Strong Memory Effects Research Articles

A Low-Computational-Complexity Digital Predistortion Model for Wideband Power Amplifier

This paper proposes a Composition Piecewise Memory Polynomial (CPMP) digital predistortion model based on a Vector Switched (VS) behavioral model to address the challenges of severe nonlinearity and strong memory effects in wideband power amplifiers (PAs). To tackle this issue, two thresholds are calculated and used to segment the envelope values of the input signal according to the nonlinear distortion characteristics of the PA. In this approach, a Generalized Memory Polynomial (GMP) model is employed for the lower segment, a Memory Polynomial (MP) model is employed for the middle segment, and a higher-order GMP model is employed for the upper segment. By sharing the fundamental MP among the proposed segmented models and leveraging a design methodology that configures different cross terms, memory depths, and polynomial orders for each segment, this model achieves superior linearization performance while simultaneously reducing the computational complexity associated with model extraction. The experimental results demonstrate that the adjacent channel power ratio (ACPR) of the predistorted PA output signal using the proposed model improves from −36 dBc to −54 dBc, matching the performance of the GMP model. Furthermore, this performance is 0.5 dBc better than the Piecewise Dynamic Deviation Reduction (PDDR) and Decomposed Vector Rotation (DVR) models. Notably, the complexity of the proposed parameter extraction process is 28.8% of the DVR model, 21.79% of the GMP model, and 12.83% of the PDDR model.

Ultrasound-triggered and glycosylation inhibition-enhanced tumor piezocatalytic immunotherapy.

Nanocatalytic immunotherapy holds excellent potential for future cancer therapy due to its rapid activation of the immune system to attack tumor cells. However, a high level of N-glycosylation can protect tumor cells, compromising the anticancer immunity of nanocatalytic immunotherapy. Here, we show a 2-deoxyglucose (2-DG) and bismuth ferrite co-loaded gel (DBG) scaffold for enhanced cancer piezocatalytic immunotherapy. After the implantation in the tumor, DBG generates both reactive oxygen species (ROS) and piezoelectric signals when excited with ultrasound irradiation, significantly promoting the activation of anticancer immunity. Meanwhile, 2-DG released from ROS-sensitive DBG disrupts the N-glycans synthesis, further overcoming the immunosuppressive microenvironment of tumors. The synergy effects of ultrasound-triggered and glycosylation inhibition enhanced tumor piezocatalytic immunotherapy are demonstrated on four mouse cancer models. A "hot" tumor-immunity niche is produced to inhibit tumor progress and lung metastasis and elicit strong immune memory effects. This work provides a promising piezocatalytic immunotherapy for malignant solid tumors featuring both low immunogenicity and high levels of N-glycosylation.

Behavioral modeling of LMBA with different back‐off state using PSO optimized XGBoost method

AbstractIn this paper, an optimization technique based on the particle swarm optimization (PSO) algorithm is applied to the eXtreme gradient boosting (XGBoost) method for load modulated balanced amplifiers (LMBAs) modeling, taking into consideration both strong nonlinearity and memory effects. An overview of the basic principles of the proposed modeling technique is provided, as well as a detailed description of how the model is extracted. To improve the performance of the XGBoost model, the hyperparameters are optimized using the PSO algorithm. An in‐house designed LMBA was used to perform experimental validation, which demonstrated that the new PSO‐XGBoost model provided very efficient and extremely accurate predictions, especially in the case of strong nonlinearities. When compared to traditional Volterra models, canonical piecewise‐linear based models, and standard XGBoost models, the proposed PSO‐XGBoost model provides improved performance with reasonable complexity.

Long-lived isospin excitations in magic-angle twisted bilayer graphene.

Numerous correlated many-body phases, both conventional and exotic, have been reported in magic-angle twisted bilayer graphene (MATBG)1-24. However, the dynamics associated with these correlated states, crucial for understanding the underlying physics, remain unexplored. Here we combine exciton sensing and optical pump-probe spectroscopy to investigate the dynamics of isospin orders in MATBG with WSe2 substrate across the entire flat band, achieving sub-picosecond resolution. We observe remarkably slow isospin dynamics in a broad filling range around ν = 2 and between ν = -3 and -2, with lifetimes of up to 300 ps that decouple from the much faster cooling of electronic temperature (about 10 ps). This non-thermal behaviour demonstrates the presence of abnormally long-lived modes in the isospin degrees of freedom. This observation, not anticipated by theory, implies the existence of long-range propagating collective modes, strong isospin fluctuations and memory effects and is probably associated with an intervalley coherent or incommensurate Kekulé spiral ground state. We further demonstrate non-equilibrium control of the isospin orders previously found around integer fillings. Specifically, through ultrafast manipulation, it can be transiently shifted away from integer fillings. Our study demonstrates a unique probe of collective excitations in MATBG and paves the way for actively controlling non-equilibrium phenomena in moiré systems.

Flow-Induced Crystallization Coupled with Strong Memory Effect: Revealing Melt Heterogeneity

Flow-Induced Crystallization Coupled with Strong Memory Effect: Revealing Melt Heterogeneity

Wrecking neutrophil extracellular traps and antagonizing cancer-associated neurotransmitters by interpenetrating network hydrogels prevent postsurgical cancer relapse and metastases

Tumor-promoting niche after incomplete surgery resection (SR) can lead to more aggressive local progression and distant metastasis with augmented angiogenesis-immunosuppressive tumor microenvironment (TME). Herein, elevated neutrophil extracellular traps (NETs) and cancer-associated neurotransmitters (CANTs, e.g., catecholamines) are firstly identified as two of the dominant inducements. Further, an injectable fibrin-alginate hydrogel with high tissue adhesion has been constructed to specifically co-deliver NETs inhibitor (DNase I)-encapsulated PLGA nanoparticles and an unselective β-adrenergic receptor blocker (propranolol). The two components (i.e., fibrin and alginate) can respond to two triggers (thrombin and Ca2+, respectively) in postoperative bleeding to gelate, shaping into an interpenetrating network (IPN) featuring high strength. The continuous release of DNase I and PR can wreck NETs and antagonize catecholamines to decrease microvessel density, blockade myeloid-derived suppressor cells, secrete various proinflammatory cytokines, potentiate natural killer cell function and hamper cytotoxic T cell exhaustion. The reprogrammed TME significantly suppress locally residual and distant tumors, induce strong immune memory effects and thus inhibit lung metastasis. Thus, targetedly degrading NETs and blocking CANTs enabled by this in-situ IPN-based hydrogel drug depot provides a simple and efficient approach against SR-induced cancer recurrence and metastasis.

Photoactivated theranostic nanomaterials based on aggregation‐induced emission luminogens for cancer photoimmunotherapy

AbstractIn this study, a series of high liposoluble near‐infrared emissive aggregation‐induced emission luminogens with triphenylamine derivatives as donor units and 1‐indanone as electron acceptor units are developed. Specifically, MTTOI has promising lipid droplets targeting ability and viscosity‐response characteristics, and it can monitor the viscosity fluctuations in living cells in real time. It is found that MTTOI is able to fulfill the activation of the apoptosis‐related signaling pathways under white light, and it can also activate the ferroptosis to synergize apoptosis resulting in tumor elimination. Interestingly, the occurrence of ferroptosis is positively related to the enhancement of immunogenic cell‐death effect, thus boosting the tumor infiltration of CD8+ T cells and reducing the proportion of regulatory T cells by cooperating with dendritic cells, which can not only carry out primary antitumor treatment, but also prevent tumor metastasis through strong immunological memory effect. Moreover, in vivo experimental results confirm that MTTOI successfully effectuates fatty liver tissue imaging. MTTOI fluorescence signals can be captured at the tumor site after 3 days of administration due to its high fat‐solubility and ease of fusion with tumors. This classic example could promote the further development of phototherapeutic agents in preclinical research and clinical applications.

Developing a fuzzy logic-based carbon emission cost-incorporated inventory model with memory effects

Inventory control is a widely discussed topic in the real world, and recently, it has become closely linked to concerns about carbon emissions and global warming. Global warming is a pressing issue, mainly due to a lack of awareness and action. Traditional inventory models, which typically use integer-order differential equations, overlook the memory aspect of the system. Addressing inventory management is essential in our efforts to combat global warming. This paper introduces a novel approach by incorporating carbon emission costs within a fuzzy environment. Fractional Calculus, a powerful mathematical tool, is employed to capture the memory effect of the system. This approach distinguishes between long memory, characterized by a strong memory effect, and short memory, associated with a poor memory effect, through the use of fractional derivatives and integrals. Numerical results are analyzed based on these memory concepts. Entrepreneurs often find it difficult to determine exact values for known parameters in the real world. Therefore, this study considers the uncertain nature of ordering costs, the rate of deterioration, and demand rates as triangular fuzzy numbers. The optimal average cost and ordering intervals are determined using a solution methodology. A sensitivity analysis is performed to demonstrate how different system parameters influence the outcomes within a fuzzy environment. Notably, it is observed that profit tends to be higher under conditions of strong memory compared to poor memory effects. Moreover, it's worth emphasizing that profits are notably more favorable when employing the signed distance method compared to the graded mean integration method, especially in situations marked by strong memory effects. This study highlights the importance of considering sensitive parameters in the model, especially under conditions of strong memory effects. Such parameters require careful attention in the pursuit of effective inventory management strategies to mitigate carbon emissions and combat global warming.

Chemically Specific Systematic Coarse-Grained Polymer Model with Both Consistently Structural and Dynamical Properties.

The coarse-grained (CG) model serves as a powerful tool for the simulation of polymer systems; its reliability depends on the accurate representation of both structural and dynamical properties. However, strong correlations between structural and dynamical properties on different scales and also a strong memory effect, enforced by chain connectivity between monomers in polymer systems, render developing a chemically specific systematic CG model a formidable task. In this study, we report a systematic CG approach that combines the iterative Boltzmann inversion (IBI) method and the generalized Langevin equation (GLE) dynamics. Structural properties are ensured by using conservative CG potentials derived from the IBI method. To retrieve the correct dynamical properties in the system, we demonstrate that using a combination of a Rouse-type delta function and a time-dependent short-time kernel in the GLE simulation is practically efficient. The former can be used to adjust the long-time diffusion dynamics, and the latter can be reconstructed from an iterative procedure according to the velocity autocorrelation function (ACF) from all-atomistic (AA) simulations. Taking the polystyrene as an example, we show that not only structural properties of radial distribution function, intramolecular bond, and angle distributions can be reproduced but also dynamical properties of mean-square displacement, velocity ACF, and force ACF resulted from our CG model have quantitative agreement with the reference AA model. In addition, reasonable agreements are observed in other collective properties between our GLE-CG model and the AA simulations as well.

The Influence of Thermal Parameters on the Self-Nucleation Behavior of Polyphenylene Sulfide (PPS) during Secondary Thermoforming.

During the secondary thermoforming of carbon fiber-reinforced polyphenylene sulfide (CF/PPS) composites, a vital material for the aerospace field, varied thermal parameters profoundly influence the crystallization behavior of the PPS matrix. Notably, PPS exhibits a distinctive self-nucleation (SN) behavior during repeated thermal cycles. This behavior not only affects its crystallization but also impacts the processing and mechanical properties of PPS and CF/PPS composites. In this article, the effects of various parameters on the SN and non-isothermal crystallization behavior of PPS during two thermal cycles were systematically investigated by differential scanning calorimetry. It was found that the SN behavior was not affected by the cooling rate in the second thermal cycle. Furthermore, the lamellar annealing resulting from the heating process in both thermal cycles affected the temperature range for forming the special SN domain, because of the refined lamellar structure, and expelled various defects. Finally, this study indicated that to control the strong melt memory effect in the first thermal cycle, both the heating rate and processing melt temperature need to be controlled simultaneously. This work reveals that through collaborative control of these parameters, the crystalline morphology, crystallization temperature and crystallization rate in two thermal cycles are controlled. Furthermore, it presents a new perspective for controlling the crystallization behavior of the thermoplastic composite matrix during the secondary thermoforming process.

Biomimetic-gasdermin-protein-expressing nanoplatform mediates tumor-specific pyroptosis for cancer immunotherapy

Pyroptosis, mediated by gasdermin proteins, has shown excellent efficacy in facilitating cancer immunotherapy. The strategies commonly used to induce pyroptosis suffer from a lack of tissue specificity, resulting in the nonselective activation of pyroptosis and consequent systemic toxicity. Moreover, pyroptosis activation usually depends on caspase, which can induce inflammation and metabolic disorders. In this study, inspired by the tumor-specific expression of SRY-box transcription factor 4 (Sox4) and matrix metalloproteinase 2 (MMP2), we constructed a doubly regulated plasmid, pGMD, that expresses a biomimetic gasdermin D (GSDMD) protein to induce the caspase-independent pyroptosis of tumor cells. To deliver pGMD to tumor cells, we used a hyaluronic acid (HA)-shelled calcium carbonate nanoplatform, H-CNP@pGMD, which effectively degrades in the acidic endosomal environment, releasing pGMD into the cytoplasm of tumor cells. Upon the initiation of Sox4, biomimetic GSDMD was expressed and cleaved by MMP2 to induce tumor-cell-specific pyroptosis. H-CNP@pGMD effectively inhibited tumor growth and induced strong immune memory effects, preventing tumor recurrence. We demonstrate that H-CNP@pGMD-induced biomimetic GSDMD expression and tumor-specific pyroptosis provide a novel approach to boost cancer immunotherapy.

Analysis of constant proportional Caputo operator on the unsteady Oldroyd‐B fluid flow with Newtonian heating and non‐uniform temperature

AbstractThe Caputo operator has recently gained popularity as a widely used operator in fractional calculus. The purpose of this current research is to develop a new operator by combining the Caputo and proportional derivatives, resulting in the constant proportional Caputo (CPC) fractional operator. To demonstrate the dynamic behavior of this newly defined operator, it was applied to the unsteady Oldroyd‐B fluid model. Additionally, the research considered an Oldroyd‐B fluid in a generalized Darcy medium, considering non‐uniform temperature, radiation, and heat generation. Analytical solutions for the proposed model were obtained and presented in graphical form using the computational software MATHCAD. The impact of various physical parameters was also examined through graphical analysis of velocity and temperature profiles, as well as a comparison between isothermal and non‐uniform temperature. In conclusion, this research found that the CPC fractional operator effectively explains the dynamics of the Oldroyd‐B fluid model with stable and strong memory effects, compared to the classical model.

Influence of chain entanglements and melt memory effect on the crystallization behavior of polyphenylene sulfide

Polyphenylene sulfide (PPS) has a prospective application in high-frequency communication due to its excellent dielectric properties. However, owing to the strong melt memory effect, the crystalline structure of PPS is very sensitive to the processing conditions and difficult to be controlled. To date, the melt memory effect of polymer cannot be detected directly and quantitatively. In this work, four PPS samples were successively prepared via polymerization, extrusion and dissolution treatment. The Fourier infrared transform spectroscopy (FTIR), high-temperature gel permeation chromatography (HT-GPC) and dynamic rheological tests disclose that these four PPS samples have analogous molecular structure and only differ in entanglement density. The molecular weight between entanglements (Me) decreases gradually from 1188 to 354 g/mol. Furthermore, differential scanning calorimetry (DSC) and polarized optical microscopy (POM) measurements were carried out to study the effect of entanglement density on the crystallization kinetics of PPS. It is found that entanglement density is a key indicator to characterize the melt memory effect of PPS semi-quantitatively, and the residual local ordered structures in PPS melt is proportional to Me. In addition, the crystallization kinetics of PPS is determined by the cooperation of melt memory effect (nucleation) and entanglement density (growth). Accordingly, the relationship of “chain entanglements” → “melt memory effect” → “crystallization behavior” of PPS is established, constructing a roadmap for the precise control of crystalline structures of PPS products during practical processing.

Excellent adsorption properties of Mg/Al/Fe LDOs for Cr(VI) in water

Cr(VI), a common wastewater pollutant discharged from metallurgical, electroplating and other industries poses a threat to human health and the ecological environment. Layered double hydroxides (LDHs), which have a strong anion exchange capacity and memory effect, are excellent adsorbents that are widely used for heavy metal adsorption. In this study, we found that Mg-Al-Fe ternary metal oxides (MAF-LDOs) obtained by the calcination of Mg-Al-Fe hydrotalcite-like compounds (MAF-LDHs) had great potential for the treatment of Cr(VI)-containing wastewater. The influences of the adsorption time, Cr(VI) concentrations, pH value and coexisting metal ions were also considered. By using batch adsorption experiments and various characterization tools, it was found that the mechanism of Cr(VI) adsorbed by MAF-LDO involved the use of a memory effect that involved HCrO4- in the reconstruction of laminates. In addition, some laminate -OH groups were protonated to electrostatically attract HCrO4-. The -OH groups in the laminate acted as electron donors to reduce Cr(VI) to Cr(III) that then underwent complexation for the effective removal of Cr(VI). The maximum theoretical adsorption capacity of MAF/LDOs for Cr(VI) was 122.85 mg/g at 20 °C. Furthermore, the MAF-LDO demonstrated excellent stability and reusability. In conclusion, the MAF-LDO exhibited a simple synthesis process, superior adsorption capacity with a short contact time, and a wide pH range of application. Hence, it is well-suited for industrial wastewater treatment and provides new insights for treating Cr(VI)-containing wastewater.

Biocompatible Polymer-Modified Nanoplatform for Ferroptosis-Enhanced Combination Cancer Therapy.

Ferroptosis is a novel type of iron-dependent non-apoptotic pathway that regulates cell death and shows unique mechanisms including causing lipid peroxide accumulation, sensitizing drug-resistant cancers, priming immunity by immunogenic cell death, and cooperatively acting with other anticancer modalities for eradicating aggressive malignancies and tumor relapse. Recently, there has been a great deal of effort to design and develop anticancer biocompatible polymeric nanoplatforms including polypeptide and PEGylated ones to achieve effective ferroptosis therapy (FT) and synergistic combination therapies including chemotherapy (CT), photodynamic therapy (PDT), sonodynamic therapy (SDT), photothermal therapy (PTT), gas therapy (GT) including nitric oxide (NO), carbon monoxide (CO), and hydrogen sulfide (H2 S), and immunotherapy (IT). To be noted, the combo therapies such as FT-CT, FT-PTT, FT-GT, and FT-IT are attracting much efforts to fight against intractable and metastatic tumors as they can generate synergistic antitumor effects and immunogenic cell death (ICD) effects or modulate immunosuppressive tumor microenvironments to initiate strong antitumor immunity and memory effects. Meanwhile, the polymeric Fenton nano-agents with good biosafety and high anticancer efficacy would provide a guarantee for their further clinical transitions. In this review, various biocompatible polymer-modified nanoplatforms designed for FT and combo treatments are summarized for anticancer therapies and discussed for potential clinical transitions. This article is protected by copyright. All rights reserved.

How 4-(7-Octen-1-yl)-N,N-diphenylaniline co-units induce strong melt memory effects in isotactic polypropylene random copolymers

The random incorporation of comonomer units in isotactic polypropylene usually disrupts the chemical regularity of the macromolecular chain, thereby remarkably affecting the crystallization and melting processes. We study the influence of a novel comonomer 4-(7-Octen-1-yl)-N,N-diphenylaniline (ODPA), in the concentration range of 1.1–6.8 mol%, on the crystallization and self-nucleation behavior of isotactic polypropylene copolymers. Non-isothermal and isothermal differential scanning calorimetry experiments demonstrated that crystallization kinetics are significantly retarded upon comonomer incorporation as the ODPA co-units are excluded to the amorphous regions. Furthermore, ODPA comonomer incorporation leads to a sharp increase in nucleation density; thus, spherulitic superstructures become significantly smaller. Remarkably, the ODPA co-units induce a strong melt memory effect that can persist even above the equilibrium melting temperature for copolymers with 4.4–6.8 mol% ODPA. The width of Domain IIa (exclusive melt-memory domain), an indicator of the self-nucleation strength, starts to increase sharply once the content of ODPA exceeds 1.8 mol%. In contrast, the width of Domain IIb (self-seeding domain) remains constant. We attribute the self-nucleation effect in these ODPA copolymers to the aggregation of co-units in the interlamellar amorphous regions that hinder, upon melting, the motion of the chain sequences that were initially packed within the crystal lattice. In this way, to reach the isotropic melt state, the sample must be heated to much higher temperatures than its apparent or even equilibrium melting point, depending on the comonomer content. Consequently, nucleation upon cooling from the self-nucleated melt becomes easier and faster.

Crystallinity and perfection in ethylene vitrimers probed by combined calorimetry, scattering, and time-domain NMR

The kinetics of crystallization and crystal-crystal transformations in ethylene vitrimers are studied by time-domain NMR. These vitrimers previously exhibited polymorphic transition of crystal structures, which are shown here to be distinguishable by NMR via their dipolar line widths based upon different proton densities and fast internal motions. The conditions under which the polymorphs are formed and interconvert are identified via time-resolved NMR experiments, with a focus on recrystallization after full and partial melting. DSC experiments are used to clarify an unexpected superheating effect, which challenges the determination of actual melting points. We further identify a strong memory effect in isothermal (re)crystallization. Implications of the dynamic nature of the vitrimers in relation to the kinetics of crystallization are discussed. We find that internal perfecting of crystals, enabled by the vitrimeric exchange process, can have a large effect on the DSC-detected melting enthalpy without change in overall crystallinity.

Effusion of stochastic processes on a line

We consider the problem of leakage or effusion of an ensemble of independent stochastic processes from a region where they are initially randomly distributed. The case of Brownian motion, initially confined to the left half line with uniform density and leaking into the positive half line is an example which has been extensively studied in the literature. Here we derive new results for the average number and variance of the number of leaked particles for arbitrary Gaussian processes initially confined to the negative half line and also derive its joint two-time probability distribution, both for the annealed and the quenched initial conditions. For the annealed case, we show that the two-time joint distribution is a bivariate Poisson distribution. We also discuss the role of correlations in the initial particle positions on the statistics of the number of particles on the positive half line. We show that the strong memory effects in the variance of the particle number on the positive real axis for Brownian particles, seen in recent studies, persist for arbitrary Gaussian processes and also at the level of two-time correlation functions.

Tunable Crystallization Kinetics and Crystal Polymorphism in Semicrystalline Polymers: Insight into the Multilevel Structural Order of Polymer Melts.

The melting of semicrystalline polymers is a typical multistep process and involves a series of intermediate melt states. However, the structural characteristics of the intermediate polymer melt is unclear. Herein, we choose polymorphic trans-1,4-polyisoprene (tPI) as a model polymer system and elucidate the structures of the intermediate polymer melt and their strong effects on the following crystallization process. We find that the metastable β crystals of the tPI melt first into an intermediate state and then recrystallize in new crystals upon thermal annealing. The intermediate melt shows multilevel structural order at the chain level depending on the melting temperature. The conformationally ordered melt can memorize the initial crystal polymorph and accelerate the crystallization process, while the ordered melt without the conformational order can only enhance the crystallization rate. This work provides deep insight into the multilevel structural order of polymer melts and its strong memory effects on the crystallization process.

Control of the crystalline morphology of polyphenylene sulfide in secondary thermoforming by the strong memory effect of crystallization

Polyphenylene sulfide (PPS), as a typical resin for aerospace thermoplastic composites, often undergoes repeated melting and crystallization during thermoforming. Thermal histories can introduce the self-nucleation (SN) effect in certain circumstances, which will significantly accelerate the overall crystallization rate of PPS. In this article, the SN behavior of PPS and its influence on nonisothermal and isothermal crystallization behavior were studied by differential scanning calorimetry, and the multiscale crystalline morphology and structure were characterized. A unique SN domain within the temperature range of 292 °C–323 °C was identified, where the melting endotherm reaches the melt baseline and the peak crystallization temperature remains stable, while the spherulite size is several hundred nanometers. The mechanisms of the impact of molecular chain topology at different melting temperatures on the SN behavior were proposed. This work provides guidance for the design of PPS crystalline structure and suggests a stable thermoforming processing region, approximately 20 °C above the melting point.