative stress. Our work provided a mechanistic insight into the therapeutic effect of SFP on the treatment of HVV.

For a downlink communication system, we propose a nonorthogonal multiple access scheme with two energy harvesting relays. The base station (BS) transmits the data of both near and far users simultaneously using the superposition coding technique. Two relays alternately amplify and forward the data to the far-user. Each relay can harvest wireless energy from the signals of both the BS and the other transmitting relay, so each relay can achieve more opportunities to accumulate more energy for a higher-quality cooperative relaying. The near-user performs adaptive interference cancelation to retrieve its desired data. Numerical results show that the nonorthogonal scheme greatly outperforms the orthogonal scheme in terms of throughput.

In this paper, we proposed an improved optical heterodyne scheme based on optical carrier suppression (OCS) and optical injection locking techniques (OIL) for prospective applications in radio-over-fiber (RoF) systems to generate high-quality millimeter waves. In our scheme, the 60-Ghz millimeter wave signal is generated by heterodyning the outputs of two vertical cavity surface emitting lasers (VCSELs) that are optically injection locked by the two modulation sidebands provided by a 30-GHz externally modulated master tunable laser with suppressed center wavelength. The combined OCS and OIL heterodyne method are not only able to eliminate the phase noise caused by the instability of laser frequencies, but also can further suppress the center wavelength, thus improving the heterodyne performance. We evaluate the transmission quality of the proposed RoF system from the center station to base stations through simulation, and results prove our proposed OCS-OIL-heterodyne scheme to have error-free propagation within a distance of 40 km, better than the OCS-heterodyne scheme.

An environmentally friendly electrochemical approach for iodoamination of various indole derivatives with a series of unactivated amines, amino acid derivatives, and benzotriazoles (more than 80 examples) has been developed. This strategy was further applied in late-stage functionalization of natural products and pharmaceuticals and gram-scale synthesis and radiosynthesis of 131I-labeled compounds. Fundamental insights into the mechanism of the reaction based on control experiments, density functional theory calculation, and cyclic voltammetry are provided.

Real-time positioning feature is becoming an essential part in a variety of military and civilian applications. In particular, the cooperation of multisensors helps to improve navigation accuracy and the universality of the system. In this article, we propose a novel robust fault-tolerant federated filter based on strapdown inertial navigation system (SINS), global navigation satellite system (GNSS), celestial navigation system (CNS), and doppler velocity log (DVL). In the proposed algorithm, the position information of the GNSS, the velocity information of the DVL, and the attitude information of the CNS are introduced as measurement information to correct the divergence error of SINS. The federated filter is exploited for its flexibility and capability in fault toleration. To amend fault and recover information in local filters, a simplified state Chi-square test (SSCST) is utilized as the fault detection, isolation, and recovery procedure. Meanwhile, a new adaptive information sharing factor algorithm based on the results of SSCST and the residuals between the actual observations and the predicted observations is designed, which can adaptively reflect the performance of each local filter. Experimental results show that the accuracy of the proposed integrated navigation and positioning algorithm can be improved and the system remains stable even when the error occurs.

Reported herein is an effective strategy for oxidative cross-coupling of indoles with various aldehydes. The strategy is based on a two-step transformation via a well-known Mannich-type reaction and a C–N bond cleavage for carbonyl introduction. The key step—the C–N bond cleavage of the Mannich product—was enabled by electrochemistry. This strategy (with over 40 examples) ensures excellent functional-group tolerance as well as late-stage functionalization of pharmaceutical molecules.

INRTODUCTION :

Peptide-tuned self-assembly of macromolecular agents (>500 Da) such as therapeutic peptides offers a strategy to improve the properties and biofunctions of degradable nanomaterials, but the tough requirement of macromolecular therapeutics delivery and a lack of understanding of peptide-based self-assembly design present high barriers for their applications. Herein, we developed a new strategy for nanoengineering macromolecular drugs by an elaborate peptide, termed PSP (VVVVVHHRGDC), capable of directly conjugating with cargo to be a PSP-cargo monomer as building block tending to self-assemble into a well-defined nanoshell with tumor-triggered shape and charge switch. As a proof of concept, conjugation PSP to a D-peptide activator of tumor suppressor p53 termed DPMI (1492.5 Da) generated hollow spheres ∼80 nm in diameter named PSP-DPMI that disintegrated only in the acidic microenvironment of tumor tissues, followed by integrin-mediated cellular uptake of PSP-DPMI monomers. Importantly, PSP-based self-assembly successfully endowed the DPMI with long circulation time and high cancer-cell-specific intracellular accumulation. PSP-DPMI nanoshells potently inhibited tumor growth in vitro and in vivo by the p53 restoration, while maintaining a highly favorable in vivo safety profile. Out of conventional encapsulation and conjugation, our study showcases a clinically viable novel method to nanoengineer macromolecular agents such as peptide for anticancer therapy and provides a hazard-free alternative strategy for the theranostics delivery.

Cpf1 is a CRISPR effector protein that has greater specificity than Streptococcus pyogenes Cas9 (SpCas9) in genome-editing applications. Here we show that Lachnospiraceae bacterium (Lb) and Acidaminococus sp. (As) Cpf1 orthologs have RNase activities that can excise multiple CRISPR RNAs (crRNAs) from a single RNA polymerase II–driven RNA transcript expressed in mammalian cells. This property simplifies modification of multiple genomic targets and can be used to increase the efficiency of Cpf1-mediated editing.

For 3D sensor networks to monitor the ocean, forest and aerosphere, etc., sensors can forward their data to the base station by greedy routing. It is critical to quantitatively greedy routing’s deliverability for evaluating network’s functionality and performance. The probability that all sensors can successfully send their data to the base station by greedy routing is usually modeled as the probability of guaranteed delivery. For a typical spherical cap 3D sensor network deployment scenario where nodes follow a homogeneous Poisson point process, the relationship between the sensor transmission radius and the probability of guaranteed delivery is studied, and a tight analytical upper bound on the sensor transmission radius to ensure the designed deliverability probability is derived in this paper. The correctness and tightness of the derived upper bound are verified by extensive simulations.

The interference calculation is essential to the flight dynamic analysis especially for multi-rotors configurations. To analyze the flight dynamic characteristics of a small tandem helicopter precisely, a vortex method is utilized to obtain the aerodynamic interaction between the tandem rotors and the fuselage. Specially, the unsteady air loads and the wake of the rotors are developed using a lifting surface method and the viscous vortex particle theory, respectively, and the fuselage is modeled by the panel method to simulate the blocking effect on the rotors. Then the aerodynamic interference of the small tandem helicopter is analyzed under the conditions of different vertical or horizontal distance between the rear and front rotors. Subsequently, to save calculation time during flight dynamic analysis, a hybrid optimization trimming method combining the equilibrium optimizer and the improved delta method is proposed. At last, the flight dynamic analysis for the small tandem helicopter with different configurations are carried out and the results indicate that configuration in which the rear rotor is located higher than the front rotor and the one with larger longitudinal distance between tandem rotors are beneficial to increase the stability in lateral and longitudinal directions, respectively.

More attention has been paid to ubiquitous microplastics (MPs). As a major food producer, the situation of MPs in China’s farmland is of even greater concern. Spatial distributions, characteristics, and compositions of MPs in five types of agricultural lands with representative crops were investigated by collecting 477 soil samples from 109 cities in 31 administrative regions of mainland China. To better control MPs in farmland, nearly 400 field questionnaires were obtained, and meteorological conditions, soil properties, and other statistics were collected to quantify potential sources and determine influencing factors. The average abundances of MPs was 2462 ± 3767 items/kg in the agricultural soils, and MP abundance in the greenhouses, farmlands with film mulching, and blank farmlands from four integrated physical geographic regions were determined. The contributions of agricultural films, livestock and poultry manures, irrigation water, and air deposition to MPs in farmlands have been calculated. Influencing factors, such as recovery method, plowing frequency, meteorological conditions, and part of soil properties, were significantly correlated with the abundances of MPs in the agricultural soils (p< 0.05), while mulching age mainly affected MPs in the greenhouses (p< 0.05). This study provides basic scientific data for decision-making and further analysis.

In this paper, we introduce the Anderson acceleration technique developed to be applied to reinforcement learning tasks. We develop an accelerated value iteration algorithm referred as Anderson accelerated value iteration (A2VI) and an accelerated deep Q-learning algorithm denoted as deep Anderson accelerated Q-learning (DA2Q) algorithm. The proposed approach allows improving the performance of value iteration by interpolating historical data. We perform a theoretical analysis on linear convergence and conduct performance evaluation of the proposed algorithms, including synthetic experiments and classical control tasks. We conclude that both theoretical and empirical results confirm the effectiveness of the proposed algorithm.

Several new polymers containing hydrophilic phosphatidylcholine analogues in the main chains and hydrophobic docosyl or stearyl groups in the side chains have been synthesized. The polymers exhibit thermotropic liquid crystalline behaviors from 65°C up to ca. 280°C as determined by polarizing microscopy. One of the polymers shows slight crystallinity as evidenced by wide-angle x-ray diffraction. The viscosity measurements show that some of the polymers have properties similar to usual polyelectrolytes. However, one polymer shows a linear increase of reduced viscosity.

Several polyurethanes containing phosphatidylcholine analogues in the side chains were synthesized by reaction of oleyl-2-[N-(methyldiethanolammonium) ethyl phosphate (3a) or (p-onylphenyl)-2-[N-(methyldiethanolammonium) ethyl phosphate (3b) with diisocyanates such as 2,4-tolylene diisocyanate (TDI), 4,4'-methylene diphenyl diisocyanate (MDI), and m-xylylene diisocyanate (XDI), respectively. The new diols 3a and 3b were characterized by their IR and 1H-NMR spectral data and elemental analyses. Polyurethanes were characterized by their IR spectral data. Polyurethanes with properties similar to the usual polyelectrolytes are described.

We report the case of a 17 year-old man with a large optic disc melanocytoma that underwent spontaneous rupture and seeding of the vitreous with pigmented cells. Potential pathogenic mechanisms and visual prognosis of this rare event are discussed.

Function of autoantibodies from patients with autoimmune diseases in malignancies development is not clear yet. It has been reported that a cell-penetrating lupus autoantibody, 3E10, which was isolated from a mouse model of systemic lupus erythematosus (SLE), has been a potential targeted therapy for DNA-repair deficient malignancies. We have got four human monoclonal antinuclear antibodies from patients with autoimmune disease, 3B5, 3C1, 3E8 and 4F3. Our data showed that four antibodies could combine HEp-2 cells and display different nuclear types as antinuclear antibody (ANA). Also, these four ANAs can inhibit HEp-2 cells proliferation. We think these antibodies may be potential antibody drugs to cancer therapy. However, the function and mechanism are not clear. Further study, we want to clarify the effects of four ANAs on proliferation of various cancers cells and to investigate the mechanism of four ANAs affecting various cancers cells proliferation and their targets. This may be a new mechanism of malignancies development in patients with autoimmune diseases, and provide novel angle of autoantibody function study.