Lower Bound Research Articles

Toward digitally twinning the process of creating machine controller digital twins – A G-code generation scenario

This paper proposes BatchEGO, an extension of Efficient Global Optimization (EGO), in an active learning context for creating and maintaining digital twins (DT). The motivation for this study is to address the challenges of obtaining high-quality yet cost and time effective data for developing accurate DTs of machine tool controllers that are robust to noise and physical system changes. BatchEGO is employed to generate manufacturing recipes (G-codes) recursively and iteratively, based on the spatial constraints of the physical machine, providing G-code based data for DTs. BatchEGO Interm is also proposed that extends BatchEGO by sampling additional intermediate points on the generated trajectory, to improve convergence and accuracy of DTs. To account for the stochastic nature of proposed methods, a total of 70 experiments based around repetitions of 4 correlation functions, 3 acquisition functions, and 4 sampling schemes are used to evaluate the performance of both methods. The results showcase impressive and faster convergence, in terms of sum of squared errors, for BatchEGO Interm with specific settings producing highly accurate and smooth G-codes. For instance, BatchEGO Interm with Matérn 3/2 correlation function and acquisition function of lower confidence bound can reach an error range of 0.0026 within 3-5 iterations. The work demonstrates the novelty and potential of such frameworks for enhancing data quality and quantity for DTs. The importance of G-code generation for DTs is also highlighted, as it can enable better control and optimization of machine tools in various industrial applications. The paper also discusses the different approaches for stitching the sampled points into G-code and compares their accuracy and efficiency.

Accelerating material discovery with a threshold-driven hybrid acquisition policy-based Bayesian optimization

Advancements in materials play a crucial role in technological progress. However, the process of discovering and developing materials with desired properties is often impeded by substantial experimental costs, extensive resource utilization, and lengthy development periods. To address these challenges, modern approaches often employ machine learning (ML) techniques such as Bayesian Optimization (BO), which streamline the search for optimal materials by iteratively selecting experiments that are most likely to yield beneficial results. However, traditional BO methods, while beneficial, often struggle with balancing the trade-off between exploration and exploitation, leading to sub-optimal performance in accelerated material discovery processes. This paper introduces a novel Threshold-Driven UCB-EI Bayesian Optimization (TDUE-BO) method, which dynamically integrates the strengths of Upper Confidence Bound (UCB) and Expected Improvement (EI) acquisition functions to optimize the material discovery process. Unlike the classical BO, our method focuses on efficiently navigating the high-dimensional material design space (MDS). TDUE-BO begins with an exploration-focused UCB approach, ensuring a comprehensive initial sweep of the MDS. As the model gains confidence, indicated by reduced uncertainty, it transitions to the more exploitative EI method, focusing on promising areas identified earlier. The UCB-to-EI switching policy, which is steered by ongoing monitoring of model uncertainty at each stage of sequential sampling, enables more efficient navigation through the MDS while guaranteeing quicker convergence. The effectiveness of TDUE-BO is demonstrated through its application on three different material science datasets, showing significantly better approximation and optimization performance over traditional EI and UCB-based BO methods in terms of the RMSE scores and convergence efficiency, respectively.

Neoadjuvant radiotherapy and endocrine therapy for oestrogen receptor positive breast cancers: the Neo-RT feasibility study

AimsTo establish safety and feasibility of delivering neoadjuvant radiotherapy and endocrine therapy for oestrogen receptor positive breast cancers with palpable size 20mm or greater, for which radiotherapy might facilitate more conservative surgery. Materials and MethodsA single arm feasibility study was conducted. Patients received whole breast radiotherapy with or without radiotherapy to nodal areas. Dose/fractionation was 40Gy in 15 fractions over 3 weeks, with or without either simultaneous integrated boost to 48Gy, or sequential boost, to the tumour bed. This was followed by endocrine treatment for 20 weeks, then surgery. The primary endpoint of the study was proportion of patients successfully completing neo-adjuvant radiotherapy and endocrine treatment followed by breast surgery. Response and toxicity endpoints including mastectomy rate, peri/postoperative complications, and pathological response were also evaluated.The primary analysis is descriptive. The study regimen would be considered feasible if more than 70% of patients completed treatment, while it might not be considered feasible if less than 50% did so. With a one sided 5% significance level and 80% power, a maximum of 43 patients would be required to detect a rate of ≤50% vs ≥70%. Results14 patients were recruited of the planned 43. Due to slow recruitment particularly during the COVID-19 pandemic, the decision was made to stop the trial in October 2021. One registered patient was found to be ineligible before starting treatment. 13/13 patients (100%, 90% CI: 75.3%, 100%) who received any trial treatment successfully completed all trial treatments. The lower bound of the Clopper-Pearson (exact) 90% confidence interval was 79%, indicating that the primary endpoint would have been met if the planned recruitment had been achieved. 3/13 patients underwent mastectomy. 7/13 had more conservative surgery than had been planned at baseline. 4/13 patients experienced any peri/postoperative complication. The only acute radiotherapy toxicities reported were grade 1/2 dermatitis and grade 1 fatigue. Long term breast outcomes were clinician assessed as none/mild at all timepoints in 12/13 patients. All tumours showed evidence of some pathological response to treatment, but none had pathological complete response. ConclusionsThis treatment schedule is likely feasible. It is difficult to draw strong conclusions on safety/toxicity given the small numbers, but these seem in keeping with other recent reports of neoadjuvant breast radiotherapy.

Efficacy and Safety of Roxadustat for Anemia in Patients Receiving Chemotherapy for Nonmyeloid Malignancies: A Randomized, Open-Label, Active-Controlled Phase III Study.

We evaluated the efficacy and safety of roxadustat, a first-in-class hypoxia-inducible factor prolyl hydroxylase inhibitor, for chemotherapy-induced anemia (CIA) in patients with nonmyeloid malignancies receiving multicycle treatments of chemotherapy. In this open-label, noninferiority phase III study conducted at 44 sites in China, 159 participants age ≥18 years with CIA nonmyeloid malignancy and CIA were randomly assigned (1:1) to oral roxadustat or subcutaneous recombinant human erythropoietin-α (rHuEPO-α) three times a week for 12 weeks. Roxadustat starting dosages were 100, 120, and 150 mg three times a week for participants weighing 40-<50, 50-60, and >60 kg, respectively. rHuEPO-α starting dosage for all participants was 150 IU/kg three times a week. Both roxadustat and rHuEPO-α dosages could be modified. The primary end point was least-squares mean (LSM) change in hemoglobin (Hb) concentration from baseline to the concentration averaged over weeks 9-13. Of the 159 participants randomly assigned, 140 were included in the per-protocol set (roxadustat, n = 78; rHuEPO-α, n = 62). The LSM (95% two-sided CI) change from baseline to weeks 9-13 in Hb concentration was 17.1 (13.58 to 20.71) g/L with roxadustat and 15.4 (11.34 to 19.50) g/L with rHuEPO-α (mean difference [95% CI], 1.7 [-3.39 to 6.84]). The lower bound of the one-sided 97.5% CI for the treatment difference (‒3.4 g/L) was greater than the predefined noninferiority margin of ‒6.6 g/L, establishing noninferiority. Noninferiority was supported by five of six key secondary end points. Rates of adverse events were generally comparable between treatments and consistent with previous findings. Roxadustat was noninferior to rHuEPO-α in treating CIA in participants with nonmyeloid malignancies receiving multicycle treatments of myelosuppressive chemotherapy. The oral formulation of roxadustat may potentially increase compliance.

Research on the Markov-Chain State Interval Division Based on Predicted Data Correction

By 2022, the total length of roads in Tibet Autonomous Region reached 121,447 kilometers. Due to the unique geological conditions in Tibet, various natural disasters such as earthquakes, mudslides, landslides, avalanches, and strong winds frequently occur. Along the Sichuan-Tibet Highway alone, over 300 disasters happen each year, significantly impacting the region’s economic development. This study focuses on the complexity and randomness of natural disaster mechanisms and combines Markov chain theory to improve the accuracy of prediction data for mudslides, landslides, and earth subsidence etc. The main method is to modify the state interval of the prediction model parameter-Markov chain based on the distribution of discrete points on the number axis. The following state interval division methods are proposed: (1) If the relative error of the predicted value exceeds 50%, adjust the prediction model. (2) Obtain the lower bound of state E1 by taking the floor value downward. (3) The width of each interval does not need to be uniform. (4) Arrange continuous, dense, and close points on the number line in the same side in batches, and represent a state continuously, dividing it into one suitable interval or batches. Using this method, an improved RMSE of 0.28mm and MAPE of 0.87% were obtained for engineering examples, outperforming other models such as GM(1,1), Verhulst, DGM(2,1) with corresponding RMSE values of 0.86 mm, 0.69 mm, and 1.38 mm, and MAPE values of 2.75%, 2.53%, and 5.99%. The combined prediction results for five sets of data yielded an RMSE of 0.14 mm and MAPE of 0.56%, which are quite close to the results obtained using Markov selection correction with an RMSE of 0.37 mm and MAPE of 1.01%. Furthermore, comparing the four sets of case, the average reduction in RMSE and MAPE is 3.56mm and 1.72%, respectively, demonstrating that this method can further improve the performance of Markov chain prediction.

Generalizing Determinacy under Monetary and Fiscal Policy Switches: The Case of the Zero Lower Bound

AbstractIn a fixed‐regime context, it has been established since the work of Leeper (1991) that a determinate and unique equilibrium can be achieved under both monetary dominance (characterized by an active monetary policy and a passive fiscal policy) and fiscal dominance (characterized by an active fiscal policy and a passive monetary policy) regimes yield a determinate unique equilibrium. In this paper, we generalize this well‐established policy‐mix taxonomy to regime‐switching models, and show that switches from monetary dominance to fiscal dominance regimes (and vice versa) render the economy indeterminate for standard parameter values. We apply our results to the important case of the exit from the zero lower bound (ZLB), where monetary policy is inherently passive. Contrary to the fixed‐regime prediction, the economy switching between the ZLB in a fiscally led regime and a monetary dominance regime is robustly indeterminate, making the coordination of agents' beliefs hard for anchoring expected inflation. Finally, we propose a direction toward which the perspective of the fiscal theory of the price level can be made consistent with a unique stable equilibrium.

Critical Thinking Evaluation Scale: Design and Validation in a Colombian Population

Critical thinking stands out as one of the most important cognitive abilities needed for effective adaptation to a knowledge-based society in the 21st century. Despite its significance, there remains a lack of consensus regarding the conceptual and methodological frameworks for measuring it. This study aimed to design and validate a comprehensive assessment scale for critical thinking. A specification table was constructed based on the critical thinking components agreed upon in the current literature, from which corresponding items were formulated and subsequently validated by expert judges. Following adjustments to the test, 258 Colombian participants completed it. Sample adequacy (KMO), Bartlett’s sphericity, and collinearity were confirmed, and the results underwent exploratory factor analysis. Reliability analysis was conducted using McDonald’s ω, Cronbach’s α, Guttman’s λ6, and Greatest Lower Bound (GLB) statistics. The final test comprised 17 items organized into 2 constituent factors, demonstrating robust content and internal structure validity, as well as high levels of precision and internal consistency (overall GLB of .93). The Critical Thinking Evaluation Scale (CTES) exhibits validity and reliability for use within the Colombian population. Its adaptation for other contexts and countries, both Spanish and English-speaking, is recommended. The Spanish version, along with the validated English version for potential adaptations, and scoring norms are provided in the attached documents.

Human papillomavirus nonavalent (HPV9) vaccination and risk of immune mediated diseases, myocarditis, pericarditis, and thromboembolic outcomes in Denmark: self-controlled case series study

ObjectiveTo assess the associations between vaccination with the nonavalent human papillomavirus (HPV9) vaccine and immune mediated diseases, myocarditis, pericarditis, arterial thromboembolism, and venous thromboembolism with or without thrombocytopenia, in adolescent...

A multicenter study to evaluate the analytical precision by pathologists using the Aperio GT 450 DX

BackgroundDigital pathology systems (DPS) are emerging as capable technologies for clinical practice. Studies have analyzed pathologists' diagnostic concordance by comparing reviews of whole slide images (WSIs) to glass slides (e.g., accuracy). This observational study evaluated the reproducibility of pathologists' diagnostic reviews using the Aperio GT 450 DX under slightly different conditions (precision). MethodDiagnostic precision was tested in three conditions: intra-system (within systems), inter-system/site (between systems/sites), and intra- and inter-pathologist (within and between pathologists). A total of five study/reading pathologists (one pathologist each for intra-system, inter-system/site, and three for intra-pathologist/inter-pathologist analyses) were assigned to the respective sub-studies.A panel of 69 glass slides with 23 unique histological features was used to evaluate the WSI system's precision. Each glass slide was scanned to generate a unique WSI. From each WSI, the field of view (FOV) was generated (at least 2 FOVs/WSI), which included the selected features (1–3 features/FOV). Each pathologist reviewed the digital slides and identified which morphological features, if any, were present in each defined FOV. To minimize recall bias, an additional 12 wild card slides from different organ types were used for which FOVs were extracted. The pathologists also read these wild card slides FOVs; however, the corresponding feature identification was not included in the final data analysis. ResultsEach measured endpoint met the pre-defined acceptance criteria of the lower bound of the 95% confidence interval (CI) overall agreement (OA) rate being ≥85% for each sub-study. The lower bound of the 95% CI for the intra-system OA rate was 95.8%; for inter-system analysis, it was 94.9%; for intra-pathologist analysis, 92.4%, whereas for inter-pathologist analyses, the lower bound of the 95% CI of the OA was 90.6%. ConclusionThe study results indicate that pathologists using the Aperio GT 450 DX WSI system can precisely identify histological features that may be required for accurately diagnosing anatomic pathology cases.

ISAC‐oriented access point placement in cell‐free mMIMO systems

AbstractIn mobile communication networks for integrated sensing and communication, site planning of access points fundamentally determines both communication quality and sensing performance. This paper aims to tackle the AP placement problem under the setting of cell‐free massive multiple‐input multiple‐output, which represents a promising direction for network architecture evolution. Seeking a balance between the sum‐throughput of communication and the Cramér–Rao lower bound of target sensing, the access points are first pre‐placed by solving a convex optimization and further adjusted with optimal angular geometry. The final step involves employing nearest neighbour projection to refine access point positions in the cell‐free massive multiple‐input multiple‐output system, ensuring alignment with integrated sensing and communication requirements. The numerical results show that the proposed algorithm achieves 90% of the optimal communication sum‐rate and 95% of the optimal target localization accuracy.

On the Consistency and Large-Scale Extension of Multiple Kernel Clustering.

Existing multiple kernel clustering (MKC) algorithms have two ubiquitous problems. From the theoretical perspective, most MKC algorithms lack sufficient theoretical analysis, especially the consistency of learned parameters, such as the kernel weights. From the practical perspective, the high complexity makes MKC unable to handle large-scale datasets. This paper tries to address the above two issues. We first make a consistency analysis of an influential MKC method named Simple Multiple Kernel k-Means (SimpleMKKM). Specifically, suppose that ∧γn are the kernel weights learned by SimpleMKKM from the training samples. We also define the expected version of SimpleMKKM and denote its solution as γ*. We establish an upper bound of ||∧γn-γ*||∞ in the order of ~O(1/√n), where n is the sample number. Based on this result, we also derive its excess clustering risk calculated by a standard clustering loss function. For the large-scale extension, we replace the eigen decomposition of SimpleMKKM with singular value decomposition (SVD). Consequently, the complexity can be decreased to O(n) such that SimpleMKKM can be implemented on large-scale datasets. We then deduce several theoretical results to verify the approximation ability of the proposed SVD-based method. The results of comprehensive experiments demonstrate the superiority of the proposed method.

A novel adaptive parameter zeroing neural network for the synchronization of complex chaotic systems and its field programmable gate array implementation

This article proposes a novel adaptive-parameter zeroing neural network (NAP-ZNN) to control the synchronization of complex chaotic systems. Different from previous zeroing neural networks (ZNNs), the NAP-ZNN model incorporates adaptive-parameter, a unique blend of time-varying convergence factor and fuzzy control parameter, which is adjusted continuously according to the real-time synchronizing error, offering greater flexibility. The NAP-ZNN model aims to address the time-varying problem in complex-valued domain, which is scarcely explored, it rapidly impels two complex chaotic systems to synchronize within predetermined time and effectively mitigates noise interference. Moreover, the upper bound of the convergence time is theoretically calculated in noiseless environments, and the disturbance-resistant property is demonstrated under various noisy disturbances. The control performance of NAP-ZNN model has been separately compared to other general ZNNs (NAP-ZNN synchronizes at 0.097 s while three general ZNNs spend 0.43 s, 0.78 s and 0.84 s, and only NAP-ZNN complete synchronization within 0.1 s under noisy interferences while general ZNNs fail) and the traditional adaptive control method through two synchronization simulation (RMSE of NAP-ZNN under sinusoidal noise is 3.165 × 10-3 while traditional is 3.383 at t = 1 s). The numerical outcomes clearly illustrate the superior performance of the NAP-ZNN model in comparison to other synchronization strategies. The hardware implementation of the NAP-ZNN model has been successfully realized through the Field Programmable Gate Array (FPGA), and the chaos synchronization process has been vividly captured via an oscilloscope, further reinforcing the practicality and effectiveness of the NAP-ZNN model.

Unexpected asymmetric distribution of cholesterol and phospholipids in equilibrium model membranes

Lipid compositional asymmetry across the leaflets of the plasma membrane is a ubiquitous feature in eukaryotic cells. How this asymmetry is maintained is thought to be primarily controlled by active transport of lipids between leaflets. This strategy is facilitated by the fact that long tail phospholipids and sphingolipids diffuse through the lipid bilayer slowly – taking many hours or days. However, a lipid like cholesterol – which is the most abundant lipid in the plasma membrane of animal cells – has been harder to pin-point in terms of its favored side. In the present work we show that when a saturated lipid is added to a mix of the unsaturated lipid palmitoyl-oleoyl-phosphatidylcholine (POPC) and cholesterol, both cholesterol and the long tail phospholipids organize asymmetrically across the membrane’s leaflets naturally. In these extruded unilamellar vesicles, most cholesterol as well as the saturated lipid – dipalmitoylphosphatidylcholine (DPPC) or sphingomyelin (SM) – segregated to the inner leaflet while POPC preferentially localized in the outer leaflet. This asymmetric arrangement generated a slight phospholipid number imbalance favoring the outer leaflet and thus opposite to where cholesterol and the saturated lipids preferentially partitioned. These results were obtained using Magic Angle Spinning (MAS) NMR in combination with Small Angle Neutron Scattering (SANS) using isotope labeling to differentiate lipid species. We suggest that sidedness in membranes can be driven by thermodynamic processes. In addition, our MAS NMR results show that the lower bound for cholesterol’s flip-flop half-time at 45°C is 10ms, which is at least two orders of magnitude slower than current MD simulations predict. This result stands in stark contrast to previous work that suggested that cholesterol’s flip-flop half-time at 37°C has an upper bound of 10ms.

VFLGAN: Vertical Federated Learning-based Generative Adversarial Network for Vertically Partitioned Data Publication

In the current artificial intelligence (AI) era, the scale and quality of the dataset play a crucial role in training a high-quality AI model. However, good data is not a free lunch and is always hard to access due to privacy regulations like the General Data Protection Regulation (GDPR). A potential solution is to release a synthetic dataset with a similar distribution to that of the private dataset. Nevertheless, in some scenarios, it has been found that the attributes needed to train an AI model belong to different parties, and they cannot share the raw data for synthetic data publication due to privacy regulations. In PETS 2023, Xue et al. [29] proposed the first generative adversary network-based model, VertiGAN, for vertically partitioned data publication. However, after thoroughly investigating, we found that VertiGAN is less effective in preserving the correlation among the attributes of different parties. This article proposes a Vertical Federated Learning-based Generative Adversarial Network, VFLGAN, for vertically partitioned data publication to address the above issues. Our experimental results show that compared with VertiGAN, VFLGAN significantly improves the quality of synthetic data. Taking the MNIST dataset as an example, the quality of the synthetic dataset generated by VFLGAN is 3.2 times better than that generated by VertiGAN w.r.t. the Frechet Distance. We also designed a more efficient and effective Gaussian mechanism for the proposed VFLGAN to provide the synthetic dataset with a differential privacy guarantee. On the other hand, differential privacy only gives the upper bound of the worst-case privacy guarantee. This article also proposes a practical auditing scheme that applies membership inference attacks to estimate privacy leakage through the synthetic dataset.

GNSS positioning uncertainty prediction over a planned path considering signal attenuation for urban autonomous driving

Autonomous driving requires path planning to choose an optimal path to destination. Most works on path planning focus on the shortest travelling time, but neglect positioning condition of a path while positioning accuracy is significant for autonomous driving. In this work, we predict GNSS protection level (PL), which is positioning uncertainty upper bound, over planned paths to help choose the optimal path. We propose an improved stochastic model that considers the signal attenuation caused by trees and buildings using laser scanning point cloud. An adaptive strategy is proposed to linearly correlate the improved model and the carrier-to-noise-density ratio to make our stochastic model more practical. Finally, pseudorange-based RTD PL is calculated by advanced receiver autonomous integrity monitoring (ARAIM) using the planned path information and GNSS ephemeris. The experiments demonstrate that our method reduces the misleading rate by over 90% both in horizontal and vertical directions compared to the original stochastic model, with the lowest false alarm rates.

A Switching Memory-Based Event-Trigger Scheme for Synchronization of Lur'e Systems With Actuator Saturation: A Hybrid Lyapunov Method.

This article is concerned with the event-triggered synchronization of Lur'e systems subject to actuator saturation. Aiming at reducing control costs, a switching-memory-based event-trigger (SMBET) scheme, which allows a switching between the sleeping interval and the memory-based event-trigger (MBET) interval, is first presented. In consideration of the characteristics of SMBET, a piecewise-defined but continuous looped-functional is newly constructed, under which the requirement of positive definiteness and symmetry on some Lyapunov matrices is dropped within the sleeping interval. Then, a hybrid Lyapunov method (HLM), which bridges the gap between the continuous-time Lyapunov theory (CTLT) and the discrete-time Lyapunov theory (DTLT), is used to make the local stability analysis of the closed-loop system. Meanwhile, using a combination of inequality estimation techniques and the generalized sector condition, two sufficient local synchronization criteria and a codesign algorithm for the controller gain and triggering matrix are developed. Furthermore, two optimization strategies are, respectively, put forward to enlarge the estimated domain of attraction (DoA) and the allowable upper bound of sleeping intervals on the premise of ensuring local synchronization. Finally, a three-neuron neural network and the classical Chua's circuit are used to carry out some comparison analyses and to display the advantages of the designed SMBET strategy and the constructed HLM, respectively. Also, an application to image encryption is provided to substantiate the feasibility of the obtained local synchronization results.

Bivariate iterated Farlie–Gumbel–Morgenstern stress–strength reliability model for Rayleigh margins: Properties and estimation

In this paper, we propose bivariate iterated Farlie–Gumbel–Morgenstern (FGM) due to [Huang and Kotz (1984). Correlation structure in iterated Farlie-Gumbel-Morgenstern distributions. Biometrika 71(3), 633–636. https://doi.org/10.2307/2336577] with Rayleigh marginals. The dependence stress–strength reliability function is derived with its important reliability characteristics. Estimates of dependence reliability parameters are obtained. We analyse the effects of dependence parameters on the reliability function. We found that the upper bound of the positive correlation coefficient is attaining to 0.41 under a single iteration with Rayleigh marginals. A comprehensive comparison between classical FGM with iterated FGM copulas is graphically examined to assess the over or under estimation of reliability with respect to α and β. We propose a two-phase estimation procedure for estimating the reliability parameters. A Monte-Carlo simulation study is conducted to assess the finite sample behaviour of the proposed reliability estimators. Finally, the proposed estimators are examined and validated with real data sets.

Maleimide-induced crosslinking of polyimide membranes for high gas separation performance and plasticization resistance

Trade-off effect and plasticization are the key issues confronted in the area of membrane separation when dealing with applications involving high-pressure, soluble gases like CO2. In this study, a novel diamine (TAPA-MAA) was synthesized derived from tris(4-aminophenyl)amine (TAPA) and maleic anhydride (MA). This diamine was copolymerized with DAM (2,4,6-trimethylbenzene-1,3-diamine) and 6FDA (4,4′-(hexafluoroisopropylidene)diphthalic anhydride) to form the polyimide (PI) membrane containing maleimide (MI) cross-linking sites via chemical imidization way. Then, under the action of heat treatment, the crosslinked PI (cPI) membrane was constructed since the MI crosslinking initiates a radical cycloaddition reaction to form a succinimide-linked structure, and named as cPSI membrane for short. Further, an increase in the ratio of TAPA-MAA gives rise to the resultant cPSI membrane with elevated cross-linking density. The obtained cPSI membranes showed significantly enhanced gas selectivities and superior anti-plasticization property compared to the un-crosslinked PI membranes due to the MI-induced crosslinking reaction in the PI main chain, resulting in a marked increment (24 %) in ultra-microporosity (<7 Å) and a reduction in the d-spacing value (6.10 Å vs 5.80 Å), generating a strong molecular sieving effect. Meanwhile, the highly interconnected covalent structure formed by the MI-induced crosslinking will suppress the plasticizing phenomenon induced by high-pressure soluble gases. The typical membrane (cPSI-3:7-350) possessed great CO2/CH4 separation performance, CO2 permeability of 334.4barrer and a CO2/CH4 selectivity of 61.9 that is exceeded the 2008Roberson upper bound, along withCO2 plasticization pressures above 44 bar. Besides, its mixed CO2/CH4 separation performance exceeded the 2018 upper gas mixture limit when the upstream pressure changed from 2-20 bar. This study provides valuable insights for the design of PIs containing MI cross-linking sites, which can enhance the performance of membrane-based gas separation.

Finite-Time Stability Analysis and Stabilization of Switched Affine Systems via an Event-Triggered Strategy.

This article investigates the finite-time control problem of the switched affine systems via an event-triggered strategy. It is well known that the existence of affine terms brings great difficulties in analysis of the finite-time property of such systems. Furthermore, the design of the globally feasible event-triggered mechanism (ETM) under a finite-time control framework is challenging. Thus, a two-step hybrid control scheme is proposed in this article. The first step focuses on the event-triggered finite-time control for practical stability, while the second step aims to achieve finite-time stabilization. Particularly, in step one, by constructing the intersection between the affine term's threshold and feasible state region of the established ETM, it is verified that the Zeno behavior can be excluded. Thereafter, an affine state-dependent switching law and sufficient conditions are provided for achieving practical stability. Meanwhile, an estimation for the practical settling time to enter the bounded set is provided. In step two, the criteria for finite-time stabilization of the considered systems are further presented, and an overall settling-time upper bound is derived. Finally, a numerical example is illustrated to demonstrate the effectiveness of our proposed method.

Ultimate Regime of Rayleigh-Bénard Turbulence: Subregimes and Their Scaling Relations for the Nusselt vs Rayleigh and Prandtl Numbers.

We offer a new model for the heat transfer and the turbulence intensity in strongly driven Rayleigh-Bénard turbulence (the so-called ultimate regime), which in contrast to hitherto models is consistent with the new mathematically exact heat transfer upper bound of Choffrut etal. [Upper bounds on Nusselt number at finite Prandtl number, J. Differ. Equations 260, 3860 (2016).JDEQAK0022-039610.1016/j.jde.2015.10.051] and thus enables extrapolations of the heat transfer to geo- and astrophysical flows. The model distinguishes between four subregimes of the ultimate regime and well describes the measured heat transfer in various large-Rayleigh experiments. In this new representation, which properly accounts for the Prandtl number dependence, the onset to the ultimate regime is seen in all available large-Rayleigh datasets, though at different Rayleigh numbers, as to be expected for a non-normal-nonlinear instability.