Search

The solubility of 2-[4-(dibutylamino)-2-hydroxy-benzoyl] benzoic acid (BBA) was determined in 12 pure solvents using the static equilibrium method. The measurements were taken at temperatures ranging from 283.15 to 323.15 K. The results indicated a positive relationship between the solubility of BBA and the temperature in the 12 pure solvents, and BBA exhibited the highest solubility in n-propanol and the lowest solubility in n-heptane. In addition, the modified Apelblat, Van’t Hoff, λh, and Wilson models were used to establish a correlation with the experimental solubility of BBA. The correlation analysis revealed a strong concordance between the experimental and estimated values. Furthermore, the solubility characteristics of BBA were further examined by utilizing Hansen’s solubility parameter. The results revealed that the dissolution of BBA in solvents is a multifaceted process, influenced by various parameters rather than solution polarity and HSP. The thermodynamic properties of the mixture of BBA in 12 pure solvents were also evaluated based on the measured solubility data and the parameter values of the Wilson model.

The demands for surface impedance vary when it comes to traveling wave diffraction and specular reflection suppression in absorbing structures across a broad frequency range. To address these conflicting requirements, a composite structure of frequency selective surface and area coated honeycomb (FSS-ACH) structure is developed herein via surface impedance modulation. This structure enables effective suppression of both types of scattering. Simulation results show that the proposed absorber achieves a monostatic radar cross section (RCS) reduction of more than −10 dB at normal incidence within the frequency range of 2–10 GHz. In addition, the first traveling wave lobe is reduced by more than 10 dB for TM polarization at grazing incidence. To validate the proposed design method, samples were fabricated and measured in an anechoic chamber. The obtained measurement outcomes closely corresponded with the simulated results, thus providing solid confirmation of the efficacy of the proposed design approach.

The in situ preparation of high-temperature strain sensors and minimization of the monitoring of the surface impact are crucial for effectively monitoring the health of devices in high-temperature and extreme environments, such as aircraft engines. However, most high-temperature strain gauges are expensive and complex to manufacture, and they exhibit poor high-temperature stability. In this study, polymer-derived ceramic (PDC) technology is introduced to prepare PDC thin-film strain gauges (TFSGs). The high-temperature stability of the sensor is improved by the superior high-temperature and adhesion performance characteristics of PDCs. In addition, SiO2 is generated at high temperatures to create a protective film layer. Herein, we present the fabrication of PDC/indium-tin oxide (ITO) TFSGs using direct ink writing (DIW) 3-D printing to assess their performance. The experimental results demonstrate that the prepared PDC/ITO TFSGs have a low-resistance drift rate of 0.55%/h and a high strain coefficient of 8 at 1100 °C after 1 h of heat preservation. These gauges have a stable structure at 1200 °C and should withstand temperatures of at least 1400 °C in the short term.

Interleukin-1 receptor associated kinase 4 (IRAK4) is an essential mediator of the IL-1R and TLR signaling pathways, both of which have been implicated in multiple autoimmune conditions. Hence, blocking the activity of IRAK4 represents an attractive approach for the treatment of autoimmune diseases. The activity of this serine/threonine kinase is dependent on its kinase and scaffolding activities; thus, degradation represents a potentially superior approach to inhibition. Herein, we detail the exploration of structure–activity relationships that ultimately led to the identification of KT-474, a potent, selective, and orally bioavailable heterobifunctional IRAK4 degrader. This represents the first heterobifunctional degrader evaluated in a nononcology indication and dosed to healthy human volunteers. This molecule successfully completed phase I studies in healthy adult volunteers and patients with atopic dermatitis or hidradenitis suppurativa. Phase II clinical trials in both of these indications have been initiated.

Imidazolium ionic liquids (ILs) are widely utilized in various fields due to their distinctive properties. However, their high viscosity limits their application in specific reactions, and mixing ILs with organic components is a way to solve this problem. While previous studies mainly focused on the structural changes of ILs after adding organic molecules, no studies elucidated the influence of their existing species on chemical reactions. In this study, aerobic α-hydroxylation of 2-methylcyclohexanone was chosen as a model reaction, and the reaction rate was found to be adjusted by varying imidazolium concentration in its mixtures with dimethyl sulfoxide. To elucidate the mechanism, the distribution of species in an IL solution and its change with concentration were studied by molecular dynamics simulations, and the results revealed the significant impact of the concentration of free cations on the reaction rate. The interaction between the ionic species and reaction intermediate, as calculated by density functional theory, highlighted the crucial role of free cations in this reaction. This study demonstrates the feasibility of tuning the concentration of free cations by varying the concentration of the IL solution, establishing the relationship between its microstructure and chemical reaction efficiency, thus providing vital information for the design and application of ILs.

Granule-based anaerobic ammonium oxidation (Anammox) is a promising biotechnology for wastewater treatments with extraordinary performance in nitrogen removal. However, traditional analytical methods often delivered an average activity of a bulk sample consisting of millions and even billions of Anammox granules with distinct sizes and components. Here, we developed a novel technique to monitor the biochemical activity of individual Anammox granules in real-time by recording the production rate of nitrogen gas with a microbarometer in a sealed chamber containing only one granule. It was found that the specific activity of a single Anammox granule not only varied by tens of folds among different individuals with similar sizes (activity heterogeneity) but also revealed significant breath-like dynamics over time (temporal fluctuation). Statistical analysis on tens of individuals further revealed two subpopulations with distinct color and specific activity, which were subsequently attributed to the different expression levels of heme c content and hydrazine dehydrogenase activity. This study not only provides a general methodology for various kinds of gas-producing microbial processes but also establishes a bottom-up strategy for exploring the structural-activity relationship at a single sludge granule level, with implications for developing a better Anammox process.

Due to the poor plasma sputtering resistance of PVD thin-film plasma anemometer electrodes, the working life of the sensor is short and the repeatability of the output signal is poor, which greatly restricts the practical process of the plasma thin-film anemometer. Polymer-derived ceramics (PDCs) have excellent high-temperature mechanical properties, high-temperature stability, oxidation resistance, electrical properties, and superior processing and molding characteristics, which is expected to solve the above problem. In this article, we use PDCs to prepare plasma thin-film anemometers, and carry out a comparison experiment with PVD thin-film plasma anemometer. The results show that the PDCs thin-film plasma anemometer has better sputtering resistance, and can continue to work for more than 2.5 h at a current of $7\sim 8$ mA, and the signal fluctuation does not exceed 2.48%. Its high-temperature resistance is up to $900~^{\circ }$ C. In addition, we carried out static calibration and repeatability tests on the PDCs thin-film plasma anemometer. The speed measurement range can reach 150 m/s on the alumina substrate with a sensitivity of $16.7~\mu $ A/(m/s). After six rounds of outbound and return repeated tests, the error is controlled within 5%. By using PDCs process to prepare a plasma thin-film anemometer, the working life and signal repeatability of the sensor are greatly improved, which provides an important support for the development of a plasma thin-film anemometer.

Conventional LLC synchronous rectifier (SR) schemes use detection circuits to sense the signals of voltage or current. But it typically operates below 500 kHz, which is unsuitable for high-frequency applications as it may lose large SR duty cycle caused by high dv/dt and GaN devices usage. To address the serious challenge, a digital SR control using extended harmonics impedance model is proposed for GaN LLC converters. By building the impedance model, the SR on-time is calculated accurately in the microcontroller. It not only minimizes the on-time of SR body diode with high precision, but also owns high immunity. A 650-kHz 1.5-kW GaN LLC converter was built. With the output of 28 V/53.5 A, the efficiency is as high as 98.1% at 1.5 kW by using the proposed SR. The power density is also up to 524 W/in3. Compared to the conventional SR, the efficiency improves 1.6% at full load.

Cabozantinib, a tyrosine kinase inhibitor (TKI), is a prevalent second-line (2 L) therapy and was approved for use after progression on TKIs. However, the 1 L treatment setting has changed since the approval of cabozantinib monotherapy in salvage therapy settings. To assess the differential effectiveness of cabozantinib after prior progression on 1 L ipilimumab with nivolumab (IPI + NIVO) compared to programmed death receptor-1 (PD-1) or PD-1 ligand (PD-L1) inhibitors (PD1/L1i) with TKIs. Utilizing a nationwide electronic health record (EHR)-derived de-identified database, we included patients with metastatic clear cell renal cell carcinoma (mccRCC) who received 1 L treatment with an immune checkpoint inhibitor (ICI)-based combination and 2 L treatment with cabozantinib monotherapy. These patients were categorized based on the type of 1 L ICI-based combination received: IPI + NIVO vs. PD1/L1i with TKI. Real-world time to next therapy (rwTTNT) and real-world overall survival (rwOS) were summarized using Kaplan-Meier curves and compared using Cox-proportional hazard models adjusted for International mRCC Database Consortium (IMDC) risk groups. Among 12,285 patients with metastatic renal cell carcinoma, 237 were eligible and included. Median rwTTNT was 8 months for the IPI + NIVO subgroup and 7.5 months for the PD1/L1i + TKI subgroup (HR 1.05, 95% CI: 0.74–1.49, p = 0.8). Median rwOS was 17 months for IPI + NIVO and 16 months for PD1/L1i + TKI subgroup (HR 0.79, 95% CI: 0.52–1.20, p = 0.3). Cabozantinib remains effective as a 2 L therapy for mccRCC independent of the type of prior 1 L ICI-based combination. Further research is needed to validate these findings and explore the ideal sequencing of therapies.

To investigate the mesoscopic influence of surfactants on seepage law during water injection in coal seam, this paper innovatively establishes a fluid transport lattice Boltzmann (LBM) model by incorporating the seepage resistance generated from the porous media and external forces, which embodies the impact of wettability degree resulted from cocamidopropyl betaine (CAB), sodium dodecyl sulfate (SDS), and coconutt diethanol amide (CDEA) reagents at a 0.1% concentration. The main conclusions derived from this investigation are as follows: Firstly, as the lattice number in the X direction increases, the average seepage velocities in coal samples treated by deionized water, 0.1% CAB, 0.1% SDS, and 0.1% CDEA reagents (Nos. 1, 2, 3, and 4) exhibit three distinct stages: rapid decline, slow decline, and steady decline; in comparison to raw coal sample, modified coal samples demonstrate decreases of 20.84%, 33.91%, and 61.70%, respectively. Secondly, the critical values of displacement pressure difference exist during the phenomenon that modified reagents spread out in the entire flow channel, which are 3.5, 3.5, and 5.2 MPa, respectively, for coal samples Nos. 2, 3, and 4; this signifies that surpassing these critical values help prevent issues such as blank belts within the wetting range and insufficient dust control. Finally, at a displacement pressure difference of 0.01 (lattice unit), the average velocity ratios for samples (Nos. 2, 3, and 4) are 0.78, 0.56, and 0.37 (lattice unit), respectively; notably, the water flow velocities in modified coal samples are lower compared to that in raw coal sample, indicating that the addition of surfactants impede the seepage process of water injection in coal seam. Moreover, when the displacement pressure difference reaches 0.03 (lattice unit), the velocity ratio of CDEA-modified coal sample exceeds 100%; this means that when the displacement pressure difference surpasses 15.6 MPa, the water injection effect of CDEA-modified coal sample begins to be improved. These research findings offer a theoretical basis for enhancing water injection technology in coal mines.

Background: Cabozantinib, a tyrosine kinase inhibitor (TKI), is a prevalent second-line (2 L) therapy and was approved for use after progression on TKIs. However, the 1 L treatment setting has changed since the approval of cabozantinib monotherapy in salvage therapy settings.Objective: To assess the differential effectiveness of cabozantinib after prior progression on 1 L ipilimumab with nivolumab (IPI + NIVO) compared to programmed death receptor-1 (PD-1) or PD-1 ligand (PD-L1) inhibitors (PD1/L1i) with TKIs.Methods: Utilizing a nationwide electronic health record (EHR)-derived de-identified database, we included patients with metastatic clear cell renal cell carcinoma (mccRCC) who received 1 L treatment with an immune checkpoint inhibitor (ICI)-based combination and 2 L treatment with cabozantinib monotherapy. These patients were categorized based on the type of 1 L ICI-based combination received: IPI + NIVO vs. PD1/L1i with TKI. Real-world time to next therapy (rwTTNT) and real-world overall survival (rwOS) were summarized using Kaplan-Meier curves and compared using Cox-proportional hazard models adjusted for International mRCC Database Consortium (IMDC) risk groups.Results: Among 12,285 patients with metastatic renal cell carcinoma, 237 were eligible and included. Median rwTTNT was 8 months for the IPI + NIVO subgroup and 7.5 months for the PD1/L1i + TKI subgroup (HR 1.05, 95% CI: 0.74–1.49, p= 0.8). Median rwOS was 17 months for IPI + NIVO and 16 months for PD1/L1i + TKI subgroup (HR 0.79, 95% CI: 0.52–1.20, p= 0.3).Conclusions: Cabozantinib remains effective as a 2 L therapy for mccRCC independent of the type of prior 1 L ICI-based combination. Further research is needed to validate these findings and explore the ideal sequencing of therapies.

To improve the accuracy of the state parameters estimation for distributed drive electric vehicles (DDEVs), a method for estimating the state parameters of DDEV based on permanent magnet synchronous motors’ (PMSMs) sensorless control is proposed in this article. First, aiming at the problem that the speed and rotor position of the PMSMs are difficult to obtain, a sensorless control method for PMSM based on the square root seventh-degree cubature quadrature Kalman filter with robust factor (RF-SR7thCQKF) algorithm is designed. The algorithm combines the seventh-order orthogonal sphere-radius criterion with Bayesian filtering to obtain the seventh-degree cubature quadrature Kalman filter (7thCQKF), which can obtain higher estimation accuracy than the third- and fifth-order criteria by increasing the number of sampling points. To further improve the stability and filtering accuracy, the orthogonal triangle (QR) decomposition is introduced of the 7thCQKF to ensure the semi-positive characterization of the covariance matrix, and the effect of the filtering accuracy degradation due to the large measurement value error is weakened by the introduction of the robust factor. Second, the hyperbolic tangent adaptive sliding mode observer (HT-ASMO) for tire forces observation is designed, and the HT-ASMO can attenuate the jitter frequency of the system, reduce the time to reach the sliding mode switching surface from any point, and effectively improve the estimation accuracy of the tire forces. Finally, the PMSMs with sensorless control are used as the drive motors of the DDEV, and the RF-SR7thCQKF algorithm is used to estimate the vehicle state parameters based on the four-degree-of-freedom vehicle dynamics model. After simulation and experimental verification, the vehicle state parameters estimation method based on the PMSMs’ sensorless control has a high estimation accuracy.

Agent-agnostic reinforcement learning aims to learn a universal control policy that can simultaneously control a set of robots with different morphologies. Recent studies have suggested that using the transformer model can address variations in state and action spaces caused by different morphologies, and morphology information is necessary to improve policy performance. However, existing methods have limitations in exploiting morphological information, where the rationality of observation integration cannot be guaranteed. We propose morphological adaptive transformer (MAT), a transformer-based universal control algorithm that can adapt to various morphologies without any modifications. MAT includes two essential components: functional position encoding (FPE) and morphological attention mechanism (MAM). The FPE provides robust and consistent positional prior information for limb observation to avoid limb confusion and implicitly obtain functional descriptions of limbs. The MAM enhances the attribute prior information of limbs, improves the correlation between observations, and makes the policy pay attention to more limbs. We combine observation with prior information to help policy adapt to the morphology of robots, thereby optimizing its performance with unknown morphologies. Experiments on agent-agnostic tasks in Gym MuJoCo environment demonstrate that our algorithm can assign more reasonable morphological prior information to each limb, and the performance of our algorithm is comparable to the prior state-of-the-art algorithm with better generalization.

In the foreseeable Intelligent Transportation System, Intelligent Connected Vehicles (ICVs) will play an important role in improving travel efficiency and safety. However, it is challenging for ICVs to support the resource-hungry autonomous driving applications due to the limitation of hardware computing power. Fortunately, the emergence of Multi-access Edge Computing helps overcome this limitation effectively. This paper addresses the vehicle-to-edge server computation offloading conundrum by optimizing the trade-offs in partial offloading and resource allocation. Proposing a distributed approach, this study confronts the multi-variable non-convex challenge directly by decoupling variables and deriving constraint-based bounds that guide the decisions for offloading and allocation. A novel low-complexity distributed algorithm is introduced that not only tends toward optimal but also demonstrates superior real-time applicability and efficiency, illustrated through enhanced performances both in simulated trials and genuine vehicular edge computing settings. The algorithm’s practical effectiveness addresses a notable gap between the theoretical models for computation offloading and actual real-life execution, reinforcing the soundness and relevance of the proposed method. Furthermore, its advanced integration with federated learning frameworks marks a leading-edge application, substantiating significant enhancements in computational efficiency and robustness.

The Long-read RNA-Seq Genome Annotation Assessment Project Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. Using different protocols and sequencing platforms, the consortium generated over 427 million long-read sequences from complementary DNA and direct RNA datasets, encompassing human, mouse and manatee species. Developers utilized these data to address challenges in transcript isoform detection, quantification and de novo transcript detection. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. Incorporating additional orthogonal data and replicate samples is advised when aiming to detect rare and novel transcripts or using reference-free approaches. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

Based on the existing pivot rules, the simplex method for linear programming is not polynomial in the worst case. Therefore, the optimal pivot of the simplex method is crucial. In this paper, we propose the optimal rule to find all the shortest pivot paths of the simplex method for linear programming problems based on Monte Carlo tree search. Specifically, we first propose the SimplexPseudoTree to transfer the simplex method into tree search mode while avoiding repeated basis variables. Secondly, we propose four reinforcement learning models with two actions and two rewards to make the Monte Carlo tree search suitable for the simplex method. Thirdly, we set a new action selection criterion to ameliorate the inaccurate evaluation in the initial exploration. It is proved that when the number of vertices in the feasible region is Cnm, our method can generate all the shortest pivot paths, which is the polynomial of the number of variables. In addition, we experimentally validate that the proposed schedule can avoid unnecessary search and provide the optimal pivot path. Furthermore, this method can provide the best pivot labels for all kinds of supervised learning methods to solve linear programming problems.

Winter wheat–summer maize cropping system in the North China Plain often experiences drought-induced yield reduction in the wheat season and rainwater and nitrogen (N) fertilizer losses in the maize season. This study aimed to identify an optimal interseasonal water- and N-management strategy to alleviate these losses. Four ratios of allocation of 360 kg N ha−1between the wheat and maize seasons under one-time presowing root-zone irrigation (W0) and additional jointing and anthesis irrigation (W2) in wheat and one irrigation after maize sowing were set as follows: N1 (120:240), N2 (180:180), N3 (240:120) and N4 (300:60). The results showed that under W0, the N3 treatment produced the highest annual yield, crop water productivity (WPC), and nitrogen partial factor productivity (PFPN). Increased N allocation in wheat under W0 improved wheat yield without affecting maize yield, as surplus nitrate after wheat harvest was retained in the topsoil layers and available for the subsequent maize. Under W2, annual yield was largest in the N2 treatment. The risk of nitrate leaching increased in W2 when N application rate in wheat exceeded that of the N2 treatment, especially in the wet year. Compared to W2N2, the W0N3 maintained 95.2% grain yield over two years. The WPCwas higher in the W0 treatment than in the W2 treatment. Therefore, following limited total N rate, an appropriate fertilizer N transfer from maize to wheat season had the potential of a “triple win” for high annual yield, WPCand PFPN in a water-limited wheat–maize cropping system.

Polycystic ovary syndrome (PCOS) is a highly heterogeneous and genetically complex endocrine disorder. Although the etiology remains mostly elusive, growing evidence suggests that abnormal changes of DNA methylation correlate well with systemic and tissue-specific dysfunctions in PCOS. Herein, a dehydroepiandrosterone-induced PCOS-like mouse model which has a similar metabolic and reproductive phenotype as human patients with PCOS was generated. It was used to experimentally validate the potential role of aberrant DNA methylation in PCOS in this study. Integrated DNA methylation and transcriptome analysis revealed the potential role of genomic DNA hypomethylation in transcription regulation of PCOS and identified several key candidate genes, including BMP4, Adcy7, Tnfaip3, and Fas, which were regulated by aberrant DNA hypomethylation. Moreover, i.p. injection of S-adenosylmethionine increased the overall DNA methylation level of PCOS-like mice and restored expression of the candidate genes to similar levels as the control, alleviating reproductive and metabolic abnormalities in PCOS-like mice. These findings provide direct evidence showing the importance of normal DNA methylation in epigenetic regulation of PCOS and potential targets for diagnosis and treatment of the disease.

Introduction: In patients with metastatic hormone-sensitive prostate cancer (mHSPC) undergoing intensified androgen deprivation therapy (ADT), not achieving an optimal PSA response, defined as PSA nadir >0.2 ng/ml (PSAsubOR) has been associated with worse survival outcomes in clinical trials (1)(10)(11). Here, we externally evaluate, the impact of optimal PSA response on survival outcomes in these patients and provide absolute PFS and OS measures in those with PSAsubORin the context of ADT intensification in real world setting. Methods: In this retrospective study, all consecutive patients with mHSPC who underwent intensified ADT treated at our institution, and whose outcomes data were available, were included. We classified patients based on their PSA nadir on treatment: those with a on treatment PSAOR(PSA nadir ≤0.2 ng/ml) versus PSAsubOR. Results: A total of 205 patients were eligible: 136 (66.3%) patients achieved PSAORversus 69 (33.7%) patients had PSAsubOR. Patients who experienced a PSAORhad significantly improved PFS and OS from the start of intensified ADT versus who did not: PFS was not reached (NR) versus 11 months (hazard ratio (HR) 0.20, P< 0.001) and OS was NR versus 38.9 months (HR 0.21, P< 0.001). Survival outcomes were poor with PSAsubORregardless of intensification with docetaxel or an ARPI (absolute PFS and OS measures for each group are provided in the text). Conclusion: Our study is the first to explore the negative impact of PSAsubORin patients with mHSPC undergoing intensified ADT in the real-world setting, and is the first to provide absolute PFS and OS in patients with PSAsubORreceiving ADT intensification with ARPIs or docetaxel outside of clinical trial setting. These data will aid with prognostication, patient counseling, and for designing future clinical trials for patients with PSAsubOR.

[Display omitted]

The solubilities of glutathione in four binary solvent mixtures (water + acetone, water + 1,4-dioxane, water + acetonitrile, and water + tetrahydrofuran) were measured using a dynamic laser monitoring method at temperatures ranging from 278.15 to 318.15 K. The molar fraction solubility of glutathione in the binary solvent increased with increasing water content and temperature. The modified Apelblat, CNIBS/R-K, Van’t Hoff–Jouyban–Acree, Apelblat–Jouyban–Acree, and NRTL were applied to calculate the solubility of glutathione in these mixtures. The relative average deviation and root-mean-square deviation indicated a good correlation between the experimental and model solubility data. In addition, the KAT-LSER model was used to evaluate the solvent effect in the solvent–solvent and solvent–solute interactions. The results showed that the nonspecific dipolarity/polarizability interactions between the solvent and the solute were the main influencing factors, followed by the hydrogen bonding interactions between the solvent and the solute.

The influences of aging temperatures (160–200 °C) and 8% pre-rolling on the mechanical properties, and microstructures of the creep-aged AA2050 alloys were investigated. The results show that for the solid-solutioned alloys after the creep aging, the strength increased with an increase of aging temperatures. The ultimate tensile strength (UTS) and yield strength (YS) reached the highest value of 527 and 484 MPa at 200 °C, respectively, although the elongation (EL) reduced to 10.8%. At expense of σ phases, the temperature increase promoted the dislocation accumulation and the dense precipitation of θ′ and T1phases, which increased the strength. It is noted that the strong oriented precipitation at 200 °C lost some strengthening effect. After the 8% pre-rolling, the strength of creep-aged alloys increased firstly and then decreased with the increase of temperature. The high strength (UTS = 574 MPa, YS = 535 MPa) at 180 °C was attributed to the dense precipitation of T1phases under the action of diffusion kinetic and thermodynamic driving force. When the temperature reached 200 °C, the activated ledge mechanism significantly thickened T1phases, thus decreasing the strength. The work revealed the critical roles of aging temperature and pre-rolling in tailoring precipitation behaviors and mechanical performance of Al–Li alloys, paving a way in designing creep-aged Al–Li alloys with the superb mechanical properties.

For the problem of the rotor position estimation and control accuracy of permanent magnet synchronous motor (PMSM), this paper proposes a PMSM sensorless based on radial basis function (RBF) neural network optimized Automatic disturbance rejection control (RBF-ADRC) and strong tracking filter (STF) improved square root generalized fifth-order cubature Kalman filter (SGHCKF-STF). The Automatic disturbance rejection control (ADRC) has strong robustness, but there are many parameters and difficult to adjust. Now we use RBF neural network to adjust the parameters in ADRC online so as to improve the robustness and anti-disturbance ability. In order to improve the estimation accuracy of rotor position and speed, the orthogonal triangle (QR) decomposition and STF are introduced on the basis of the generalized fifth-order cubature Kalman filter (GHCKF) to design the SGHCKF-STF algorithm that not only ensure the non-positive nature of the covariance matrix but also improve the ability to cope with sudden changes in state during the filtering process. Experimental results show that the combination of RBF-ADRC and SGHCKF-STF improve the sensorless control effect of the PMSM to some extent.

Dynamic speed guidance for vehicles in on-ramp merging zones is instrumental in alleviating traffic congestion on urban expressways. To enhance compliance with recommended speeds, the development of a dynamic speed-guidance mechanism that accounts for heterogeneity in human driving styles is pivotal. Utilizing intelligent connected technologies that provide real-time vehicular data in these merging locales, this study proposes such a guidance system. Initially, we integrate a multi-agent consensus algorithm into a multi-vehicle framework operating on both the mainline and the ramp, thereby facilitating harmonized speed and spacing strategies. Subsequently, we conduct an analysis of the behavioral traits inherent to drivers of varied styles to refine speed planning in a more efficient and reliable manner. Lastly, we investigate a closed-loop feedback approach for speed guidance that incorporates the driver’s execution rate, thereby enabling dynamic recalibration of advised speeds and ensuring fluid vehicular integration into the mainline. Empirical results substantiate that a dynamic speed guidance system incorporating driving styles offers effective support for human drivers in seamless mainline merging.