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Zero velocity detection is a critical component in zero velocity update (ZUPT)-aided foot-mounted pedestrian navigation systems. Robust and accurate zero velocity detection significantly enhances the precision of pedestrian trajectory estimation. Existing zero velocity detectors based on fixed threshold and gait cycle segmentation techniques struggle to adapt to the complexity and variability of human motion. To address this issue, we propose an adaptive zero velocity detector based on deep learning. The raw inertial data possess spatial features with significant differences and temporal features that conform to certain patterns. This detector utilizes a contrastive learning (CL) network and a long short-term memory (LSTM) neural network (NN) to extract the spatial and temporal features of the inertial data, respectively. Experimental results demonstrate that the detector can achieve adaptive zero velocity detection and improve trajectory estimation accuracy regardless of individual differences or motion types. In two indoor experiments, the 2-D position error is 0.410 m for a mixed walking and running path, and the 3-D position error is 0.546 m for a mixed walking, running, and up/down stairs path.

MgCl2–KCl mixed salts have been identified as promising thermal energy storage (TES) media and heat transfer fluids (HTF) for concentrated solar power (CSP) systems and other energy storage applications. A comprehensive understanding of the ionic structure of these mixed salts is essential to elucidate the relationship between their structural arrangements and thermophysical properties. In this study, 35Cl solid-state NMR spectroscopy was employed to provide detailed insights into the local structure of MgCl2–KCl mixed salts. By analyzing the quadrupolar interactions of the coordinated Cl–ions, specifically quadrupolar coupling constant (CQ) and asymmetry parameter (η), the disruption of symmetry and the coordination of Cl–ions were characterized. The study confirmed a structural transformation from KCl to K2MgCl4, KMgCl3, and MgCl2phases as the concentration of MgCl2increased, resulting in changes of Cl–ionic coordination from 6-fold to 5-fold or 4-fold geometries. Such structural coordination changes will influence the lattice vibrational modes, and thus altering the thermophysical properties, such as heat capacity. These results offer a deeper understanding of the ionic structure and structural evolution of MgCl2–KCl mixed salts. Furthermore, the results highlight the utility of 35Cl NMR spectroscopy as a powerful tool for investigating the microstructure and structural evolution of solid eutectic salts.

This paper presents an efficient and risk-aware search-optimization hierarchical trajectory planning method for automated vehicles in different road structures. The proposed approach incorporates a time-series motion risk field, capturing diverse road structures through a spatiotemporal map. Then, an adaptive motion primitive is developed, dynamically adjusting action time windows based on evolving risk and expected deviation during the search process. This enables efficient and accurate initial trajectory generation. Additionally, a bilevel corridor is introduced to extract the drivable area and re-represent the risk field, enabling trajectory smoothing to consider motion risk without resorting to non-convex optimization methods. Simulation results in structured and unstructured scenarios demonstrate that the proposed method improves efficiency, flexibility, and optimization quality compared to fixed-step search and single-level corridor-based optimization approaches. Real-world experiments on autonomous vehicles validated the dynamic characteristics and effectiveness of the proposed method in the actual environment.

As an important component of land transportation systems, tracked vehicles (TRVs) and wheeled vehicles (WVs) have developed independently in parallel, particularly in the modeling of vehicle-ground interactions. However, their differences are not as significant as they appear. This paper introduces a simplified terramechanics-based track-ground interaction model for the motion control of TRVs on firm ground. The simplified interaction model addresses the problem that the terramechanics-based models are too complex to be applied to optimization-based real-time control algorithms. Interestingly, the proposed track-ground interaction model closely resembles to the tire model used for WVs. Through comparison, we present the unified mechanisms underlying vehicle-ground interactions. In our approach, TRVs can be treated as a special type of skid-steer WV, which benefits the theories and methods of wheel vehicles to be deployed in the TRV domain. Finally, we verify the proposed interaction model with extensive dynamic data from a real dual motor-driven TRV to demonstrate its effectiveness.

This article presents a 17.7–20.2 GHz eight-element four-beam RF-beamforming transmitter in 65-nm CMOS for satellite communication (SATCOM). The transmitter utilizes an analog scheme in the variable-gain amplifier (VGA) to achieve dB-in-linear gain control with a high dynamic range (DR), together with a current combining crossbar for a compact footprint. The vector-modulation-based (VM-based) phase shifter (PS) adopts the cancellation-based $G_{\mathrm {m}}$ units for low switching variation. Furthermore, eight PSs of each beam are split into two groups, with each group sharing the same tunable I/Q generator for low power consumption. Considering the increased peak-to-average power ratio (PAPR) caused by high-order modulation schemes and multibeam operation, the transmitter incorporates compact transformer-based Doherty power amplifiers (DPAs) with adaptive bias control to improve the power efficiency at back-off. The chip achieves a 31-dB gain-tuning range with a 0.283-dB step and a 360° phase-shifting range with a calibrated 7-bit resolution. The measured root-mean-square (RMS) phase/gain errors induced by the VGA/PS are below 2.05°/0.147 dB, respectively, which decouples phase/gain control. The transmitter achieves a maximum output 1-dB gain compression point (OP $_{\mathrm {1 dB}}$ ) of 17.9 dBm and a maximum saturated power ( $P_{\mathrm {sat}}$ ) of 18.9 dBm. The output element exhibits 29.3% drain efficiency (DE) at 6-dB power back off (PBO) from $P_{\mathrm {sat}}$ , which is 1.56/3.12 times over the normalized class-B/class-A implementations, demonstrating Doherty PBO efficiency enhancement. The chip occupies an area of $8.59\times 4.17$ mm2 and consumes 398 mW per element at OP $_{\mathrm {1~dB}}$ . Additionally, a 16-element linear array has been developed to showcase the capabilities of the multibeam operation and gain tapering.

Most existing methods that cope with noisy labels usually assume that the classwise data distributions are well balanced. They are difficult to deal with the practical scenarios where training samples have imbalanced distributions, since they are not able to differentiate noisy samples from tail classes’ clean samples. This article makes an early effort to tackle the image classification task in which the provided labels are noisy and have a long-tailed distribution. To deal with this problem, we propose a new learning paradigm which can screen out noisy samples by matching between inferences on weak and strong data augmentations. A leave-noise-out regularization (LNOR) is further introduced to eliminate the effect of the recognized noisy samples. Besides, we propose a prediction penalty based on the online classwise confidence levels to avoid the bias toward easy classes which are dominated by head classes. Extensive experiments on five datasets including CIFAR-10, CIFAR-100, MNIST, FashionMNIST, and Clothing1M demonstrate that the proposed method outperforms the existing algorithms for learning with long-tailed distribution and label noise.

Phytophthora infestans-induced potato late blight is considered the “cancer of the potato crop.” In this work, mesoporous silica nanoparticles (MSNs) with ultrahigh specific surface area (786.28 m2/g) were synthesized, which significantly inhibited P. infestanscompared with some commercial fungicides. Moreover, MSNs inhibited the growth and reproductive of P. infestansprocesses, including germination, sporangia infection, and zoospore release. MSNs targeted key biological pathways and induced a stress response in the P. infestans, leading to reactive oxygen species (•O2–, •OH, and 1O2) production and structural damage of sporangia. Pot experiments showed that MSNs are translocated from leaves to roots of potato plants, enhancing physiological and biochemical processes, alleviating drought stress, improving resistance to pathogens, and exhibiting soil microbe-friendly. This study systematically reveals the mechanism of MSNs to weaken the reproduction process of P. infestansand confirm the safety and feasibility of MSNs as a green and sustainable fungicide.

Extracellular vesicles (EVs) are cell-derived membrane-bound particles with molecular cargo reflective of their cell of origin. Analysis of disease-related EVs and associated cargo from biofluids is a promising tool for disease management. To facilitate the analysis of intravesicular molecules, EV lysis is needed. Moreover, highly sensitive and multiplexed detection methods are required to achieve early diagnostics. While cell lysis approaches have been well studied, the analysis of EV lysis methods and their effects on downstream molecular detection is lacking. In this work, we analyzed chemical, thermal, and mechanical EV lysis methods and determined their efficiency based on EV particle concentration and immunoassay activity. We, for the first time, discovered that vortex was an efficient EV lysis method and used it for detection of surface and intravesicular markers in a highly sensitive multiplexed reverse phase immunoassay on a gold-nanoparticle-embedded membrane. In phosphate-buffered saline, detection limits up to 3 orders of magnitude lower than enzyme-linked immunosorbent assay were achieved. In spiked human plasma, detection limits as low as 7.27 × 104EVs/mL were achieved, making it suitable for early diagnostics. These results demonstrated an effective pipeline for lysing and molecular analysis of EVs from complex biofluids, paving the way for their broad applications in biomedicine.

Maize chlorotic mottle virus (MCMV) is one of the main viruses causing significant losses in maize. N6-methyladenosine (m6A) RNA modification has been proven to play important regulatory roles in plant development and stress response. In this study, we found that MCMV infection significantly up-regulated the m6A level in maize, and methylated RNA immunoprecipitation sequencing (MeRIP-seq) and RNA sequencing (RNA-seq) were performed to investigate the distribution of m6A modified peaks and gene expression patterns in MCMV-infected maize plants. The results showed that 1325 differentially methylated genes (DMGs) and 47 differentially methylated and expressed genes (DMEGs) were identified and analyzed. Moreover, the results of virus-induced gene silencing (VIGS) assays showed that ZmECT18and ZmGST31were required for MCMV infection, while silencing of ZmMTC, ZmSCI1or ZmTIP1significantly promoted MCMV infection in maize. Our findings provided novel insights into the regulatory roles of m6A modification in maize response to MCMV infection.

The use of a bipolar membrane (BPM) in a hybrid acid/alkali electrolyzer is widely considered as a promising energy technology for efficient hydrogen production. The stability of a BPM is often believed to be largely limited by the anion exchange layer (AEL) due to the hydrophilic attack of AEL polymers by hydroxide groups in alkaline. In this study, we employ X-ray computed tomography (CT) to investigate the degradation behaviors of BPM and found that the cation exchange layer (CEL) experiences more pronounced degradation compared with the AEL during water splitting operations. Despite its chemical stability in both acidic and alkaline environments, the CEL is more prone to electrochemical corrosion under the influence of applied voltages. This susceptibility leads to the formation of micropores and a consequent increase in the porosity. The results of this work provide a new perspective on and highlight the complexity of the degradation behaviors of BPMs in hybrid acid/alkali electrolyzers.

This article conducts the issue of event-triggered reduced-order filtering for continuous-time semi-Markov jump systems with imperfect measurements as well as randomly occurring uncertainties (ROUs). Specifically, the sojourn-time-dependent transition probability matrix (TPM) is presumed to be polytopic and a quantizer is introduced to quantize output signals aiming to reflect the reality. Both ROUs and sensor failures are generated by individual random variables belonging to be mutually independent Bernoulli-distributed white sequences. First, sufficient conditions for the existence of the event-triggered reduced-order filter are obtained by utilizing the dissipativity-based technique to ensure the asymptotical stability with a strictly dissipative performance of the filtering error system. The time-varying TPM is then fractionalized, which enhances the results as stated. Furthermore, the required reduced-order filter parameters are obtained by introducing slack symmetric matrix as well as cone complementarity linearization algorithm. The effectiveness of the suggested event-triggered reduced-order filter design method is shown through simulation results.

In this paper, three new iridium(III) complexes: [Ir(piq)2(DFIPP)]PF6(piq = deprotonated 1-phenylisoquinoline, DFIPP = 3,4-difluoro-2-(1H-imidazo[4,5-f][1,10]phenenthrolin-2-yl)phenol, 3a), [Ir(bzq)2(DFIPP)]PF6(bzq = deprotonated benzo[h]quinoline, 3b), and [Ir(ppy)2(DFIPP)]PF6(ppy = deprotonated 1-phenylpyridine, 3c), were synthesized and characterized. The complexes were found to be nontoxic to tumor cells via 3-(4,5-dimethylthiazole-2-yl)-diphenyltetrazolium bromide (MTT) assay. Surprisingly, its liposome-entrapped complexes 3alip, 3blip, and 3clip on B16 cells showed strong cytotoxicity (IC50= 13.6 ± 2.8, 9.6 ± 1.1, and 18.9 ± 2.1 μM). Entry of 3alip, 3blip, and 3clip into B16 cells decreases mitochondrial membrane potential, regulates Bcl-2 family proteins, releases cytochrome c, triggers caspase family cascade reaction, and induces apoptosis. In addition, we also found that 3alip, 3blip, and 3clip triggered ferroptosis and autophagy. In vivo studies demonstrated that 3blip inhibited melanoma growth in C57 mice with a high inhibitory rate of 83.95%, and no organic damage was found in C57 mice.

To fulfil the demands of rapid proliferation, tumour cells undergo significant metabolic alterations. Suppression of hyperactivated metabolism has been proven to counteract tumour growth. However, whether the reactivation of downregulated metabolic pathways has therapeutic effects remains unexplored. Here we report a nutrient-based metabolic reactivation strategy for effective melanoma treatment. l-Tyrosine–oleylamine nanomicelles (MTyr–OANPs) were constructed for targeted supplementation of tyrosine to reactivate melanogenesis in melanoma cells. We found that reactivation of melanogenesis using MTyr–OANPs significantly impeded the proliferation of melanoma cells, primarily through the inhibition of glycolysis. Furthermore, leveraging melanin as a natural photothermal reagent for photothermal therapy, we demonstrated the complete eradication of tumours in B16F10 melanoma-bearing mice through treatment with MTyr–OANPs and photothermal therapy. Our strategy for metabolism activation-based tumour treatment suggests specific nutrients as potent activators of metabolic pathways.

The absorption-saturated carbon materials and waste template agent may cause secondary pollution to the environment, if it was treated inappropriately. To avoid the potential environmental risk, the regeneration of adsorption-saturated carbon materials and template agent were investigated. Thermal regeneration and solvent regeneration methods were both employed in regeneration of absorption-saturated carbon. Results showed that the thermal-regenerated carbon outperformed solvent-regenerated carbon. The maximum adsorption value (453.5 mg/g) of Congo red was obtained at the regeneration temperature of 400°C, slightly higher than the maximum value of 443.5 mg/g obtained in solvent regeneration. In the aspect of template agent regeneration, regenerated calcium citrate was obtained by acid washing of the waste template agent and precipitation crystallization of calcium ions. The best condition was achieved at a crystallization temperature of 80°C and a droplet rate of 0.4 mL/min. Porous carbon prepared by the optimal regenerated template agent showed a maximum adsorption capacity of 429.5 mg/g, which is still acceptable for Congo red adsorption. Its removal ratio remained above 78.4% after four cycles. The results of this study realized the regeneration of absorption-saturated carbon materials and calcium citrate, avoids the environmental pollution caused by the preparation and usage of porous carbon.

Enhancing field emission in ultrascaled electronics improves the device performance and energy efficiency. Conventional lithography defines electrodes with a few-nanometer spacing on the cost of strengthened electron scattering and the reduced field enhancement factor, thus presenting challenges to enhance field emission at a small bias. Here, we used self-assembled nanorods with sub-5 nm spacing as electrodes to overcome these challenges. Intrinsic ballistic transport through high-crystallinity solution-synthesized nanorods minimized charge scattering; meanwhile ultrascaled anisotropic morphologies concentrated local electric fields and thereby lowered the barrier height. Enabled by these structural features, we demonstrated field emission density up to 4.1 × 104A cm–2at 1 V in air, more than 10-fold higher than typical molecular and vacuum electronics at similar conditions, and constructed an air-operating electron source with an on/off ratio of 105at the collector electrode. Energy-efficient high-conductance electron emission suggested the potential of using solution-synthesized nanomaterials in ultrascaled electronics.

It is important to understand the altitude adaptability of the turbocharging system for maximizing its potential in the power recovery of the diesel engine at high altitudes. This study investigated the influence of altitudes ranging from 0 to 4500 m on the performance of the single-stage and two-stage turbocharging systems in a heavy-duty diesel engine. The research was conducted using a six-cylinder, four-stroke, turbocharged, direct-injection diesel engine. An altitude simulation test bench was used to simulate altitudes of 0 to 4500 m by adjusting the temperature and pressure. According to the test results, the altitude adaptability of different turbocharging systems was analyzed based on turbine work and turbocharger efficiency. It was concluded that the high-pressure stage regulation in the two-stage turbocharging system (HRT) strengthens the regulation ability in turbine work, effectively regulating the boost pressure and maintaining high turbocharger efficiency at different altitudes. The HRT can satisfy the regulation ability for altitudes ranging from 0 to 4500 m. The low-pressure stage regulation in the two-stage turbocharging system (LRT) weakens the regulation ability in turbine work and relies on reduction of the turbocharger efficiency to regulate the boost pressure. The LRT ineffectively regulates the boost pressure at low altitudes, with altitude adaptability from 1500 to 4500 m. Due to the exhaust temperature limitation, the waste-gate in the single-stage turbocharging system (WG) is not suitable for large-span regulation to satisfy the performance of the diesel engine at altitudes above 3,000 m compared with the HRT and LRT.

This article presents an event-triggered adaptive neural networks secure tracking control method for a class of nonlinear cyber–physical systems under unknown sensor and actuator deception attacks. To obtain the desired system performance, dynamic surface technique is applied to design controller and radial basis function neural networks are introduced to deal with unknown nonlinear and actuator attacks. By skillfully combining compensation signals with the attack compensators, the unknown deception attacks are effectively mitigated. To reduce the transmission communication load, a novel event-driven control scheme is developed by applying relative threshold triggered mechanism. On this basis, all the signals of closed-loop system are bounded under deception attacks by using Lyapunov stability analysis. Additionally, the presented secure tracking control strategy can ensure the tracking error converges to a small neighborhood of origin and the Zeno behavior is ruled out. Finally, a practical example is employed to verify the feasibility and effectiveness of the designed control algorithm. [ABSTRACT FROM AUTHOR]

Recent studies indicated that vitamin A (VA) might be involved in the pathology of type 2 diabetes mellitus (T2DM). This cross-sectional study was conducted to explore the association between circulating VA level and T2DM. A total of 1 818 subjects aged 50 years old and above were recruited from the community. Binomial logistic regression and restricted cubic spline (RCS) were applied to analyze the association of plasma VA level with the risk of T2DM. Serum VA and lipid-adjusted VA levels of T2DM patients were significantly higher than that of non-T2DM subjects (P< 0.05). The ratios of plasma VA/total cholesterol (TC), VA/high-density lipoprotein cholesterol (HDL-c) and VA/low-density lipoprotein cholesterol (LDL-c) were positively associated with the risk of T2DM in the aging population (P< 0.05). Compared with the Q1 level, subjects with Q2 to Q3 levels of plasma VA/triglyceride (TG) have decreased risk of T2DM (odds ratio (OR)Q2= 0.68, PQ2= 0.021; ORQ3= 0.59, PQ3< 0.01). Our results indicated that the imbalance of circulating lipids and VA might affect the relationship between VA and T2DM. The middle and aging subjects with higher ratios of plasma VA/TC, VA/HDL-c, and VA/LDL-c displayed increased risk for T2DM, but the moderate ratio of VA/TG might protect against risk of T2DM.

Platycodon grandiflorusis a medicinal plant whose main component is platycodins, which have a variety of pharmacological effects and nutritional values. The farnesyl pyrophosphate synthase (FPS) is a key enzyme in the isoprenoid biosynthesis pathway, which catalyzes the synthesis of farnesyl diphosphate (FPP). In this study, we cloned the FPSgene from P. grandiflorus(PgFPS) with an ORF of 1260 bp, encoding 419 amino acids with a deduced molecular weight and theoretical pI of 46,200.98 Da and 6.52, respectively. The squalene content of overexpressed PgFPSin tobacco leaves and yeast cells extract was 1.88-fold and 1.21-fold higher than that of the control group, respectively, and the total saponin content was also increased by 1.15 times in yeast cells extract, which verified the biological function of PgFPSin terpenoid synthesis. After 48 h of MeJA treatment and 6 h of ethephon treatment, the expression of the PgFPSgene in roots and stems reached its peak, showing a 3.125-fold and 3.236-fold increase compared to the untreated group, respectively. Interestingly, the expression of the PgFPSgene in leaves showed a decreasing trend after exogenous elicitors treatment. The discovery of this enzyme will provide a novel perspective for enhancing the efficient synthesis of platycodins.

To tackle the proliferation of pathogenic microorganisms without relying on antibiotics, innovative materials boasting antimicrobial properties have been engineered. This study focuses on the development of graphene oxide/silver (GO/Ag) nanocomposites, derived from partially reduced graphene oxide adorned with silver nanoparticles. Various nanocomposites with different amounts of silver (GO/Ag-1, GO/Ag-2, GO/Ag-3, and GO/Ag-4) were synthesized, and their antibacterial efficacy was systematically studied. The silver nanoparticles were uniformly deposited on the partially reduced graphene oxide surface, exhibiting spherical morphologies with an average size of 25 nm. The nanocomposites displayed potent antibacterial properties against both gram-positive bacteria (S. aureusand B. subtilis) and gram-negative bacteria (E. coliand S. enterica) as confirmed by minimum inhibition concentration (MIC) studies and time-dependent experiments. The optimal MIC for Gram-positive bacteria was 62.5 μg/mL and for Gram-negative bacteria was 125 μg/mL for the GO/Ag nanocomposites. Bacterial cells that encountered the nanocomposite films exhibited significantly greater inhibitory effects compared to those exposed to conventional antibacterial materials. Furthermore, the cytotoxicity of these nanocomposites was assessed using human epithelial cells (HEC), revealing that GO/Ag-1 and GO/Ag-2 exhibited lower toxicity levels toward HEC and remained compatible even at higher dilution rates. This study underscores the potential of GO/Ag-based nanocomposites as versatile materials for antibacterial applications, particularly as biocompatible wound dressings, offering promising prospects for wound healing and infection control.

A Pd-catalyzed dual C–H carbonylation of commercially available diarylamines using Co2(CO)8as a safe CO source has been developed. This methodology provides a facile approach for the synthesis of diversified acridones in moderate to good yields. The protocol features good functional group compatibility, operational safety, easy scale-up, and versatile transformations.

Biomass-to-ethylene glycol is an effective means to achieve high-value utilisation of cellulose but is hindered by low conversion efficiency and poor catalyst activity and stability. Glucose and cellobiose are derivatives of cellulose conversion to ethylene glycol, and it is found that studying the reaction process of both can help to understand the reaction mechanism of cellulose. It is desirable to develop a reusable, highly active catalyst to convert cellulose into ethylene glycol. This ideal catalyst might have one or more active sites described the conversion steps above. Here, we discuss the catalyst development of cellulose-to-ethylene glycol, including tungsten, tin, lanthanide, and other transition metal catalysts, and special attention is given to the reaction mechanism and kinetics for preparing ethylene glycol from cellulose, and the economic advantages of biomass-to-ethylene glycol are briefly introduced. The insights given in this review will facilitate further development of efficient catalysts, for addressing the global energy crisis and climate change related to the use of fossil fuels.

Nowadays, vision oriented intelligent vehicle systems such as autonomous driving or transportation assistance can be optimized by enhancing the visual visibility of images acquired in bad weather conditions. The presence of haze in such visual scenes is a critical threat. Image dehazing aims to restore spatial details from hazy images. There have emerged a number of image dehazing algorithms, designed to increase the visibility of those hazy images. However, much less work has been focused on evaluating the visual quality of dehazed images. In this paper, we propose a Reduced-Reference dehazed image quality evaluation approach based on Partial Discrepancy (RRPD) and then extend it to a No-Reference quality assessment metric with Blind Perception (NRBP). Specifically, inspired by the hierarchical characteristics of the human perceiving dehazed images, we introduce three groups of features: luminance discrimination, color appearance, and overall naturalness. In the proposed RRPD, the combined distance between a set of sender and receiver features is adopted to quantify the perceptually dehazed image quality. By integrating global and local channels from dehazed images, the RRPD is converted to NRBP which does not rely on any information from the references. Extensive experiment results on both synthetic and real dehazed image quality databases demonstrate that our proposed methods outperform state-of-the-art full-reference, reduced-reference, and no-reference quality assessment models. Furthermore, we show that the proposed dehazed image quality evaluation methods can be effectively applied to tune parameters for image dehazing algorithms and have the potential to be deployed in real transportation systems.

For the shift control of clutchless automotive manual transmission (CLAMT) in electric vehicle, great difficulty is caused by the high level of precision and rapidity requirements of the speed and mode response of motor as well as the position response of gearshift sleeve, especially when confronted with off-road environment. To overcome the difficulty and achieve fast shift, a practical control method is proposed and applied to two-speed planetary CLAMT for off-road tracked vehicle with bilateral electric drive system, wire control system and unmanned driving purpose. In shift process, the method lets motor be controlled by applying torque mode and constant torque during active speed adjusting phase, lets gear engaging phase be started at the time when transmission ratio is regulated beyond a certain value close to target gear ratio – that is, at the time when the approach of synchronized state is achieved, lets synchronizer make a help for precise gear synchronization. Theoretical analysis of gear synchronization process is carried out. By increasing the level of motor torque, the duration of active speed adjusting phase can be obviously shortened. With the approach of synchronized state judged by using transmission ratio margin of small fixed positive value for reference, gear engaging phase can be achieved quickly. Off-road experiments show good performance of the shift control method. Experimental results and phenomena are discussed in detail for further and better understanding of real shift process.

Owing to the deep integration of intelligent control, big data and communication, networked Takagi–Sugeno fuzzy control systems is widely studied and applied to the real-world scenarios. This paper studies the issue of resilient event-triggered dynamic output feedback controller design of networked Takagi–Sugeno fuzzy systems under denial-of-service (DoS) attacks launched by adversaries. Considering the types of the attack limited by frequency and duration, a resilient event-triggered mechanism is established to resist the impact of DoS attacks and improve resource utilization efficiency, and two new switched fuzzy system models are constructed by integrating the underlying system and the event-based static and dynamic output feedback intelligent controllers. Then sufficient conditions are obtained to guarantee that the switched systems are exponential stable and then the control gains are designed by using a novel iterative algorithm. Finally, two examples are employed to verify the effectiveness of the developed method.

• A cost-effective strategy was suggested to produce high-performance near-β titanium alloy. • A excellent balance of strength and ductility (1570 MPa, 6.1%) was obtained. • A relationship between strength and Vickers hardness was established to analyze the negative influence of residual pores. • Under negative influence of residual pores, the evolution of tensile and fatigue properties was analyzed. Heat treatment plays an important role in tailoring the mechanical properties of powder-metallurgy (PM) titanium alloys. However, only limited work about the rapid heat treatment (RHT) of PM titanium alloys has been reported. In this work, RHT was applied to PM Ti–5Al–5Mo–5V–1Cr–1Fe alloy after hot rolling to study the evolution of its mechanical properties and the influence of residual pores on its properties. Through hot rolling and annealing, a fine and uniform α + β structure with few residual pores is obtained. During RHT, the primary α dissolves gradually and completes in the β region, and the β grains then grow, resulting in the continuous decrease in elongation after aging. Moreover, the tensile strength first increases and then decreases with increasing RHT temperature, owing to the increase in volume fraction of secondary α in α + β region and the β grain growth in β region. In contrast to the RHT of cast-and-wrought titanium, the negative influence of residual pores lowers the RHT temperature for obtaining the highest tensile strength to a temperature below the β-transus temperature. Despite the negative influence of the residual pores, retained primary α and fine β grains with fine secondary α inside contribute to achieving a good strength/ductility balance (1570 MPa and 6.1%, respectively). Additionally, although at higher cycles to failure, the negative influence of residual pores increases as it affects the crack initiation zone at the subsurface, the good resistance of secondary α to fatigue crack propagation still enhances the fatigue strength considerably (about 300 MPa). This work suggests a cost-effective strategy to produce titanium alloys with high performance. [Display omitted] [ABSTRACT FROM AUTHOR]

Alanine-serine-cysteine transporter 2 (ASCT2) is up-regulated in lung cancers, and inhibiting it could potentially lead to nutrient deprivation, making it a viable strategy for cancer treatment. In this study, we present a series of ASCT2 inhibitors based on aminobutanoic acids, which exhibit potent inhibitory activity. Two compounds, 20kand 25e, were identified as novel and potent ASCT2 inhibitors, with IC50values at the micromolar level in both A549 and HEK293 cells, effectively blocking glutamine (Gln) uptake. Additionally, these compounds regulated amino acid metabolism, suppressed mTOR signaling, inhibited non-small-cell lung cancer (NSCLC) growth, and induced apoptosis. In vivo, experiments showed that 20kand 25esuppressed tumor growth in an A549 xenograft model, with tumor growth inhibition (TGI) values of 65 and 70% at 25 mg/kg, respectively, while V9302only achieved a TGI value of 29%. Furthermore, both compounds demonstrated promising therapeutic potential in patient-derived organoids. Therefore, these ASCT2 inhibitors based on aminobutanoic acids are promising therapeutic agents for treating NSCLC by targeting cancer Gln metabolism.

In many clinical and research settings, the scarcity of high-quality medical imaging datasets has hampered the potential of artificial intelligence (AI) clinical applications. This issue is particularly pronounced in less common conditions, underrepresented populations and emerging imaging modalities, where the availability of diverse and comprehensive datasets is often inadequate. To address this challenge, we introduce a unified medical image–text generative model called MINIM that is capable of synthesizing medical images of various organs across various imaging modalities based on textual instructions. Clinician evaluations and rigorous objective measurements validate the high quality of MINIM’s synthetic images. MINIM exhibits an enhanced generative capability when presented with previously unseen data domains, demonstrating its potential as a generalist medical AI (GMAI). Our findings show that MINIM’s synthetic images effectively augment existing datasets, boosting performance across multiple medical applications such as diagnostics, report generation and self-supervised learning. On average, MINIM enhances performance by 12% for ophthalmic, 15% for chest, 13% for brain and 17% for breast-related tasks. Furthermore, we demonstrate MINIM’s potential clinical utility in the accurate prediction of HER2-positive breast cancer from MRI images. Using a large retrospective simulation analysis, we demonstrate MINIM’s clinical potential by accurately identifying targeted therapy-sensitive EGFRmutations using lung cancer computed tomography images, which could potentially lead to improved 5-year survival rates. Although these results are promising, further validation and refinement in more diverse and prospective settings would greatly enhance the model’s generalizability and robustness.

This paper investigates the problem of event-based finite-time L2filtering for networked interconnected fuzzy systems under denial-of-service attacks. To counter the impact of the attacks and improve the utilization of communication resources, a resilient event-triggered transmission strategy is introduced. Subsequently, a Takagi–Sugeno fuzzy filter is designed to estimate the unknown information, and an augmented fuzzy filter error system is formulated. Under this framework, a new Lyapunov–Krasovskii functional related to the membership functions is constructed to analyze the finite-time stability of the underlying error system. The filter gains and the event trigger parameters are obtained by solving the linear matrix inequality. Finally, the effectiveness of the developed method is substantiated by a numerical simulation example.

Recently, polar side chains have emerged as a functional tool to enhance conjugated polymer doping properties by improving the polymer miscibility with polar chemical dopants and facilitate solvated ion uptake. In this work, we design and investigate a novel family of side chains containing a single ether function, enabling the modulation of the oxygen atom position along the side chain. A meticulous investigation of this new polymer series by differential scanning calorimetry, fast scanning chip calorimetry and X-ray scattering shows that polymers bearing single-ether side chains can show high degree of crystallinity under proper conditions. Importantly, due to a gaucheeffect allowing the side chain to bend at the oxygen atom, the degree of crystallinity of polymers can be controlled by the position of the oxygen atom along the side chain. The further the oxygen atom is from the conjugated backbone, the more crystalline the polymer becomes. In addition, for all new polymers, high thermomechanical properties are demonstrated, leading to remarkable electrical conductivities and thermoelectric power factors in rub-aligned and sequentially doped thin films. This work confirms the potential of single-ether side chains to be used as polar solubilizing side chains for the design of a next generation of p- and n-type semiconducting polymers with increased affinity to polar dopants while maintaining high molecular order.

This article presents a $C$ -band multibeam phased-array receiver for high-throughput wireless communications. The proposed four-element beamformer supports 1–8 co-aperture simultaneously reconfigurable beams and demonstrates a 23-dB gain and a 6.5-dB noise figure (NF) at 5 GHz. In addition, it leverages a large-signal nonlinearity cancellation scheme and achieves a −10.8-dBm input 1-dB gain compression point (IP1dB) and a −4.7-dBm input third-order intermodulation intercept point (IIP3) at 5.5 GHz. By using the proposed merged gain-programmable phase shifter (GPS) technique, the beamformer achieves 32-path amplitude and phase control with high accuracy and a compact chip area. The entire chip occupies $6.4\times3.1$ mm2 area and consumes 1265 mW. To tackle the design challenge of the onboard multibeam-forming network, the proposed receive phased array adopts a scalable slat-type array configuration, enabling a low-cost design with high isolation. To the authors’ knowledge, this work demonstrates the largest number of concurrent co-aperture beams among integrated radio frequency (RF)-beamforming phased arrays.

This article proposes an adaptive fuzzy dual-channel event-triggered output feedback control approach for a class of multiple-input–multiple-output (MIMO) systems with deception attacks and input saturation. Due to the consideration of two pivotal factors simultaneously, including deception attacks and input saturation, the existing methods are difficult to be directly applied. To this end, a novel fuzzy state observer and an auxiliary system are constructed to address unavailable impaired system states and input saturation, respectively. Furthermore, by constructing a new transformation of coordinate and employing adaptive fuzzy technique and single parameter learning approach, the sensor deception attacks, fuzzy weight, and external disturbance are reconstructed online into linear composite uncertain terms with single parameter under the framework of backstepping and dynamic surface design. In addition, the communication and computation burden is significantly reduced by using fewer single-parameter adaptive laws and dual-channel event-triggered strategy. The proposed control method guarantees that all signals within the closed-loop system are bounded. Meanwhile, the Zeno behavior is avoided. Finally, a simulation example is provided to verify the availability of the presented approach.

Wireless sensor network (WSN) is usually deployed in unattended monitoring environments, with limited energy and large-scale characteristics. Therefore, the performance of WSN is susceptible to the influence of external environment and its own energy. The existing routing protocols try to optimize energy efficiency and routing reliability from the perspective of the network itself. However, they do not take into account the environmental impact from the outside, which makes them unable to properly respond to harsh environment. Therefore, a new environment fusion routing protocol (EFRP) is proposed. Cluster heads (CHs) are selected in a probabilistic manner according to the ratio of the energy of each node and environmental factors. Nodes with excellent environment have a higher probability of being selected as CHs. Besides, the EFRP optimal path is determined according to the comprehensive potential field superimposed by the distance field, residual energy field, and environmental field. The best path can be weighed among delay, energy saving, and routing invulnerability. Therefore, the balance of network energy is realized, and the invulnerability of the network in harsh environment is improved. The experimental results show that EFRP can significantly improve the data transmission and invulnerability of the network in harsh environments.

Wall climbing represents a crucial task in a heavy unmanned ground vehicle (HUGV) working under poor road conditions. Inspired by the human perception-action behavior, this study proposes an effective human-like planning system for solving the wall-climbing problem in the HUGVs. In the proposed model, the Gaussian mixture model (GMM) and hidden semi-Markov model (HSMM) are combined to imitate the stochastic dynamic driving behavior. Based on the decision made by the GMM-HSMM-based driver model, the speed planner uses the dynamic motion primitive (DMP) to generate the expected speed curve. Furthermore, in the climbing-over process, the DMP is employed to predict the motor torque curve. This study considers a driver's perception of acceleration, which strengthens the planning system's adaptability and flexibility. The proposed method is verified by experiments with a real electric tracked HUGV. The experimental results show that the proposed system with duration constraints can maintain a reasonable acceleration rate, balancing driving safety and efficiency in the wall-climbing task. Moreover, the proposed method can adapt well to different road conditions without using a vehicle dynamics model.

Extracting discriminative information from complex spectral details in hyperspectral image (HSI) for HSI classification is pivotal. While current prevailing methods rely on spectral magnitude features, they could cause confusion in certain classes, resulting in misclassification and decreased accuracy. We find that the derivative spectrum proves more adept at capturing concealed information, thereby offering a distinct advantage in separating these confusion classes. Leveraging the complementarity between spectral magnitude and derivative features, we propose a content-driven spectrum complementary network (CSCN) based on magnitude-derivative dual encoder, employing these two features as combined inputs. To fully utilize their complementary information, we raise a content-adaptive pointwise fusion module (CPFM), enabling adaptive fusion of dual-encoder features in a pointwise selective manner, contingent upon feature representation. To preserve a rich source of complementary information while extracting more distinguishable features, we introduce a hybrid disparity-enhancing loss that enhances the differential expression of the features from the two branches and increases the interclass distance. As a result, our method achieves state-of-the-art results on the extensive WHU-OHS dataset and eight other benchmark datasets.

Multi-vehicle coordinated motion planning has always been challenged to safely and efficiently resolve conflicts under non-holonomic dynamic constraints. Constructing spatial-temporal corridors for multi-vehicle can decouple the high-dimensional conflicts and further reduce the difficulty of obtaining feasible trajectories. Therefore, this article proposes a novel hierarchical multi-vehicle coordinated motion planning method based on interactive spatio-temporal corridors (ISTCs). In the first layer, based on the initial guidance trajectories, Mixed Integer Quadratic Programming is designed to construct ISTCs capable of resolving conflicts in generic multi-vehicle scenarios. And then in the second layer, Non-Linear Programming is settled to generate in-corridor trajectories that satisfy the vehicle dynamics. By introducing ISTCs, the multi-vehicle coordinated motion planning problem is able to be decoupled into single-vehicle trajectory optimization problems, which greatly decentralizes the computational pressure and has great potential for real-world applications. Besides, the proposed method searches for feasible solutions in the 3-D$(x,y,t)$ configuration space, preserving more possibilities than the traditional velocity-path decoupling method. Simulated experiments in unsignalized intersection and challenging dense scenarios have been conducted to verify the feasibility and adaptability of the proposed framework.

Effective trajectory prediction is of great significance for the design of intelligent driving systems. To overcome the problems of low algorithm efficiency and insufficient scenario adaptation in urban environments, this article proposes a trajectory prediction framework based on the rule and learning-based frameworks fusion (TP-FRL). By augmenting the observed trajectory under the guidance of a physically possible trajectory set, the proposed framework improves algorithmic adaptation in the presence of disturbed trajectory observations. Meanwhile, rule-based spatio-temporal semantic corridors are used to vectorize agent trajectory-related regions, which improves the rationality of each agent region division and enhances the adaptability in different scenarios. Finally, based on the trajectory-related region modeling of each agent, the interest region of the central agent is learned by a graph convolutional network, and only the scenario elements in the interest region are encoded to improve the trajectory prediction efficiency of the transformer multi-head attention network. Traffic data from Argoverse and ApolloScape datasets are used to evaluate the performance of the TP-FRL model. Specifically, the TP-FRL model shows efficient performance and strong adaptability on datasets from two countries, which shows the promise of predicting trajectories under various scenarios.

Circular RNAs (circRNAs) have emerged as key regulators of cancer occurrence and progression, as well as promising biomarkers for cancer diagnosis and prognosis. However, the potential mechanisms of circRNAs implicated in lymph node (LN) metastasis of gastric cancer remain unclear. Herein, we identify a novel N6-methyladenosine (m6A) modified circRNA, circPAK2, which is significantly upregulated in gastric cancer tissues and metastatic LN tissues. Functionally, circPAK2 enhances the migration, invasion, lymphangiogenesis, angiogenesis, epithelial-mesenchymal transition (EMT), and metastasis of gastric cancer in vitro and in vivo. Mechanistically, circPAK2 is exported by YTH domain-containing protein 1 (YTHDC1) from the nucleus to the cytoplasm in an m6A methylation-dependent manner. Moreover, increased cytoplasmic circPAK2 interacts with Insulin-Like Growth Factor 2 mRNA-Binding Proteins (IGF2BPs) and forms a circPAK2/IGF2BPs/VEGFA complex to stabilize VEGFA mRNA, which contributes to gastric cancer vasculature formation and aggressiveness. Clinically, high circPAK2 expression is positively associated with LN metastasis and poor prognosis in gastric cancer. This study highlights m6A-modified circPAK2 as a key regulator of LN metastasis of gastric cancer, thus supporting circPAK2 as a promising therapeutic target and prognostic biomarker for gastric cancer.

Currently, the synthesis of activated carbon predominantly relies on trial and error, specifically centered on the modulation of activators or alterations in activation conditions. However, the resultant characteristics of activated carbon obtained through such procedures normally lacked predictability and control. This study utilized natural pine wood powder as the primary material and three distinct biochar precursors were prepared through meticulous control of oxidation time, possessed similar O/C with varying initial pore structures. Except that, the porosity or mesopore volume were significantly different. Final results showed that precursor materials with higher mesoporous ratios/volumes prefer to hinder the increase of specific surface area during activation. The T600-1.5D exhibits a mesopore ratio of 35.26%, nearly double that of T600-0.5D, yet concurrently displays a relatively modest specific surface area only of 1765.6 m2/g. Finally, our study highlights the intrinsic correlation between the mesoporous ratio or mesoporous volume in biochar precursors and the specific surface area of final activated carbon. These findings provide new insights into targeted, predictable, and controllable activation of carbonaceous materials, offering innovative pathways to address the challenges in developing porous materials.

An object-level attention prediction framework for drivers in the urban environment with rich semantic and motion information is proposed in this article. The proposed framework is based on the visual working memory mechanism, which decomposes the perception process into three phases, external stimuli, cognitive constructing, and memory search. In the external stimuli phase, semantic and motion information of surrounding objects is obtained. In the cognitive constructing phase, the neighbor-based hierarchical clustering method is applied to extract both independent and dependent features of traffic participants and driving events. In the memory search phase, the heterogeneous motif graph neural network is utilized to construct visual memory layers and integrate multilevel features for attention reasoning. Finally, the feature embedding is fed into a multilayer perceptron to predict the object-level visual attention. Training and testing data are collected from crowded and dynamic traffic scenes. Experimental results show that the proposed framework can achieve a superior object-level prediction performance in the information-rich environments compared with the state-of-the-art methods. In addition, the proposed framework can reduce the time bias of visual attention effectively.

Intrauterine adhesion is a major cause of female reproductive disorders. Although we and others uncontrolled pilot studies showed that treatment with autologous bone marrow stem cells made a few patients with severe intrauterine adhesion obtain live birth, no large sample randomized controlled studies on this therapeutic strategy in such patients have been reported so far. To verify if the therapy of autologous bone marrow stem cells-scaffold is superior to traditional treatment in moderate to severe intrauterine adhesion patients in increasing their ongoing pregnancy rate, we conducted this randomized controlled clinical trial. Totally 195 participants with moderate to severe intrauterine adhesion were screened and 152 of them were randomly assigned in a 1:1 ratio to either group with autologous bone marrow stem cells-scaffold plus Foley balloon catheter or group with only Foley balloon catheter (control group) from February 2016 to January 2020. The per-protocol analysis included 140 participants: 72 in bone marrow stem cells-scaffold group and 68 in control group. The ongoing pregnancy occurred in 45/72 (62.5%) participants in the bone marrow stem cells-scaffold group which was significantly higher than that in the control group (28/68, 41.2%) (RR=1.52, 95%CI 1.08–2.12, P=0.012). The situation was similar in live birth rate (bone marrow stem cells-scaffold group 56.9% (41/72) vs.control group 38.2% (26/68), RR=1.49, 95%CI 1.04–2.14, P=0.027). Compared with control group, participants in bone marrow stem cells-scaffold group showed more menstrual blood volume in the 3rd and 6th cycles and maximal endometrial thickness in the 6th cycle after hysteroscopic adhesiolysis. The incidence of mild placenta accrete was increased in bone marrow stem cells-scaffold group and no severe adverse effects were observed. In conclusion, transplantation of bone marrow stem cells-scaffold into uterine cavities of the participants with moderate to severe intrauterine adhesion increased their ongoing pregnancy and live birth rates, and this therapy was relatively safe.

Among all kinds of anticancer agents, small molecule drugs produce an unsatisfactory therapeutic effect due to the lack of selectivity, notorious drug resistance and side effects. Therefore, researchers have begun to pay extensive attention to macromolecular drugs with high efficacy and specificity. As a plant toxin, gelonin exerts potent antitumor activity viainhibiting intracellular protein synthesis. However, gelonin lacks a translocation domain, and thus its poor cellular uptake leads to low outcomes of antitumor response. Here, tumor acidity and matrix metalloproteinase (MMP) dual-responsive functional gelonin (Trx-PVGLIG-pHLIP-gelonin, TPpG), composed of a thioredoxin (Trx) tag, a pH low insertion peptide (pHLIP), an MMP-responsive motif PVGLIG hexapeptide and gelonin, was innovatively proposed and biologically synthesized by a gene recombination technique. TPpG exhibited good thermal and serum stability, showed MMP responsiveness and could enter tumor cells under weakly acidic conditions, especially for MMP2-overexpressing HT1080 cells. Compared to low MMP2-expressing MCF-7 cells, TPpG displayed enhanced in vitroantitumor efficacy to HT1080 cells at pH 6.5 as determined by different methods. Likewise, TPpG was much more effective in triggering cell apoptosis and inhibiting protein synthesis in HT1080 cells than in MCF-7 cells. Intriguingly, with enhanced stability and pH/MMP dual responsiveness, TPpG notably inhibited subcutaneous HT1080 xenograft growth in mice and no noticeable off-target side effect was observed. This ingeniously designed strategy aims at providing new perspectives for the development of a smart platform that can intelligently respond to a tumor microenvironment for efficient protein delivery.

Biomass is normally a poor thermal conductor with high moisture content. These characteristics not only reduce the calorific value of biomass, but also promote the formation of coke and non-condensable gas during subsequent thermal processing. However, the commercial application of biomass is limited to the high energy and time consumption during drying stage. In this research, a pilot-scale cyclone dryer was designed for efficient drying of biomass and the drying characteristics were explored. Its superiority was revealed via the comparison of two traditional drying methods as blast drying oven and fluidized bed. Results showed that cyclone drying has the highest moisture diffusion coefficient (9.0 × 10−10m2/s to 1.3 × 10−9m2/s) and the lowest drying activation energy (18.3 kJ/mol). Its drying time is nearly 10% less than that of fluidized bed drying. Even this value is only about 1/4 of blast drying oven. Experimental results show that most of the free water can be removed in a shorter time in the stage of drying speed reduction in cyclone, especially in the initial stage of drying at the same temperature in the low-temperature zone (60 to 80 ℃). It was found that the cyclone drying technology can dry biomass particles in a short time with low energy consumption.

In this brief, we investigate the fixed-time consensus of discrete-time heterogeneous multi-agent systems with model predictive control. Stability conditions are derived through Lyapunov functions, and the settling time independent of initial conditions is obtained. Based on the sufficient stability conditions, a distributed model predictive controller is designed by optimizing the consensus problem. Numerical examples are conducted to showcase the validity of the derived theoretical results and the effectiveness of the designed controller.

In this study, Wen et al. provide mechanistic insights into the regulation of the oncoprotein BOWL, which is marked for ubiquitin-mediated degradation by the E3 ligase HYD when complexed with the substrate adaptor LIN, highlighting a putative tumor-suppressive role for the HYD–LIN complex. Their findings define a previously unrecognized tumor suppressor pathway that links the epigenetic program to regulated protein degradation in tissue growth control and tumorigenesis.