Dynamic Analysis Research Articles

Polysquaramides.

Thermoplastics, while advantageous for their processability and recyclability, often compromise thermochemical stability and mechanical strength compared to thermosets. Addressing this limitation, we introduce an innovative approach employing reversibly cross-linked polymers, utilizing squaramide moieties to reconcile recyclability and robustness. Herein, we detail the synthesis of supramolecularly cross-linked polysquaramides through the condensation polymerization of diethyl squarate with primary and secondary diamines. This methodology embeds hydrogen-bonding squaramide motifs into the polymer chains, yielding materials with significantly enhanced storage moduli, reaching up to 1.2 GPa. Material characterization via dynamic mechanical analysis, creep-recovery, and stress relaxation experiments delineate a distinctive rubbery plateau across a broad temperature range, excellent creep resistance, and multimodal viscoelastic flow, respectively, attributable to the dynamic nature of the supramolecular cross-links. Additionally, the study showcases the modulation of glass transition temperature (Tg) by altering the monomer composition and stoichiometry, demonstrating the tunability of polymer viscoelastic properties through precise control over hydrogen bonding interactions. Overall, the incorporation of squaramide motifs not only provides the structural integrity and mechanical performance of these thermoplastics but also leads to engineering materials with tailored viscoelastic characteristics.

Unusual dynamics of tetrahedral liquids caused by the competition between dynamic heterogeneity and structural heterogeneity.

Tetrahedral liquids exhibit intriguing thermodynamic and transport properties because of the various ways tetrahedra can be packed and connected. Recently, an unusual temperature dependence of the stretching exponent β in a model tetrahedral liquid ZnCl2 from Tm + 85K to Tm + 35K has been reported using neutron-spin echo spectroscopy. This discovery stands in sharp contrast to other glass-forming liquids. In this study, we conducted neural network force field driven molecular dynamic simulations of ZnCl2. We found a non-monotonic temperature dependence of β from liquid to supercooled liquid temperatures. Further structural decomposition and dynamic analysis suggest that this unusual dynamic behavior is a result of the competition between the decrease in the diversity of tetrahedra motifs (structural heterogeneity) and the increase in glassy dynamic heterogeneity. This result may contribute to new understandings of the structural relaxation of other network liquids.

Determination of Ambient Air Vaporizers’ Performance Based on a Study on Heat Transfer in Longitudinal Finned Tubes

Ambient air vaporizers (AVVs) are the most commonly used type of heat exchanger for cryogenic regasification stations. The transfer of heat from the environment for heating the liquefied gas and its vaporization is a cost-free and efficient method. Designing ambient air vaporizers for regasification or fueling stations requires accepting the size and related thermal power of the AVV considering the operating conditions and the type of liquefied gases to be vaporized. The nominal capacity of the ambient air vaporizer depends on its design, the frosting of longitudinal finned tubes, and the airflow through the vaporizer structure. This paper presents the results of experimental studies and computational fluid dynamics (CFD) analysis on determining the heat output of AVV longitudinal finned tubes depending on their design. This experiment was conducted in order to establish a numerical model. The relation between the longitudinal finned tubes thermal power and the air flow velocity is demonstrated and the beneficial effect of forced convection is proved. The obtained results are used for verification calculations of ambient air vaporizers’ performance depending on the size of the AVV, the profile cross-section, and the airflow velocity for different liquefied gases. Under conditions of forced convection, profiles with 12 equal-height fins were discovered to be the most efficient for higher airflow velocity providing up to 7% higher heat rate than profiles with 8 equal-height fins. However, at low air velocity, profiles with 8 equal-length fins showed a comparable heat output to profiles with 12 equal-length fins. Profiles with 8 and 12 unequal high fins differ in average heat output by about 28%. The profile with 12 unequal high fins turned out to be the least effective when 2D airflow was considered in this analysis.

Nonlinear Dynamics in Variable-Vacuum Finsler–Randers Cosmology with Triple Interacting Fluids

Considering the interaction among matter, vacuum, and radiation, this paper investigates the evolution of cosmic dynamics of the varying-vacuum model in a case of Finslerian geometry through dynamic analysis methods. Surprisingly, this model can alleviate the coincidence problem and allows for a stable later cosmological solution corresponding to the accelerating universe.

Seismic Response and Collapse Analysis of a Transmission Tower Structure: Assessing the Impact of the Damage Accumulation Effect

This paper delves into the impact of the damage accumulation effect, which leads to the degradation of material strength and stiffness, on the seismic resistance of transmission towers. Building upon the elastic–plastic finite element theory, a mixed hardening constitutive model is derived for circular steel tubes, standard elements in transmission towers, incorporating the damage accumulation effect. A user material subroutine, UMAT, is created within the LS–DYNA framework. The program’s validity and reliability are established through axial constant–amplitude loading tests on single steel tubes. The subroutine is employed to conduct the incremental dynamic analysis (IDA) of an individual transmission tower and to contrast it with the structure utilizing the Plastic Kinematic material model, assessing the discrepancies in tower top displacements and segment damage indices (SDIs) at both macroscopic and microscopic scales. The results shows that the Plastic Kinematic model inflates the seismic performance of the transmission tower. When considering the damage accumulation effect in structural failure, the damage index of the members increases, leading to a reduction in both the structural strength and stiffness. The dynamic response in the plastic phase becomes more pronounced, and the onset of structural failure is accelerated. Consequently, structural analysis under seismic conditions should account for the damage accumulation process. Through the delineation of member and segment damage, the extent of damage to transmission tower segments can be quantitatively assessed. Subsequently, the ultimate load–bearing capacity and the most vulnerable location of the transmission tower can be ascertained. Finally, this paper provides a detailed analysis of the transmission tower collapse process under seismic action and summarizes the mechanism of collapse for the structure.

The influence of vesicularity on grain morphology in basaltic pyroclasts from Mauna Loa and Kīlauea volcanoes

Vesicularity of individual pyroclasts from airfall tephra deposits is an important parameter that is commonly measured at basaltic volcanoes. Conventional methods used to determine pyroclast vesicularity on a large number of clasts has the potential to be time consuming, particularly when rapid analysis is required. Here we propose dynamic image analysis on two-dimensional (2D) projection shapes of crushed pyroclasts from tephra deposits as a new method to estimate vesicularity. This method relies on the influence of vesicles and uses grain morphology as a proxy for vesicle size and abundance. Pyroclasts from a variety of basaltic tephra deposits from the volcanoes of Mauna Loa and Kīlauea were analyzed. Vesicularities between 52–98% were measured via nitrogen-gas pycnometry. The same pyroclasts were then crushed and sieved, and their grain shapes measured using dynamic image analysis on a CAMSIZER®. This yields values for the mean sphericity, elongation, compactness, and Krumbein roundness of the grains. Our data show that grains become increasingly irregular with increasing vesicularity, with the degree of correlation between shape parameters and vesicularity depending on the size of measured grains. Shape irregularities in small grains (60–250 µm) are mostly area-based, with elongation being the best vesicularity indicator, whereas shape irregularities in large grains (250–700 µm) are mostly perimeter-based, with Krumbein roundness as the best vesicularity indicator. Using mean shape parameter values with all grain sizes included, grain elongation is the most well-correlated shape parameter with vesicularity, with the best fitted model explaining 76% of variation in the observations. Microscope images of thin sections of intact pyroclasts, as well as from crushed pyroclasts, were analyzed using CSDCorrections 1.6 software in ImageJ to find local vesicularity, vesicle size, grain size, grain elongation, and vesicle spatial distribution by stereological conversion. Observed correlation between grain shape and vesicularity can be explained by the local effect of vesicles on the shape of the solid structure in between those vesicles. Grain shape depends not only on vesicularity, but also on vesicle to grain size ratio and the spatial distribution of vesicles. The influence of vesicles on grain shape is best captured by grains with the size of the solid structure in between vesicles, which generally increases with decreasing vesicularity. Dynamic image analysis is a useful tool to quickly gauge vesicularity, which could be used in near-real-time during an eruption response. However, this method is best suited for highly vesicular (> 80%) basaltic pyroclasts from tephra deposits with few microlites and phenocrysts. Further research on crushing techniques, optimum grain size for shape measurements, and Krumbein roundness measurements for the grain size range of 250–700 µm might enable application of this method to lower vesicularity pyroclasts.

Acid-mediated strategies designed for stretchable and durable polyacrylamide/sodium alginate dual-network hydrogels toward flexible capacitors and wearable sensors

The utilization of acid as a synthesis assistant provides an effective means to regulate the structure of hydrogels, thereby simplifying the design and preparation process of multifunctional hydrogels. However, there remains a dearth of discourse concerning the utilization of this convenient acid-mediated strategy, which possesses the potential to directly govern molecular interactions within gel networks for rational structure and property design. Herein, we describe the preparation of flexible dual-network conductive hydrogels using polyacrylamide (PAM) and sodium alginate (SA) as substrates, driven by the strategy of acid-mediated (HCI, H2SO4, and H2C2O4) in detail for the first time. Especially, the structure-activity relationship of hydrogels was elucidated through a comparative analysis of molecular dynamics (MD) simulations and empirical properties, thereby enhancing the understanding of this field. Furthermore, extensive investigations have been conducted to explore the distinct impacts of acid ions and concentrations. The acid-mediated method exhibits superior versatility and operability compared to the filler modification method, thereby enabling a more convenient acquisition of conductive and robust hydrogels suitable for flexible capacitors and wearable sensors. Consequently, this study presents a straightforward, efficient, and cost-effective universal strategy for targeted functional hydrogel design.

The Impact and Mechanism Analysis of Clean Development Mechanism on the Synergistic Effects of Pollution Mitigation and Carbon Reduction

The establishment of the Clean Development Mechanism (CDM) has greatly improved China's carbon emission trading system. However, due to the unbalanced development of CDM in China, the effects and mechanism of CDM on reducing pollution and carbon are still unclear. In order to explore the effects and mechanism of CDM on the synergistic effects of pollution mitigation and carbon reduction, we first set up a theoretical analysis framework. Utilizing panel data from 254 prefecture-level cities across China spanning from 2004 to 2021, we employ a synergy degree model of composite system to evaluate the synergistic effects of pollution mitigation and carbon reduction. By treating CDM as a quasi-natural experimental research subject, we construct a multi-period difference-in-difference model to assess the CDM projects' effects. Our findings indicate a positive association between CDM projects and the synergistic effects of pollution mitigation and carbon reduction. Heterogeneity analysis reveals that CDM projects located in the western region, areas with lower levels of economic development, non-resource cities, non-old industrial bases, and projects with Certified Emission Reductions issued exhibit the most pronounced synergistic effects. Specially, dynamic policy effect analysis shows that only non-resource cities and non-old industrial bases exhibit enhanced policy implementation regarding CDM. Mechanism analysis demonstrates that CDM primarily enhances synergistic effects through improved energy efficiency, technological innovation and energy transition. These findings enrich empirical investigations concerning market-driven emission reduction policy in China, shedding light on pivotal pathways for synergistic control of pollution mitigation and carbon reduction and offering valuable policy insights for comprehensive economic and social green transformation in China.

Explorations of Integrated Multi-Energy Strategy under Energy Simulation by DeST 3.0: A Case Study of College Dining Hall

Buildings characterized by high energy consumption necessitate the implementation of efficient multi-energy complementary systems to achieve energy conservation and emission reduction objectives. College dining halls use a lot more electricity than typical residential buildings, despite their relatively small size. The dining hall at the Dongshan Campus of Shanxi University is employed as a representative case study in this research. By utilizing DeST 3.0 software, a comprehensive dynamic load analysis is conducted to estimate the annual energy consumption of the dining hall, with the ultimate goal of an energy-saving system being proposed based on the analysis results. Leveraging DeST 3.0 software, dynamic load characteristics were assessed, revealing an annual energy consumption of 2.39 × 106 kWh for the dining hall. Cooling accounted for 0.91 × 106 kWh, while heating requirements amounted to 0.24 × 106 kWh. These findings illustrate peak power consumption trends, seasonal variations, and potential avenues for energy conservation. To satisfy the heating, cooling, and electricity demands of the dining hall, an integrated energy system incorporating solar and wind energy, as well as utilizing restaurant kitchen garbage as a biomass source, was proposed. This study compares two solar energy utilization systems: photothermal and photovoltaic, with total capacities of 2.375 × 106 kWh and 2.52 × 106 kWh, respectively. The research outcomes underscore that Strategy 2, which integrates a photovoltaic system with wind and biomass energy, emerges as the optimal approach for load management. Ultimately, this investigation demonstrates the feasibility and promise of constructing a hybrid renewable energy system within a college dining hall setting, aligning with sustainability objectives and global trends toward environmentally responsible energy solutions.

Dynamic variable analysis guided adaptive evolutionary multi-objective scheduling for large-scale workflows in cloud computing

Energy consumption and makespan of workflow execution are two core performance indicators in operating cloud platforms. But, simultaneously optimizing these two indicators encounters various challenges, such as elastic resources, large-scale decision variables, and sophisticated workflow structures. To handle these challenges, we design an adaptive evolutionary scheduling algorithm, namely AESA, with three innovative strategies. First, a heuristic population initialization strategy is devised to gather workflow tasks onto limited potential resources, thereby alleviating the negative impact of redundant cloud resources on evolutionary search efficiency. Then, a variable analysis strategy is designed to dynamically measure the contribution of each decision variable in pushing the population towards Pareto-optimal fronts. Moreover, AESA embraces an adaptive strategy to reward more evolutionary opportunities for decision variables with higher contributions to handle large-scale decision variables in a targeted manner, further improving the efficiency of evolutionary search. Finally, extensive experiments are performed based on real-world cloud platforms and workflow traces to verify the effectiveness of the proposed AESA. The comparison results validate its superior performance by significantly outperforming five representative baselines in optimizing makespan and energy consumption. Also, the results of ablation experiments demonstrate that all three components contribute to AESA’s overall performance, with the adaptive reward mechanism being the most significant.

Dynamic analysis of the fractional-order Duffing-Van der Pol oscillator and its application extension

Dynamic analysis of the fractional-order Duffing-Van der Pol oscillator and its application extension

DYNAMICAL BEHAVIOR OF AN SIR EPIDEMIC MODEL WITH RATIO-DEPENDENT IMPULSIVE CONTROL AND BEDDINGTON–DEANGELIS INCIDENCE

In this paper, we propose an epidemic model of SIR type with ratio-dependent impulse control and Beddington–DeAngelis (B–D) incidence. According to the magnitude of the basic reproductive number [Formula: see text] and the relation of the endemic equilibrium [Formula: see text] and the ratio threshold [Formula: see text], dynamical analysis of the controlled system is conducted. Under the control strategy, if [Formula: see text], the solutions converge to the disease-free equilibrium. If [Formula: see text] and [Formula: see text], the impulsive system has periodic solution that is orbitally asymptotically stable, and order-[Formula: see text] periodic solution does not exist. Furthermore, if [Formula: see text] and [Formula: see text], the solution converges either to the endemic equilibrium or to a periodic solution, which is proved to be determined by the initial value. Finally, numerical simulations are performed to demonstrate the theoretical results.

SomaSeg: A robust neuron identification framework for two-photon imaging video.

Accurate neuron identification is fundamental to the analysis of neuronal population dynamics and signal extraction in fluorescence videos. However, several factors such as severe imaging noise, out-of-focus neuropil contamination, and adjacent neuron overlap would impair the performance of neuron identification algorithms and lead to errors in neuron shape and calcium activity extraction, or ultimately compromise the reliability of analysis conclusions. Herein, to address these challenges, we developed a novel cascade framework - SomaSeg that combines Duffing denoising, neuropil contamination defogging and stacked instance differentiating. Compared with the state-of-the-art neuron identification methods, both simulation and actual experimental results demonstrate that SomaSeg framework is robust to noise, insensitive to out-of-focus contamination and effective in dealing with overlapping neurons in actual complex imaging scenarios, providing a widely applicable framework for two-photon video processing.

Unveiling the Structural and Dynamic Characteristics of Concentrated LiNO3 Aqueous Solutions through Ultrafast Infrared Spectroscopy and Molecular Dynamics Simulations.

Highly concentrated aqueous electrolytes have attracted a significant amount of attention for their potential applications in lithium-ion batteries. Nevertheless, a comprehensive understanding of the Li+ solvation structure and its migration within electrolyte solutions remains elusive. This study employs linear vibrational spectroscopy, ultrafast infrared spectroscopy, and molecular dynamics (MD) simulations to elucidate the structural dynamics in LiNO3 solutions by using intrinsic and extrinsic vibrational probes. The N-O stretching vibrations of NO3- exhibit a distinct spectral splitting, attributed to its asymmetric interaction with the surrounding solvation structure. Analysis of the vibrational relaxation dynamics of intrinsic and extrinsic probes, in combination with MD simulations, reveals cage-like networks formed through electrostatic interactions between Li+ and NO3-. This microscopic heterogeneity is reflected in the intertwined arrangement of ions and water molecules. Furthermore, both vehicular transport and structural diffusion assisted by solvent rearrangement for Li+ were analyzed, which are closely linked with the bulk concentration.

Crucial Structural Understanding for Selective HDAC8 Inhibition: Common Pharmacophores, Molecular Docking, Molecular Dynamics, and Zinc Binder Analysis of selective HDAC8 inhibitors.

Overexpression of HDAC8 was observed in various cancers and inhibition of HDAC8 has emerged as a promising therapeutic approach in recent decades. This review aims to facilitate the discovery of novel selective HDAC8 inhibitors by analyzing the structural scaffolds of 66 known selective HDAC8 inhibitors, along with their IC50 values against HDAC8 and other HDACs. The inhibitors were clustered based on structural symmetry, and common pharmacophores for each cluster were identified using Phase. Molecular docking with all HDACs was performed to determine binding affinity and crucial interacting residues for HDAC8 inhibition. Representative inhibitors from each cluster were subjected to molecular dynamics simulation to analyze RMSD, RMSF, active site amino acid residues, and crucial interacting residues responsible for HDAC8 inhibition. The study reviewed the active site amino acid information, active site cavities of all HDACs, and the basic structure of Zn2+ binding groups. Common pharmacophores identified included AADHR_1, AADDR_1, ADDR_1, ADHHR_1, and AADRR_1. Molecular docking analysis revealed crucial interacting residues: HIS- 142, GLY-151, HIS-143, PHE-152, PHE-20 in the main pocket, and ARG-37, TYR-100, TYR-111, TYR-306 in the secondary pocket. The RMSD of protein and RMSF of active site amino acid residues for stable protein-ligand complexes were less than 2.4 Å and 1.0 Å, respectively, as identified from MD trajectories. The range of Molecular Mechanics Generalized Born Surface Area (MMGBSA) ΔG predicted from MD trajectories was between -15.8379 Å and -61.5017 Å kcal/mol. These findings may expedite the rapid discovery of selective HDAC8 inhibitors subject to experimental evaluation.

Dynamical analysis of a prey–predator model in toxic habitat with weak Allee effect and additional food

Dynamical analysis of a prey–predator model in toxic habitat with weak Allee effect and additional food

Influence of Repeated Earthquake events on Structural Response of Multi‐storeyed RC buildings

Over the past decade, reinforced concrete (RC) multi-storeyed buildings have become more prevalent in urban environments. In addition, it has been well established in literature, that collapse of several RC buildings and resulting causalities, thereof are mainly attributed to the repeated nature of occurrence of earthquakes, more often leading to collapse. However, most existing design codes consider only a scenario earthquake characterized by the response spectrum specified by local codes of practice. This consideration do not address the repetitive nature of earthquakes, leading to inadequate estimation of design earthquake force. Hence, the present investigation focusses on proposing a probabilistic model to logically address the number of earthquake sequences to be considered at a chosen location. In addition, to ascertain attainment of collapse state of code designed 3D RC buildings, under a pattern of earthquake sequences (with simultaneous bi-directional ground motion data), a simple and computationally less intensive NLTHA (Nonlinear Time History Analysis) approach has been considered. Moreover, this approach captures the effect of sequential earthquakes and provides a quick rational decision on the structural behaviour, necessary for further analysis. Hence, eliminating the need to resort always for complex IDA (Incremental Dynamic Analysis) approaches to illustrate the structural behaviour. Moreover, the structural behaviour of RC buildings are represented in terms of base shear experienced and their corresponding response parameters (Horizontal displacement, Inter-story drift ratio (IDR), etc.,). The outcome of the results clearly contemplates the accumulation of damages in terms of response parameters, emphasizing the need for consideration of repeated earthquake sequences in seismic analysis.

Sex-dependent nonlinear Granger connectivity patterns of brain aging in healthy population

BackgroundBrain aging is a complex process that involves functional alterations in multiple subnetworks and brain regions. However, most previous studies investigating aging-related functional connectivity (FC) changes using resting-state functional magnetic resonance images (rs-fMRIs) have primarily focused on the linear correlation between brain subnetworks, ignoring the nonlinear casual properties of fMRI signals. MethodsWe introduced the neural Granger causality technique to investigate the sex-dependent nonlinear Granger connectivity (NGC) during aging on a publicly available dataset of 227 healthy participants acquired cross-sectionally in Leipzig, Germany. ResultsOur findings indicate that brain aging may cause widespread declines in NGC at both regional and subnetwork scales. These findings exhibit high reproducibility across different network sparsities, demonstrating the efficacy of static and dynamic analysis strategies. Females exhibit greater heterogeneity and reduced stability in NGC compared to males during aging, especially the NGC between the visual network and other subnetworks. Besides, NGC strengths can well reflect the individual cognitive function, which may therefore work as a sensitive metric in cognition-related experiments for individual-scale or group-scale mechanism understanding. ConclusionThese findings indicate that NGC analysis is a potent tool for identifying sex-dependent brain aging patterns. Our results offer valuable perspectives that could substantially enhance the understanding of sex differences in neurological diseases in the future, especially in degenerative disorders.

Enhancing cellulose acetate biodegradability in cigarette filters: an in-depth analysis of thermal alkaline pretreatment, microbial dynamics, and breakdown pathway prediction

BackgroundThe demand for bioplastics has increased exponentially as they have emerged as alternatives to petrochemical plastics. However, there is a substantial lack of knowledge regarding bioplastic degradation. This study developed a novel pretreatment method to improve the accessibility of a bioplastic substrate for biodegradation. In this study, cellulose acetate, a bioplastic found in the world’s most littered waste, e.g. cigarette filters, was selected as a potential substrate. Before anaerobic digestion, three thermal alkaline pretreatments: TA 30 °C, TA 90 °C, and TA 121 °C, were used to evaluate their effects on the chemical alterations of cellulose acetate.ResultThe ester groups in cellulose acetate were significantly reduced by the TA 30 °C pretreatment, as seen by a decrease in C = O stretching vibrations and shortening of C − O stretches (1,270 ∼ 1,210 cm− 1), indicating effective removal of acetyl groups. This pretreatment significantly enhanced cellulose acetate biodegradability to a maximum of 91%, surpassing the previously reported cellulose acetate degradation. Methane production increased to 695.0 ± 4 mL/g of volatile solid after TA 30 °C pretreatment, indicating enhanced cellulose acetate accessibility to microorganisms, which resulted in superior biogas production compared to the control (306.0 ± 10 mL/g of volatile solid). Diverse microbes in the anaerobic digestion system included hydrolytic (AB240379_g, Acetomicrobium, FN436103_g, etc.), fermentative, and volatile fatty acids degrading bacteria (JF417922_g, AB274492_g, Coprothermobacter, etc.), with Methanobacterium and Methanothermobacter being the sole hydrogenotrophic methanogens in the anaerobic digestion system. Additionally, an attempt to predict the pathway for the effective degradation of cellulose acetate from the microbial community in different pretreatment conditions.ConclusionsTo the best of our knowledge, this is the first study to estimate the maximum cellulose acetate degradation rate, with a simple and cost-effective pretreatment procedure. This approach holds promise for mitigating the environmental impact of cellulose acetate of cigarette filters and presents a sustainable and economically viable waste management strategy.

Hints from Hertz: Dynamic Frequency Scaling Side-Channel Analysis of Number Theoretic Transform in Lattice-Based KEMs

Hints from Hertz: Dynamic Frequency Scaling Side-Channel Analysis of Number Theoretic Transform in Lattice-Based KEMs