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This article proposes a novel extended sliding-mode predictive control strategy for three-phase three-level voltage source inverters. Initially, the control domain is established using sliding-mode theory, dynamically reducing the search space. Subsequently, a unique parallel optimization strategy is presented in the two-phase stationary coordinate system, with an analysis of the monotonicity of the cost functions and the constraints within the search space. Compared to traditional model predictive control, this approach results in a calculation time reduction of at least 51.3%. To mitigate output ripple, a novel design method for virtual voltage vectors (VVVs) is proposed based on α and β components, demonstrating notable scalability. At the same time, to maintain neutral point voltage balance, two output modes are devised for the VVVs using redundant small voltage vectors, eliminating weighting factors. Additionally, the excessive voltage jumps are mitigated and the method operates at a constant switching frequency. Experimental results robustly validate the algorithm's superior performance.

A new genus and species belonging to the planthopper family Inoderbidae, Imbricatala novitas gen. and sp. nov., is described based on a well-preserved specimen from the mid-Cretaceous Kachin amber of northern Myanmar. This is the second genus of the subfamily Inoderbinae which mainly differs from the previously described genus in frons elongate with paired sublateral swellings, mesonotum with five carinae, tegmen about 1.5 times as long as hind wing, tegmen with triangular basal cell and RP and CuA both with 4 terminals, legs covered with short setae, metatibio-tarsal formula 5: 10: 11. The subfamilial diagnosis characters of Inoderbidae are briefly discussed. Imbricatala gen. nov. provides more information to understand the morphological diversity of Inoderbidae during the mid-Cretaceous.

Bivalves are often employed for biomonitoring contaminants in marine environments; however, in these large-scale programs, unavoidably, using multiple species presents a significant challenge. Interspecies differences in contaminant bioaccumulation can complicate data interpretation, and direct comparisons among species may result in misleading conclusions. Here, we propose a robust framework based on toxicokinetic measurements that accounts for interspecies differences in bioaccumulation. Specifically, via a recently developed double stable isotope tracer technique, we determined the toxicokinetics of cadmium (Cd)─a metal known for its high concentrations in bivalves and significant interspecies bioaccumulation variability─in six widespread bivalve species including mussels (Perna viridis, Mytilus unguiculatus, Mytilus galloprovincialis) and oysters (Magallana gigas, Magallana hongkongensis, Magallana angulata). Results show that oysters generally have higher Cd uptake rate constants (ku: 1.18–3.09 L g–1d–1) and lower elimination rate constants (ke: 0.008–0.017 d–1) than mussels (ku: 0.21–0.64 L g–1d–1; ke: 0.018–0.037 d–1). The interspecies differences in tissue Cd concentrations are predominantly due to Cd uptake rather than elimination. Utilizing toxicokinetic parameters to back-calculate Cd concentrations in seawater, we found that the ranking of Cd contamination levels at the six sites markedly differs from those based on tissue Cd concentrations. We propose that this approach will be useful for interpreting data from past and future biomonitoring programs.

The regioselective installation of chalcogen atoms into biaryl scaffolds is an important synthetic task due to the great value of chalcogen-containing biaryl derivatives in many fields. Here we undertake this task by developing a regioselective 2,2′-dichalcogenation of 2-bromobiaryls with common chalcogen sources using an organolanthanum-mediated one-pot, two-step protocol. This strategy features high regioselectivity, readily available substrates, transition-metal-free conditions, and performance superior to those of previous methods, thereby demonstrating the unique advantages of organolanthanum reagents in organic synthesis.

The nonuniform current distribution in high-power thyristors leads to a significant rise in local junction temperature (Tlj), potentially threatening the reliability of high-power thyristors. For online monitoring Tlj, a novel temperature-sensitive electrical parameter method was proposed based on peak stray gate current (ipsg). First, simplified turn-off models for high-power thyristors with an amplifying gate were set up to explore the variations of gate-cathode voltage and stray gate current in the turn-off transition. Subsequently, the theoretical relationship between ipsg and Tlj was established. Significantly, the physical meaning of Tlj was illustrated by the theoretical relationship and the temperature distribution simulation. Next, the feasibility of the proposed method was verified by the temperature calibration experiment. Considering self-heating, the temperature sensitivity is 89 mA/°C at a thyristor voltage of 1.0 kV, which increases with increasing thyristor voltage. Finally, an online monitoring Tlj case was carried out based on a tunnel magnetoresistance current sensor. The proposed method is easy to implement and is capable of measuring local junction temperature concerning major heat generation regions, which is suitable for high-voltage applications.

In response to a series of problems such as high computational complexity, slow processing speed, poor denoising effect, signal loss, energy attenuation, and decreased transmission performance that traditional filtering methods face when filtering digital signals from electronic measuring instruments in the laboratory, a fast filtering method for digital signals of electronic measuring instruments in the laboratory on the basis of the Fourier transform is studied. Based on the Fourier transform, an adaptive time–frequency filtering method based on the fractional Fourier transform is proposed. By utilizing the important characteristic that this transform is equivalent to rotating the signal in the time–frequency plane, mixed noisy signals are subjected to a fractional Fourier transform at a specific rotation angle to minimize the overlap between the signal and noise in the transform domain. The linear frequency modulation (LFM) signal is filtered and extracted through fractional Fourier transform method. Most of the noise energy is removed, and the original LFM signal is recovered by fractional Fourier inverse transform to realize the rapid filtering of high-quality digital signals of electronic measuring instruments in the laboratory. Experiments have shown that using this filtering method to denoise digital signals from laboratory electronic measuring instruments can not only reduce computational complexity, improve filtering speed, but also enhance filtering effectiveness. The filtered signal has low noise content, high restoration, good transmission performance, reduced attenuation, and strong anti-interference ability. At the same time, it can effectively remove various types of noise, with an average improvement percentage of 15.68% in signal-to-noise ratio. It also maintains the integrity of data sampling and the accuracy of statistical results, which is conducive to further analysis and research.

Graph models many real-world data like social, transportation, biology, and communication data. Hence, graph traversal including multi-hop or graph-walking queries has been the key operation atop graph stores. However, since different graph traversals may touch different sets of vertices, it is hard or even impossible to have a one-size-fits-all graph partitioning algorithm that preserves access locality for various graph traversal workloads. Meanwhile, prior shard-based migration faces a dilemma such that coarse-grained migration may incur more migration overhead over increased locality benefits, while fine-grained migration usually requires excessive metadata and incurs non-trivial maintenance costs. We present Pragh, an efficient locality-preserving live graph migration scheme for graph stores in the form of key-value pairs. The key idea of Pragh is a split migration model that only migrates values physically while retaining keys in the initial location. This allows fine-grained migration while avoiding the need to maintain excessive metadata. Pragh integrates an RDMA-friendly location cache from DrTM-KV to provide fully-localized access to migrated data and further makes a novel reuse of the cache replacement policy for lightweight monitoring. Pragh further supports evolving graphs through a check-and-forward mechanism to resolve the conflict between updates and migration of graph data. Evaluations on an 8-node RDMA-capable cluster (100 Gbps) using a representative graph traversal benchmark show that Pragh can increase the throughput by up to 19× and decrease the median latency by up to 94%, thanks to split live migration that eliminates 97% remote accesses. A port of split live migration to Wukong shows up to 2.53× throughput improvement on representative workloads like LUBM-10240, thanks to a reduction of 88% remote accesses. This further confirms the effectiveness and generality of Pragh. Finally, though Pragh focuses on RDMA-based graph traversal, we show its generality by extending it to support graph traversals under traditional networking. Evaluations on the graph traversal benchmarks and graph query workloads on the same cluster but with 10 Gbps TCP/IP network further confirm its effectiveness without RDMA. Specifically, when evaluating on the LUBM-10240, Wukong-TCP with Pragh can achieve up to 1.87× throughput improvement with a 56% decrease in remote accesses.

Selective atomic layer deposition (S-ALD) is gaining significant attention for its pivotal role in the bottom-up manufacturing of semiconductors and catalysts. This study delves into the selective growth mechanisms of M(NtBU)(NEt2)3(M = Nb and Ta) on Cu and SiO2substrates using density functional theory (DFT) calculations. We discovered that the nucleation delay on Cu substrates is primarily due to sluggish dissociation kinetics. Utilizing these insights, we propose an anisotropic growth model framed within microkinetics and numerical nucleus expansion approaches. Our model integrates defect- and diffusion-induced nucleation parameters, aligning closely with experimental growth curves and accurately quantifying ALD nucleation delays in the initial stages. Such a model builds a direct link between the observed nucleation delay and ALD experimental parameters from the atomic scale. Furthermore, this DFT-based nucleation model demonstrates a robust predictive capacity for nucleation delay cycles for a wide range of materials, aligning well with the experimental findings. This advancement offers a theoretical method for assessing the selectivity of S-ALD from the bottom up, enhancing our understanding and control of these critical processes.

The corrosion behavior of WE43 alloy with different rolling reductions (0%, 25%, 45%, and 80%) at 500 °C was investigated in 3.5 wt.% NaCl solution. The microstructure evolution of the rolled WE43 alloy was characterized in detail by means of optical microscopy (OM), transmission electron microscopy (TEM) and electron back-scattered diffraction (EBSD). The results show that with increasing reductions, basal texture is gradually enhanced and grain size gradually decreases. Only the alloy with 45% reduction exhibits dispersed dynamic precipitates. Immersion and electrochemical measurements demonstrate the decreasing order of the corrosion resistance of the rolled WE43 alloy: 45% reduction > 80% reduction > 25% reduction > 0 reduction. The best corrosion resistance of the WE43 alloy with 45% reduction is mainly related to a large number of finely dispersed precipitates, which are capable of promoting the formation of a compact corrosion product layer. The increased corrosion rate of the sample with 80% reduction is induced by the re-solution of the majority of precipitates into the matrix. The grain size, basal texture and deformation twins have a limited effect on the corrosion resistance of rolled WE43 alloy compared with the precipitates.

Electrochemical paper-based analytical devices (ePADs) are an excellent choice to achieve the goal of global health due to their advantages of low cost, portability, and rapid analysis. However, the low sensitivity limits the application of ePADs. In this study, a 3D origami-inspired ePAD with flow-through electrodes and quasi-steady flow was presented for signal amplification to enhance the sensitivity. A Silhouette Studio plotter/cutter was used to design four schemes with a porous gold electrode as the working electrode. The flow-through electrode with quasi-steady flow exhibited the highest current due to enhanced convective transfer. The peak current of the device combined with flow-through porous electrodes with flow increased by 97.2 and 63.8% compared with the device without flow and the device combined flow-over electrodes with flow, respectively. The finite element simulation results showed that the current increased 10 times compared with the conventional saturated devices with flow-over electrodes and flow-through electrodes. Moreover, the evaluation of the device used copper ions as the detection species. The current of the device that combined flow-through with quasi-steady flow was about twice as large as other schemes and owned higher sensitivity. This strategy provides new insights and a more facile way to amplify signals of ePADs.

Development of a highly performing heterojunction photoanode is significantly important for photoelectrochemical cells. Herein, a novel strategy is proposed to construct a protonated g-C3N4nanosheets/nitrogen-doped TiO2photoanode inspired by polydopamine microspheres. The polydopamine microspheres can enhance the adsorption of protonated g-C3N4nanosheets via electrostatic interaction, facilitating heterojunction formation. Moreover, the addition of the polydopamine microspheres into the preparation process can not only dope a nitrogen element into TiO2, improving solar energy utilization, but also create a vigorous pore structure in the photoanode, promoting mass transport and light scattering. Besides, the specific surface area can also be increased. Owing to these merits, the photoelectrochemical activity of this newly developed photoanode is greatly improved. Furthermore, the superiority of this photoanode is evaluated by integrating it into a photoelectrochemical cell for simultaneous wastewater treatment and power generation. The maximum power density generated by the newly developed protonated g-C3N4nanosheets/nitrogen-doped TiO2photoanode is about 138.5% and 40.9% higher than the TiO2photoanode and the protonated g-C3N4nanosheets/TiO2photoanode prepared without using the polydopamine microspheres, respectively. The present study provides a novel strategy for developing a highly performing heterojunction photoanode.

The dense and uniform Cr coating is successfully applied to the Zry-4 (zircaloy-4) substrate using multi-arc ion plating as an accident-tolerant fuel cladding. The isothermal oxidation behavior of the Cr-coated Zry-4 is investigated in air and steam at 1200 °C. The mass gain, microstructure evolution and phase composition of the Cr-coated Zry-4 after different oxidation times are compared. The mass gain of Cr-coated Zry-4 in air is higher than in steam. In air, the dense Cr2O3layer consisted of bulk Cr2O3, while protruding flake Cr2O3is found on the surface of the Cr coating in steam. The degradation process and oxidation failure mechanism of the Cr-coated Zry-4 in air and steam at 1200 °C are analyzed.

Liquid confined in a nanochannel or nanotube has exhibited a superfast transport phenomenon, providing an ideal heat and mass transfer platform to meet the increasingly stringent challenge of thermal management in developing high-power-density nanoelectronics and nanochips. However, understanding the thermal transport of confined liquid is currently lacking and is speculated to be fundamentally different from that of bulk counterparts due to the unprecedented thermodynamics of liquid in nanoconfined environments. Here, we report that the thermal conductivity of water confined in a silica nanotube is nearly 2-fold as that of bulk status. Further molecular dynamics simulations reveal that this unusual enhancement originates from the densification and reorientation of local hydrogen bonds close to the nanotubes. Thermal-confinement scaling law is established and quantitatively supported by comprehensive simulations with remarkable agreement. Our findings lay a theoretical foundation for designing nanofluidics-enabled cooling strategies and devices.

Corrosion-erosion performances of Ti-6.5Al–2Zr–1Mo–1V (TA15) alloy fabricated by two laser additive manufacturing technologies, namely selective laser melting (SLM) and laser metal deposition (LMD) were investigated, and compared with those of traditional forged counterpart. Results show that SLM-ed TA15 possesses better corrosion, wear, and tribocorrosion resistances than LMD-ed and forged TA15. This is mainly attributed to the ultrafine-grain αʹ phase in the microstructure of SLM-ed sample, which improves the hardness and thereby enhances the wear and tribocorrosion resistance. Additionally, the complete αʹ phase formed in SLM-ed sample also avoids the galvanic corrosion that occurs at the α+β-type LMD-ed and forged samples.

A dense three-layer corrosion product film was formed on aged WE43 alloy in 3.5 wt.% NaCl solution. The microstructure of the film was analyzed in detail by TEM. The three-layer corrosion product film is composed of RE2O3, MgO layer doped with RE2O3and Mg(OH)2layer doped with RE2O3from the inside to the outside. A large amount of rare earth oxide particles formed both by the outward oxidation of rare earth precipitates and rare earth elements, are the main reason for the formation of the corrosion film. The RE2O3has the preferential orientation with ( 2-11) plane and [231] direction parallel to (002) plane and [ 1-1-0] direction of MgO, respectively. Thus, the rare earth oxide particles can fill the gap of porous MgO layer, and improve the compactness of the film. The inner RE2O3layer and mixed layer of MgO and RE2O3play an important role in the formation of the film. The compact inner film can prevent the corrosion medium from reacting with the Mg matrix.

Luminescent perovskite nanocrystals (NCs), possessing the advantages of low cost, easy detection, and excellent luminescence, are becoming more and more significant in the fields of information encryption and decryption. Most hydrochromic perovskite NCs for information encryption have moderate reversibility and are easily passively decrypted by water in the moist air, limiting their practical applications. Herein, a lyochromic material is synthesized based on reversible phase transition between luminescent CsPbBr3–HBr (pretreating CsPbBr3with HBr) and nonluminescent Cs4PbBr6, exhibiting excellent reversibility in 50 cycles triggered by CsBr solution. HBr treatment boosts the ion migration of NCs via diminishing surface ligands and passivating Br vacancy, assisting CsBr concentration acting as a crucial factor in dynamic ion exchange equilibrium between the trigger solution and CsPbBr3–HBr. By utilizing CsPbBr3–HBr as a safety ink, the CsBr-triggered photoluminescence switch has been demonstrated to be reproducible, stable, and reliable for information encryption and decryption.

IMPORTANCE: Sublingual edaravone dexborneol, which can rapidly diffuse and be absorbed through the oral mucosa after sublingual exposure, is a multitarget brain cytoprotection composed of antioxidant and anti-inflammatory ingredients edaravone and dexborneol. OBJECTIVE: To investigate the efficacy and safety of sublingual edaravone dexborneol on 90-day functional outcome in patients with acute ischemic stroke (AIS). DESIGN, SETTING, AND PARTICIPANTS: This was a double-blind, placebo-controlled, multicenter, parallel-group, phase 3 randomized clinical trial conducted from June 28, 2021, to August 10, 2022, with 90-day follow-up. Participants were recruited from 33 centers in China. Patients randomly assigned to treatment groups were aged 18 to 80 years and had a National Institutes of Health Stroke Scale score between 6 and 20, a total motor deficit score of the upper and lower limbs of 2 or greater, a clinically diagnosed AIS symptom within 48 hours, and a modified Rankin Scale (mRS) score of 1 or less before stroke. Patients who did not meet the eligibility criteria or declined to participate were excluded. INTERVENTION: Patients were assigned, in a 1:1 ratio, to receive sublingual edaravone dexborneol (edaravone, 30 mg; dexborneol, 6 mg) or placebo (edaravone, 0 mg; dexborneol, 60 μg) twice daily for 14 days and were followed up until 90 days. MAIN OUTCOMES AND MEASURES: The primary efficacy outcome was the proportion of patients with mRS score of 1 or less on day 90 after randomization. RESULTS: Of 956 patients, 42 were excluded. A total of 914 patients (median [IQR] age, 64.0 [56.0-70.0] years; 608 male [66.5%]) were randomly allocated to the edaravone dexborneol group (450 [49.2%]) or placebo group (464 [50.8%]). The edaravone dexborneol group showed a significantly higher proportion of patients experiencing good functional outcomes on day 90 after randomization compared with the placebo group (290 [64.4%] vs 254 [54.7%]; risk difference, 9.70%; 95% CI, 3.37%-16.03%; odds ratio, 1.50; 95% CI, 1.15-1.95, P = .003). The rate of adverse events was similar between the 2 groups (89.8% [405 of 450] vs 90.1% [418 of 464]). CONCLUSION AND RELEVANCE: Among patients with AIS within 48 hours, sublingual edaravone dexborneol could improve the proportion of those achieving a favorable functional outcome at 90 days compared with placebo. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04950920

•To study the adsorption of coal under the comprehensive influence of temperature and pressure, one thermobaric adsorption experiment has been introduced. The unique characteristic of thermobaric is one adsorption at a pair of temperature and pressure. Its main advantage of thermobaric adsorption is to simulate temperatures and pressures corresponding to coal reservoirs at different depths. To verify the thermobaric adsorption's data, it is acquired new theory and improved the experimental method, this paper will briefly describe adsorption instruments and procedure, mathematically analyze the differences between isothermal adsorption and thermobaric adsorption in complexity of test procedure. A temperature-pressure-adsorption equation (TPAE) has been used to regress the measured data and error calculation and expand the application probability of thermobaric adsorption. The 3-dimensional TPAE surface is also used for verification. The other 3 sets of optimized thermobaric adsorptions (10 pairs, 8 pairs, and 6 pairs) have been created. To cover a range of temperature (18∼72 °C) and pressure (1∼19 MPa), there must be at least the minimum 6 pairs of thermobaric adsorptions including the lowest temperature 18 °C and pressure 1 MPa, and the highest temperature 72 °C and pressure 19 MPa.

Suspended particulate matter (SPM) carries a major fraction of metals in turbid coastal waters, markedly influencing metal bioaccumulation and posing risks to marine life. However, its effects are often overlooked in current water quality criteria for metals, primarily due to challenges in quantifying SPM’s contribution. This contribution depends on the SPM concentration, metal distribution coefficients (Kd), and the bioavailability of SPM-bound metals (assimilation efficiency, AE), which can collectively be integrated as a modifying factor (MF). Accordingly, we developed a new stable isotope method to measure metal AE by individual organisms from SPM, employing the widely distributed filter-feeding clam Ruditapes philippinarumas a representative species. Assessing SPM from 23 coastal sites in China, we found average AEs of 42% for Zn, 26% for Cd, 20% for Cu, 8% for Ni, and 6% for Pb. Moreover, using stable isotope methods, we determined metal Kdof SPM from these sites, which can be well predicted by the total organic carbon and iron content (R2= 0.977). We calculated MFs using a Monte Carlo method. The calculated MFs are in the range 9.9–43 for Pb, 8.5–37 for Zn, 2.9–9.7 for Cu, 1.4–2.7 for Ni, and 1.1–1.6 for Cd, suggesting that dissolved-metal-based criteria values should be divided by MFs to provide adequate protection to aquatic life. This study provides foundational guidelines to refine water quality criteria in turbid waters and protect coastal ecosystems.

The potential risk for mental health conditions over the menopause transition shapes women's expectations and informs putative physiological mechanisms regulating women's mental health. We review evidence from prospective studies reporting on associations between mental health conditions and the menopause transition. Major depressive disorder and the more prevalent subthreshold depressive symptoms are the most common conditions studied. We reviewed 12 prospective studies reporting depressive symptoms, major depressive disorder, or both over the menopause transition and found no compelling evidence for a universal increased risk for either condition. However, specific subgroups of participants, primarily defined by menopause-related risk factors (ie, vasomotor symptoms that are severe or disturb sleep, a long duration of the transition, or reproductive hormone dynamics) and psychosocial risk factors (eg, stressful life events), were vulnerable to depressive symptoms. The increased risk of major depressive disorder over the menopause transition appears predominantly in individuals with previous major depressive disorder. Greater focus on recognising risk factors in primary care is warranted. On the basis of scarce data, we found no compelling evidence that risk of anxiety, bipolar disorder, or psychosis is universally elevated over the menopause transition. Potential misattribution of psychological distress and psychiatric disorders to menopause could harm women by delaying accurate diagnosis and the initiation of effective psychotropic treatments, and by creating negative expectations for people approaching menopause. A paradigm shift is needed. We conclude with recommendations for the detection and treatment of depressive symptoms or major depressive disorder and strategies to promote good mental health over the menopause transition, while responsibly preparing and supporting those at risk.

Post-weld heat treatment and rolling deformation are used to improve the mechanical properties of 2195-O Al–Li alloy friction stir welding (FSW) joints, and the effects on the grain structure, precipitation behaviors, hardness distribution, and tensile performance are discussed. Microstructural characterization was conducted using scanning electron microscopy (SEM), electron backscattered diffraction (EBSD), and transmission electron microscopy (TEM). Mechanical properties were measured by hardness test and tensile test. Results show that coarse precipitates are subjected to various degrees of dissolution after FSW. Solution treatment following artificial aging (SAA) and 40% rolling deformation + SAA treatment (R40-SAA) enables the dissolution of coarse precipitates completely and precipitation of strengthening phases (T1and θ′) in the nugget zone (NZ), thermo-mechanically affected zone and heat-affected zone (HAZ). These strengthening precipitates have little difference in precipitation behavior after SAA and R40-SAA treatment and remain consistent across all regions, resulting in joint hardness change a little between these two joints with a homogeneous distribution. The change in precipitates leads to an increase in hardness and enhances both the SAA joint strength and the R40-SAA joint strength to 503 MPa and 528 MPa (superior to the original joints by 309 MPa and 334 MPa, respectively), respectively. The SAA joints fracture in the NZ resulting from the development of AGG, and develop an intergranular fracture morphology with an elongation of 4.2%. The R40-SAA joints have an elongation of 7.2% due to the generation of uniformly fine grains in the NZ, and fail in the HAZ exhibiting a brittle fracture mechanism.

The traditional finite-set model predictive voltage control for three-phase three-level voltage source inverters with LC-filter suffers from high computational burden, fussy weighting factor adjustment, and variable switching frequency. To address these issues, this article proposes an improved model predictive voltage control scheme with optimal switching sequence. Two voltage vector switching modes are designed to eliminate weighting factors and achieve neutral-point voltage balancing. Furthermore, a subsector optimization method based on boundary conditions is proposed, which avoids the calculation of multiple groups of duty cycle and hence, greatly reducing the computational burden. Additionally, the proposed method operates at a constant switching frequency. The effectiveness of the proposed algorithm is verified by experimental results based on a laboratory prototype from various perspectives, including steady-state and dynamic performance, algorithm execution time, and parameter sensitivity.

Abstract: The present study investigated inhibitory effects of 1,4-dihydropyridines (1,4-DHPs) calcium channel antagonists (1,4-DHP-CCAs) on cytochromeP450 3A4 (CYP3A4) of human liver microsomes and further explored importance of 1,4-DHPs molecular structural descriptors. Partial Least Squares method was applied to probe the quantitative relationships between the 1,4-DHPs molecular structural descriptors and its inhibitory actions, which demonstrated that different 1,4-DHP-CCAs could inhibit CYP3A4 enzyme’s activity differently. The K i values of nicardipine, lercandipine, cilnidipine, nitrendipine, lacidipine, nifedipine, felodipine were 10.13, 10.17, 11.44, 23.90, 29.34, 29.06 and 32.64 μmol L−1, respectively. It is suggested that the 1,4-DHPs molecular structural descriptors are the most important for its inhibitory effects based on the quantitative structure–activity relationship (QSAR) formula. The LogP was positively correlated to the K i, whereas molecular weight and molecule volume were negatively correlated. It is concluded that analysis of K i of 1,4-DHPs derivatives on the CYP3A4 activity may apply for the QSAR formula at the initial stage of clinical application of new drugs.

In order to develop a highly efficient H2S gas sensor at low working temperature, in this work, a kind of novel Ce-doped ZnCo2O4hollow microspheres (Ce/ZnCo2O4HMSs) were successfully synthesized using a template-free one-pot method, showing a sensitive response toward H2S. The microstructure and morphology of the material were characterized by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The gas-sensing performance of the composite was investigated, showing that the ZnCo2O4doped with 6 mol% Ce had the highest response to 20 ppm H2S at a low operating temperature of 160 °C with a response value of 67.42, which was about 2 times higher than that of original ZnCo2O4. The prepared Ce/ZnCo2O4HMS sensor in response to H2S exhibited a linear range of 0.1–200 ppm with a low detection limit of 0.1 ppm under the conditions of ambient humidity of 45% and ambient temperature of 20 °C. Meanwhile, it also possessed good selectivity, repeatability and reproducibility. The response value of the sensor decreased by 5.32% after 7 months of continuous monitoring of H2S in an atmospheric environment of a pig farm, indicating that the sensor had a long-term stability and continuous service life with important application prospects.

Gallium nitride offers an ideal material platform for next-generation high-power electronics devices, which enable a spectrum of applications. The thermal management of the ever-growing power density has become a major bottleneck in the performance, reliability, and lifetime of the devices. GaN/diamond heterostructures are usually adopted to facilitate heat dissipation, given the extraordinary thermal conduction properties of diamonds. However, thermal transport is limited by the interfacial conductance at the material interface between GaN and diamond, which is associated with significant mechanical stress at the atomic level. In this work, we investigate the effect of mechanical strain perpendicular to the GaN/diamond interface on the interfacial thermal conductance of heterostructures using full-atom non-equilibrium molecular dynamics simulations. We found that the heterostructure exhibits severe mechanical stress at the interface in the absence of loading, which is due to lattice mismatch. Upon tensile/compressive loading, the interfacial stress is more pronounced, and the strain is not identical across the interface owing to the contrasting elastic moduli of GaN and diamond. In addition, the interfacial thermal conductance can be notably enhanced and suppressed by tensile and compressive strains, respectively, leading to a 400% variation in thermal conductance. More detailed analyses reveal that the change in interfacial thermal conductance is related to the surface roughness and interfacial bonding strength, as described by a generalized relationship. Moreover, phonon analyses suggest that the unequal mechanical deformation under compressive strain in GaN and diamond induces different frequency shifts in the phonon spectra, leading to an enhancement in phonon overlapping energy, which promotes phonon transport at the interface and elevates the thermal conductance and vice versafor tensile strain. The effect of strain on interface thermal conductance was investigated at various temperatures. Based on the mechanical tunability of thermal conductance, we propose a conceptual design for a mechanical thermal switch that regulates thermal conductance with excellent sensitivity and high responsiveness. This study offers a fundamental understanding of how mechanical strain can adjust interface thermal conductance in GaN/diamond heterostructures with respect to mechanical stress, deformation, and phonon properties. These results and findings lay the theoretical foundation for designing thermal management devices in a strain environment and shed light on developing intelligent thermal devices by leveraging the interplay between mechanics and thermal transport.

This article presents a new finite control set model predictive control (FCS-MPC) algorithm for three-phase (3P) T-type voltage source inverters. The proposed algorithm incorporates a vector combination technique to generate a total of 51 virtual vectors (VVs), which is 89% more than the traditional algorithm, leading to excellent inverter output voltage tracking capability with reduced harmonics. Such VVs do not affect the neutral point (NP) voltage. Therefore, the NP voltage balance term can be eliminated in the cost function. In addition, to achieve a low computational burden, a three-stage optimization is employed. Experimental results validate the effectiveness of the proposed algorithm and demonstrate its superiority over conventional approaches.

Aberrant mRNA expression is implicated in uterine corpus endometrial carcinoma (UCEC) oncogenesis and progression. However, effective prognostic biomarkers for UCEC remain limited. We aimed to construct a reliable multi-gene risk model using gene expression profiles. Utilizing TCGA data (543 UCEC samples, 35 controls), we identified 1517 differentially acting genes. Weighted gene co-expression complex analysis (WGCCA), hub gene screening, and risk regression analysis (RRA) were employed to determine prognosis-related genes and construct the risk model. Nomograms visualized risk scores and receiver operator characteristic (ROC) curves assessed model performance. Seven novel prognosis-related hub genes (ANGPT1, ASB2, GAL, GDF7, ONECUT2, SV2B, TRPC6) were identified. The model’s concordance index (C index) by multivariate Cox regression analysis was 0.79. ROC curves yielded AUCs of 0.811 (3-year) and 0.79 (5-year), demonstrating the model’s efficacy in predicting UCEC survival. Our study proposes a promising seven-biomarker risk model for predicting UCEC prognosis, offering potential clinical utility.

The key to improving the efficiency by which acid-soil-growing plants utilize nitrogen is to improve their efficiency of utilizing ammonium. The carbon deficiency is recognized as the main cause of the failure to increase ammonium efficiency by simply strengthening the ammonium absorption capacity of the roots. Whether increasing carbon input by manipulating the stomatal aperture can enhance the utilization of ammonium in plants that receive high-intensity ammonium absorption in roots is our goal. We use a high ammonium treatment to mimic the excessive ammonium uptake condition and manipulate the stomata by spraying potassium or potassium uptake inhibitors through a foliar method. This was performed to investigate the effect of manipulating the stomatal aperture on the ammonium utilization capacity of centipedegrass, a typical acid soil-growing excellent turf grass, under the root excessive ammonium uptake condition. Once a high-ammonium root environment is encountered, the stomatal aperture rapidly decreases. Leaf potassium supply, rather than sodium ion supply, increases the stomatal aperture. Under hydroponic conditions, foliar application of potassium solution alleviates the inhibition of stomatal opening, restores photosynthetic capacity, and thus increases plant tolerance to high ammonium levels. When additional potassium absorption inhibitor Cs is added, the plant loses the relieving effect caused by foliar potassium spraying. Foliar spraying of potassium solution improves the high ammonium tolerance of centipedegrass by increasing the stomatal aperture. Co-reinforcing the leaf stomatal opening process and the root ammonium absorption capacity process is a feasible strategy to achieve the high efficiency of ammonium.

Protists are important microorganisms involved in the transformation of nutrients, but little information is available regarding their roles in composting. This study investigated the changes in the protist community during composting and their relationships with the conversion of nitrogen. The protist community structure varied among the different composting phases, but the communities were similar in the cooling phase and at the end of the thermophilic phase. Phagotrophic protists such as Acantharea-Group-II_XX and Acantharea_XXX dominated in the composting process. The abundance of Acantharea-Group-II_XX increased by 12.8% in the thermophilic phase, whereas that of Acantharea_XXX increased by 74.5% and 275.3% during the cooling and maturation phases, respectively. The protist community was mainly affected by the NO3−and NO2−concentrations and the bacterial community, where NO3−and NO2−inhibited phagotrophic protists. Furthermore, compared with the nitrifying bacterial communities, the denitrifying bacterial communities were more conducive to the growth of Acantharea-Group-II_XX and Acantharea_XXX. Phagotrophic protists were key predators that regulated bacteria with denitrification functions.

Four kinds of Mg alloys with different Zn and Ca concentration were selected to analyze the effect of Zn and Ca concentration on the microstructure and the mechanical properties of Mg–Zn–Ca alloys. It was found that Zn and Ca concentration has a great influence on the volume fraction, the morphology and the size of second phase. The Mg–1.95Zn–0.75Ca (wt%) alloy with the highest volume fraction, continuous network and largest size of Ca2Mg6Zn3phase showed the lowest elongation to failure of about 7%, while the Mg–0.73Zn–0.12Ca (wt%) alloy with the lowest volume fraction and smallest size of Ca2Mg6Zn3phase showed the highest elongation to failure of about 37%. It was suggested that uniform elongations of the Mg–Zn–Ca alloys were sensitive to the volume fraction of the Ca2Mg6Zn3phases, especially the network Ca2Mg6Zn3phases; post-uniform elongations were dependent on the size of the Ca2Mg6Zn3phase, especially the size of network Ca2Mg6Zn3phase. Reduction in Zn and Ca concentration was an effective way to improve the room-temperature ductility of weak textured Mg–Zn–Ca alloys.

Molecular solid solutions of metal clusters containing different metal centers with well-defined structures can accurately regulate the HOMO-LUMO gap, but are rarely available. Herein, a series of colorless lanthanide-titanium-oxo clusters Ln2Ti4(μ2-O)2(μ3-O)4(Piv)10(THF)2(Ln2Ti4, Ln = Eu, Gd, Tb, and Ce, HPiv = pivalic acid) were synthesized by the reaction of pivalic acid with Ln(Ac)3and titanium isopropoxide. The light yellow crystal of cluster solid solutions Eu2Ti4−xCdx, containing a mixture of Eu2Ti4and Eu2Ti3Cd, was obtained by in situdoping Cd2+and S2−. Eu2Ti3.92Cd0.08displays efficient photocatalytic hydrogen evolution activity without a co-catalyst, which is up to 2.6 times that of Eu2Ti4. Femtosecond time-resolved transient absorption spectroscopy and spin-polarized density functional calculations showed that the enhanced photocatalytic performance of Eu2Ti4−xCdxcan be attributed to the narrower HOMO-LUMO gap and lower LUMO position than that of Eu2Ti4. This studyprovides an in situdoping method to realize the simple preparation of cluster solid solution.

Code comments are a crucial source of software documentation that captures various aspects of the code. Such comments play a vital role in understanding the source code and facilitating communication between developers. However, with the iterative release of software, software projects become larger and more complex, leading to a corresponding increase in issues such as mismatched, incomplete, or outdated code comments. These inconsistencies in code comments can misguide developers and result in potential bugs, and there has been a steady rise in reports of such inconsistencies over time. Despite numerous methods being proposed for detecting code comment inconsistencies, their learning effect remains limited due to a lack of consideration for issues such as characterization noise and labeling errors in datasets. To overcome these limitations, we propose a novel approach called MCCL that first removes noise from the dataset and then detects inconsistent code comments in a timely manner, thereby enhancing the model's learning ability. Our proposed model facilitates better matching between code and comments, leading to improved development of software engineering projects. MCCL comprises two components, namely method comment detection and confidence learning denoising. The method comment detection component captures the intricate relationships between code and comments by learning their syntactic and semantic structures. It correlates the code and comments through an attention mechanism to identify how changes in the code affect the comments. Furthermore, confidence learning denoising component of MCCL identifies and removes characterization noises and labeling errors to enhance the quality of the datasets. This is achieved by implementing principles such as pruning noisy data, counting with probabilistic thresholds to estimate noise, and ranking examples to train with confidence. By effectively eliminating noise from the dataset, our model is able to more accurately learn inconsistencies between comments and source code. Our experiments on 1,518 open-source projects demonstrate that MCCL can accurately detect inconsistencies, achieving an average F1-score of 82.6%. This result outperforms state-of-the-art methods by 2.4% to 28.0%. Therefore, MCCL is more effective in identifying inconsistent comments based on code changes compared to existing approaches.

Quantifying metal bioaccumulation in a sedimentary environment is a valuable line of evidence when evaluating the ecological risks associated with metal-contaminated sediments. However, the precision of bioaccumulation predictions has been hindered by the challenges in accurately modeling metal influx processes. This study focuses on nickel bioaccumulation from sediment and introduces an innovative approach using the isotopically modified bioassay to directly measure nickel assimilation rates in sediment. Tested in sediments spiked with two distinct nickel concentrations, the measured Ni assimilation rates ranged from 35 to 78 ng g–1h–1in the Low-Ni treatment and from 96 to 320 ng g–1h–1in the High-Ni treatment. Integrating these rates into a biodynamic model yielded predictions of nickel bioaccumulation closely matching the measured results, demonstrating high accuracy with predictions within a factor of 3 for the Low-Ni treatment and within a factor of 1 for the High-Ni treatment. By eliminating the need to model metal uptake from various sources, this streamlined approach provides a reliable method for predicting nickel bioaccumulation in contaminated sediments. This advancement holds promise for linking bioaccumulation with metal toxicity risks in sedimentary environments, enhancing our understanding of metal-contaminated sediment risks and providing valuable insights to support informed decision-making in ecological risk assessment and management.

This article introduces an innovative approach to address the challenge of inadequate electrostatic excitation in a metal-shell resonator gyroscope. The methodology involves a comprehensive analysis of the gyroscope oscillator’s mechanical model, followed by the creation of an equivalent kinematic model using thin-shell theory and Lagrange planetary equations. To optimize the performance of the gyroscope, finite element simulations are leveraged to fine-tune the dimensional parameters and electrode excitation technique of the resonator gyroscope. The signal detection circuit of the metal-shell resonator gyroscope comprises two key components: an excitation circuit and a detection circuit. The excitation circuit utilizes electrostatic excitation, while the detection circuit employs a ${C}/{V}$ conversion circuit. This particular circuit converts the oscillations of the gyroscope into voltage variations, enabling accurate detection of the gyroscope’s vibrational signals. The final iteration of the gyroscope prototype demonstrates remarkable performance characteristics. Notably, the gyroscope exhibits exceptional bias stability, with readings of 35 °/h (1 s) and 18 °/h (10 s). The gyroscope’s operational range spans from −257 to 260 °/s, providing a broad measurement capacity. Furthermore, the gyroscope achieves a scale factor nonlinearity of just 1305 ppm, ensuring precise and reliable measurements.

Development of conductive hydrogels with high sensitivity and excellent mechanical properties remains a challenge for constructing flexible sensor devices. Herein, a universal strategy is presented for enhancing the mechanical strength of Mxene-based double-network hydrogels through metal ion coordination effects. Polyacrylamide (PAM)/sodium alginate (SA)/Mxene double-network (PSM-DN) hydrogels were prepared by metal ion impregnation of PAM/SA/Mxene (PSM) hydrogels. High electrical conductivity is achieved due to MXene nanosheets, while the strong coordination bond between metal ions and SA constructs a second network that increases the mechanical strength of the hydrogel by an order of magnitude. Mechanical tests demonstrated that the elastic modulus of hydrogels matches that of human tissues. Hence, they can be used as a highly sensitive electronic skin sensor to recognize the movement of different joints in humans and also as a pressure sensing interface to recognize characters for anticounterfeiting and information transfer. This work can promote the practical application of conductive hydrogels in high-tech fields, such as flexible electronic skin and interface interaction.

Hydrogel sensors are fascinating as flexible sensors and electronic skin due to their excellent biocompatibility and structure controllability. However, developing conductive hydrogels possessing both excellent mechanical and antifreezing properties for environmental-adaptive sensors remains a challenge. Herein, a strategy of combining betaine and metal ions to construct poly(acrylic acid) (PAA)-based high-conductive hydrogels has been reported. PAA-Al3+/betaine hydrogels with high toughness and antifreezing property were prepared by a one-step UV curing method. Their high toughness is attributed to the coordination of metal ions with the carboxylic groups in PAA, the interaction of betaine with PAA, and the formation of hydrogen bonds between them and water molecules. Moreover, the significant antifreezing property is due to the reduction of free water in the hydrogel. This, in turn, is attributed to the hydration of metal ions and the synergistic hydrogen bonding between betaine and water. The experiments demonstrate that the hydrogel has excellent mechanical property, high conductivity, superior transparency, antiswelling property, antipuncture as well as shape memory properties, and especially, low cytotoxicity. It can be used as a sensor for motion detection and information recognition. This work provides new insights into the application of flexible sensors and human–machine interfaces in multienvironmental conditions.

ABSTRACTThe continuous homogeneous rail constraint of embedded rail system (ERS) is realized by the encapsulation of rails with the elastic poured compound (EPC) which is a composite material. Previous treatment of EPC as linear elastic material was insufficient in the failure analysis of ERS. In this work, a hyperelastic model is developed to describe the mechanical properties of the EPC with engineering strain up to 150%. Physical tests of uniaxial tension, planar tension and quadruple shear are conducted. A 4-parameter Ogden model is determined by curve fitting and validated with a progressive validation strategy, and then is applied to the failure analysis of ERS. It is found that the material nonlinearity of EPC contributes noticeably to the decrease of the longitudinal stiffness of ERS. The 2nddebonding is more probably caused by the failure of adhesive at the interface between EPC and rail rather than EPC itself.

High-density light-emitting diodes (LEDs) show great potential for next-generation micro-display technology due to their high resolution, long operational life, high brightness and high efficiency. However, conventional fabrication methods for high density LEDs suffer from issues such as growth difficulties, etch damage, and ion implantation damage. In this work, we propose an epitaxial slice damage-free process to fabricate an LED array with high density (2500 pixels per inch). To inhibit the potential electrical and optical crosstalk, the single-contact (SC) operation mode is employed. It is demonstrated that the SC-LEDs show frequency-selective luminescence characteristics. Moreover, crosstalk effect of the LEDs is significantly reduced compared to that operating in conventional DC mode. Finally, the mechanism of crosstalk suppression is revealed by finite element analysis. This work provides a promising approach for realizing high density LED array, offering valuable reference for further development in micro/nano-display technology.

Studies have revealed that both extracorporeal shock‐wave therapy (ESWT) and hyperbaric oxygen therapy (HBOT) can accelerate wound healing. This study aimed to compare the effectiveness of ESWT and HBOT in enhancing diabetic wound healing. A dorsal skin defect in a streptozotocin‐induced diabetes rodent model was used. Postoperative wound healing was assessed once every 3 days. Histologic examination was performed with hematoxylin and eosin staining. Proliferation marker protein Ki‐67 (Ki‐67), endothelial nitric oxide synthase (eNOS), vascular endothelial growth factor (VEGF), and 8‐hydroxy‐2‐deoxyguanosine (8‐OHdG) were evaluated with immunohistochemical (IHC) staining. The wound area was significantly reduced in the ESWT and HBOT groups compared to that in the diabetic controls. However, the wound healing time was significantly increased in the HBOT group compared to the ESWT group. Histological findings showed a statistical increase in neovascularization and suppression of the inflammatory response by both HBOT and ESWT compared to the controls. IHC staining revealed a significant increase in Ki‐67, VEGF, and eNOS but suppressed 8‐OHdG expression in the ESWT group compared to the HBOT group. ESWT facilitated diabetic wound healing more effectively than HBOT by suppressing the inflammatory response and enhancing cellular proliferation and neovascularization and tissue regeneration.

We consider partitioned scheduling of an imprecise mixed-criticality (IMC) taskset on a uniform multiprocessor platform, with the earliest deadline first-virtual deadline (EDF-VD) as the uniprocessor task scheduling algorithm, and address the optimization problem of finding a feasible task-to-processor assignment and low-criticality (LO) mode processor speed with the objective of minimizing the system’s average energy consumption in LO mode. We propose a task-to-processor assignment algorithm criticality-unaware worst-fit decreasing (CU-WFD) algorithm, which allocates tasks with the worst-fit decreasing (WFD) heuristic method based on utilization values at their respective criticality levels. We determine the energy-efficient speed for each processor based on EDF-VD scheduling, and present our algorithm energy-efficient partitioned scheduling for imprecise mixed-criticality (EEPSIMC) with the CU-WFD heuristic algorithm to minimize system energy consumption. The experimental results show that our proposed algorithm has good performance in terms both schedulability ratio and normalized energy consumption compared to seven comparison baselines.

The safe proximity to spacecraft is a prerequisite for most on-orbit service missions. However, performing proximity operations on orbit is dangerous and high cost. Therefore, preverification of the proximity control algorithm through ground experiments can determine the reliability and promote the success of actual on-orbit missions. This article constructs an air floating experiment system and a guidance algorithm for the safe proximity to a complex-shaped tumbling spacecraft. The proposed control algorithm consists of two parts: 1) one part is an improved Gaussian mixture model, with which a novel artificial potential function is designed to accurately describe the complex shape of the target and provide three-dimensional collision avoidance constraints and 2) the other part is to use the fixed time control method to ensure that the service spacecraft can reach the desired position within a fixed time. The numerical simulation and experiments are implemented to verify the effectiveness of the proposed algorithm.

• Plate-impact experiments were conducted on TiZrNbV under strain rate of approximately 107 s−1 by self-sacrificial samples. • Hugoniot elastic limit of TiZrNbV was 4.12–5.86 GPa. Dislocation movement was affected by fluctuating stress field and severe lattice distortion, as well as dynamic Hall–Petch effect caused by dislocation cutting. • Critical strain rate for phonon drag effect was related to relative atomic mass and lattice distortion of alloys. • Spall Strength of TiZrNbV was 1.84–2.03 GPa as shock pressure increased from 5.07 to 12.17 GPa, with intergranular, transgranular and mixed-type cracks dominating the spall failure. • Bulk modulus of HEAs was positively correlated with valence-electron concentration. In this study, the dynamic compressive response behavior of a body-centered cubic (BCC) single-phase TiZrNbV refractory high-entropy alloy (RHEA) was investigated under impact at speeds of 313–1584 m s–1 using two-stage, gas-gun-driven, high-speed plate-impact experiments; recovery sample analysis; and theoretical calculations. The strain rate and pressure were approximately 107 s−1 and 5.07–29.37 GPa, respectively. The results showed that the TiZrNbV RHEA had a Hugoniot elastic limit of 4.12–5.86 GPa and a spall strength of 1.84–2.03 GPa. The initial yield strength of the alloy showed a strong strain-rate dependence and could be described by the modified Zerilli–Armstrong model, while the phonon-damping effect was the main reason for its high strain-rate sensitivity. Microstructural analysis showed that the dynamic deformation of the TiZrNbV RHEA was controlled by the dislocation slip, dislocation proliferation, intersection of the deformation bands, and grain refinement. The analysis also showed that the intergranular, transgranular, and mixed-type cracks dominated the spall failure of the material. The dynamic Hall–Petch effect and pinning from the lattice distortion led to high dynamic yield strength. The critical strain rate for the phonon drag effect was positively related to the relative atomic mass and local strain field of the metals. Within the experimental loading range, the RHEA showed good structural stability, and simultaneously, the theoretical calculation method for the equation of state based on a cold-energy mixture could accurately predict its shock-response behavior. The valence-electron concentration (VEC) had a direct effect on the shock-compression properties of the HEAs; higher VEC implied more difficulty in compressing the HEAs. The findings of this study provide insights into understanding the mechanical response characteristics of RHEAs under extreme conditions such as high-speed impact and ultrahigh strain-rate loading. [Display omitted] [ABSTRACT FROM AUTHOR]

Single-cell diagnosis of cancer drug resistance is highly relevant for cancer treatment, as it can be used to identify the subpopulations of drug-resistant cancer cells, reveal the sensitivity of cancer cells to treatment, and monitor the progress of cancer drug resistance. However, simple and effective methods for cancer drug resistance detection at the single-cell level are still lacking in laboratory and clinical studies. Inspired by the fact that nanoparticles with diverse physicochemical properties would generate distinct and specific interactions with drug-resistant and drug-sensitive cancer cells, which have distinctive molecular signatures, here, we have synthesized a library of fluorescent nanoparticles with various sizes, surface charges, and compositions (SiO2nanoparticles (SNPs), organic PS-co-PAA nanoparticles (ONPs), and ZIF-8 nanoparticles (ZNPs)), thus demonstrating that the composition has a critical influence on the interaction of nanoparticles with drug-resistant cancer cells. Furthermore, the clathrin/caveolae-independent endocytosis of ZNPs together with the P-glycoprotein-related decreased cell membrane fluidity resulted in a lower cellular accumulation of ZNPs in drug-resistant cancer cells, consequently causing the distinct cellular accumulation of ZNPs between the drug-resistant and drug-sensitive cancer cells. This difference was further quantified by detecting the fluorescence signals generated by the accumulation of nanoparticles at the single-cell level via flow cytometry. Our findings provide another insight into the nanoparticle–cell interactions and offer a promising platform for the diagnosis of cancer drug resistance of various cancer cells and clinical cancer samples at the single-cell level.

Recent research on on-orbit service rarely considers the complex shapes of servicing spacecraft (chaser) and the target simultaneously, which could cause collision problems in ultraclose-range proximity. This article presents a novel trajectory planning method via critical safety curve (TPCSC). The core of the framework is the construction of collision avoidance constraints called critical safety curve (CSC) using geometrized mathematical methods. CSC has good mathematical properties and innovatively combines the complex shape and relative attitude constraints of two spacecraft. Subsequently, TPCSC proposes an improved disturbed fluid method based on CSC that can handle non-convex constraints to generate smooth approach trajectories. Finally, the framework can achieve ultraclose-range proximity between spacecraft with complex shapes under complex non-convex constraints. The simulation results indicate that the planning of TPCSC is rapid, and the formed trajectory is safe, smooth, and easy to track.

Application review event inference aims to assess the effectiveness of application problems in response to user actions, which enables application developers to promptly discover and address potential issues in various applications, thereby improving their development and maintenance efficiency. Despite the development of event inference models for app reviews, which extract them as user action and app problem events and establish a relationship model between events and inference labels, the accuracy of these models is constrained due to limitations in labeling and characterizing noise and the lack of robustness and generalization. To address this challenge, we propose a model called Easy Data Augmentation for Application Reviews Event Inference (short for EDA-AREI), which comprises a denoising component, data augmentation component, and event inference prediction component. Specifically, the denoising component identifies labels and characterizes noisy data to enhance dataset quality, the data augmentation component replaces non-stop words with synonyms to increase textual diversity, and the event inference and prediction component reconstructs the classifier using denoised and augmented data. Experimental results on six datasets of one-star app reviews in the Apple App Store demonstrate that the EDA-AREI method achieves an Accuracy of 71.19%, 79.14%, 69.05%, 69.02%, 68.24% and 68.48%, respectively, representing an improvement of 0.83%–2.09% compared to state-of-the-art models. Regarding the F1-score, EDA-AREI achieves values of 71.30%, 69.93%, and 68.76% on the threshold_0.5, k-means_2, and random datasets, respectively, outperforming state-of-the-art models by 1.89%–4.02%. Furthermore, EDA-AREI achieves AUC values of 75.66% and 73.37% on the threshold_0.5 and k-means_2 datasets, respectively. As a result, EDA-AREI demonstrates substantial improvements in Accuracy, as well as enhanced F1-score and AUC across most datasets, thereby enhancing the model's accuracy and robustness in identifying related action-problem pairs.