Effect Of Fluctuations Research Articles

Abstraction-based segmental simulation of reaction networks using adaptive memoization

Background Stochastic models are commonly employed in the system and synthetic biology to study the effects of stochastic fluctuations emanating from reactions involving species with low copy-numbers. Many important models feature complex dynamics, involving a state-space explosion, stiffness, and multimodality, that complicate the quantitative analysis needed to understand their stochastic behavior. Direct numerical analysis of such models is typically not feasible and generating many simulation runs that adequately approximate the model’s dynamics may take a prohibitively long time.Results We propose a new memoization technique that leverages a population-based abstraction and combines previously generated parts of simulations, called segments, to generate new simulations more efficiently while preserving the original system’s dynamics and its diversity. Our algorithm adapts online to identify the most important abstract states and thus utilizes the available memory efficiently.Conclusion We demonstrate that in combination with a novel fully automatic and adaptive hybrid simulation scheme, we can speed up the generation of trajectories significantly and correctly predict the transient behavior of complex stochastic systems.

Extrinsic fluctuations in the p53 cycle.

Fluctuations are inherent to biological systems, arising from the stochastic nature of molecular interactions, and influence various aspects of system behavior, stability, and robustness. These fluctuations can be categorized as intrinsic, stemming from the system's inherent structure and dynamics, and extrinsic, arising from external factors, such as temperature variations. Understanding the interplay between these fluctuations is crucial for obtaining a comprehensive understanding of biological phenomena. However, studying these effects poses significant computational challenges. In this study, we used an underexplored methodology to analyze the effect of extrinsic fluctuations in stochastic systems using ordinary differential equations instead of solving the master equation with stochastic parameters. By incorporating temperature fluctuations into reaction rates, we explored the impact of extrinsic factors on system dynamics. We constructed a master equation and calculated the equations for the dynamics of the first two moments, offering computational efficiency compared with directly solving the chemical master equation. We applied this approach to analyze a biological oscillator, focusing on the p53 model and its response to temperature-induced extrinsic fluctuations. Our findings underscore the impact of extrinsic fluctuations on the nature of oscillations in biological systems, with alterations in oscillatory behavior depending on the characteristics of extrinsic fluctuations. We observed an increased oscillation amplitude and frequency of the p53 concentration cycle. This study provides valuable insights into the effects of extrinsic fluctuations on biological oscillations and highlights the importance of considering them in more complex systems to prevent unwanted scenarios related to health issues.

Numerical Analysis and Validation of Horizontal and Vertical Displacements of a Floating Body for Different Wave Periods

This study concentrates on numerically evaluating the behavior of a floating body with a box format. Although research on floating objects has been conducted, the numerical modeling of Wave Energy Converter (WEC) devices, considering the effects of fluctuations, remains underexplored. Therefore, this research intends to facilitate the analysis of floating devices. First, the experimental data served as a benchmark for evaluating the motion paths of the floating box’s centroid. Second, the effects of various wave periods and heights on the floating body’s movement were analyzed. The Volume of Fluid (VOF) multiphase model was applied to simulate the interactions between phases. The computational model involved solving governing equations of mass conservation, volumetric fraction transport, and momentum, employing the Finite Volume Method (FVM). The validation demonstrated that the Normalized Root Mean Square Error (NRMSE) for the x/h ratio was 3.3% for a wave height of 0.04 m and 4.4% for a wave height of 0.1 m. Moreover, the NRMSE for the z-coordinate to the depth of water (z/h) was higher, at 5% for a wave height of 0.04 m and 5.8% for a wave height of 0.1 m. The overall NRMSE remained within acceptable ranges, indicating the reliability of the numerical solutions. Additionally, the analysis of horizontal and vertical velocities at different wave periods and heights showed that for H = 0.04 m, the wave periods had a minimal impact on the amplitude, but the oscillation frequency varied. At H = 0.1 m, both velocities exhibited significantly larger amplitudes, especially for T = 1.2 s and T = 2.0 s, indicating stronger motion with higher wave heights.

Investigating the impacts of climate variations and armed conflict on drought and vegetation cover in Northeast Syria (2000–2023)

Over the last decades, The Northeast part of Syria (NES) has been significantly affected by multiple drought events, which are exacerbated by armed conflict and climate variations. In this study, the spatiotemporal effects of climate fluctuations on drought episodes and agricultural areas in NES from 2000 to 2023 were examined by utilizing diverse meteorological parameters combined with the normalized difference vegetation index. The relationships between the change in climatic variables and vegetation cover alterations were determined by performing different statistical methods, such as the Pearson correlation coefficient and Mann-Kendall trend analysis. The results indicated a significant decrease in the agricultural area, especially in recent years, accompanied by a notable increase in the precipitation levels. Moreover, there has been a substantial increase in temperatures, particularly in the minimum temperatures. The results also indicate that drought severity and frequency have increased since the armed conflict despite the area receiving higher precipitation amounts, highlighting the role and impacts of violence. Therefore, we recommend further research on how different vegetation species have been affected by climate change and armed conflict, defining specific growing seasons for each vegetation species, and creating land use land cover maps to understand the spatial alteration of these types better.

Effects of Interest Rate Change on Private Sector Investment, Evidence From Pakistan

This study examines the effects of lending rates, inflation, and exchange rate fluctuations on private sector credits (PSC) in Pakistan from 1961 to 2017. The analysis shows that lending rates have a minimal impact on PSC, with an insignificant relationship. However, inflation and exchange rates show significant negative effects, indicating that rising prices and currency depreciation reduce private sector borrowing by increasing costs and uncertainty. These findings suggest that while interest rate management remains important, policymakers should prioritize strategies for stabilizing inflation and exchange rates to support private sector investment. Consequently, fostering macroeconomic stability may mitigate the indirect effects of the crowding-out phenomenon, promoting a favorable investment environment conducive to private sector growth.

Unveiling the nonclassicality within quasi-distribution representations through deep learning

Abstract To unequivocally distinguish genuine quantumness from classicality, a widely adopted approach focuses on the negative values of a quasi-distribution representation as compelling evidence of nonclassicality. Prominent examples include the dynamical process nonclassicality characterized by the canonical Hamiltonian ensemble representation (CHER) and the nonclassicality of quantum states
characterized by the Wigner function. However, to construct a multivariate joint quasi-distribution function with negative values from experimental data is typically highly cumbersome. Here we propose a computational approach utilizing a deep generative model, processing three marginals, to construct the bivariate joint quasi-distribution functions. We first apply our model to tackle the
challenging problem of the CHERs, which lacks universal solutions, rendering the problem ground-truth (GT) deficient. To overcome the GT deficiency of the CHER problem, we design optimal synthetic datasets to train our model. While trained with synthetic data, the physics-informed optimization enables our model to capture the detrimental effect of the thermal fluctuations on nonclassicality, which cannot be obtained from any analytical solutions. This underscores the reliability of our approach. This approach also allows us to predict the Wigner functions subject to thermal noises. Our model predicts the Wigner functions with a prominent accuracy by processing three marginals of probability distributions. Our approach also provides a significant reduction of the experimental efforts of
constructing the Wigner functions of quantum states, giving rise to an efficient alternative way to realize the quantum state tomography.

Detecting quantum vacuum fluctuations of the electromagnetic field

Abstract Quantum vacuum fluctuations of the electromagnetic field result in two signatures on a harmonically trapped charged particle: a shift from the natural trap frequency and generation of quantum coherences. We assess the role of the long-wavelength and rotating-wave approximations in estimating this frequency shift. We estimate the magnitude of the frequency shift using parameters from a single-electron cyclotron experiment and also demonstrate how the dependence of the frequency shift on the magnetic field of the cyclotron is tied to the rotating-wave approximation. We expect the frequency shift to be observable in future experiments. We also suggest a possible route to detecting vacuum-generated quantum coherences. These experiments should settle the debate on
the choice of approximations and gauge in capturing the effect of the quantum vacuum fluctuations.

Revealing the influence mechanism of pre-fermentation degree and storage temperature fluctuations on frozen steamed bread dough quality

This study investigated the effects of pre-fermentation degree and storage temperature fluctuations on the gas cells, gluten protein, rheological properties of frozen dough, and quality of steamed bread. Three pre-fermentation degrees and four fluctuating temperatures (−10 °C, 0 °C, 10 °C, and 25 °C) were used. The gas cell size increased with the pre-fermentation degree; however, the gas cells merged and ruptured during temperature fluctuations. Sodium dodecyl sulfate extraction protein content and free sulfhydryl content increased by 3.07 % and 33.62 %, respectively, in the medium pre-fermentation group at 25 °C compared with those at −10 °C. The maximum strain of dough increased as pre-fermentation degree and fluctuating temperatures increased. The specific volumes of steamed bread with medium pre-fermentation degree were 1.87 mL/g at −10 °C and 1.47 mL/g at 25 °C. In conclusion, higher temperature fluctuations exceeding the freezing point exacerbated the dough and steamed bread quality, particularly in high pre-fermentation degree dough.

The origin and control of interstitial impurities in refractory complex concentrated alloys

Interstitial impurities, primarily O and N, inadvertently introduced during the processing of refractory complex concentrated alloys (RCCAs) significantly limit the mechanical properties of the alloys at room temperature. Plasma arc melting (PAM) has facilitated the quest for RCCAs, showcasing remarkable combinations of strength and ductility. In this work, the composition and chemistry of residual gases in the PAM chamber environment during arc melting and the interstitial impurities in elemental feedstocks were analyzed to quantify the origin of O and N during synthesis. Moreover, the thermodynamic mechanisms governing the origin of interstitial impurities in arc-melted MoNbTaW RCCAs were discussed. With an understanding of the mechanisms governing the content of interstitial impurities in RCCAs during PAM, arc-melted MoNbTaW RCCAs with fewer than 100 ppm O were synthesized. The arc-melted MoNbTaW RCCAs were then characterized using electron microscopy and atom probe tomography to establish the compositional architecture of grain boundaries and thereby elucidate the thermodynamic drive for segregation and oxide formation in MoNbTaW. Additionally, density functional theory calculations of a MoNbTaW grain boundary were employed to analyze the effect of local chemical fluctuations on the O segregation and oxide formation at the grain boundary. This detailed understanding of the thermodynamic mechanisms governing the origin of interstitial impurities and their grain boundary segregation in MoNbTaW RCCAs provides greater context surrounding O interactions in RCCAs, which is key for the successful development of refractory alloys with unique combinations of strength and ductility.

Nuclear Quantum Effects Have a Significant Impact on UV/Vis Absorption Spectra of Chromophores in Water.

Despite the broadly acknowledged importance of solvationeffects on measured UV/Vis spectra in the context ofsolvatochromism or chemical reactions in solution, it is still an open challenge to calculate UV/Vis spectra with predictive accuracy. This is particularly true when it comes to theimpact of nuclear quantum effects on these experimentalobservables. In the present work, we calculate the UV/Visabsorption spectrum of indole in aqueous solution with acombination of a correlated wavefunction method for computing electronic excitation energiesand enhanced path integralsimulations for rigoroussampling of nuclear configurations includingthe quantum effects in solution.Aftervalidating our approach based on gas-phase benchmarking, we demonstrate that the lineshape ofthe spectrum measured in aqueous solution is quantitatively recovered,without the application of any shifting, scaling, or broadening,only after including nuclear quantum effects in additionto thermal fluctuations and solvation at ambient conditions.Our findings demonstrate that nuclear quantum effects are"visible" in UV/Vis spectra of chromophores measured in solution even at room temperature and, therefore, thatthey must be considered computationally to achieve predictive accuracy.

Josephson Critical Currents and Related Effects in Ultracold Atomic Superfluid Sytems

The Josephson and Proximity effects play a pivotal role in the design of superconducting devices for the implementation of quantum technology, ranging from the standard Al based to the more exotic twisted high-Tc junctions. Josephson critical currents have been recently investigated also in ultracold atomic systems where a potential barrier acts as a weak link. The unifying feature of the above systems, apart from being superconducting/superfluid, is the presence of spatial inhomogeneity, a feature that has to be properly taken into account in any theoretical approach employed to investigate them. In this work, we review the novel (dubbed LPDA for Local Phase Density Approximation) approach based on a coarse graining of the Bogoliubov–de Gennes (BdG) equations. Non-local and local forms of this coarse graining were utilized when investigating Proximity and Josephson effects. Moreover, the LPDA approach was further developed to include pairing fluctuations at the level of the non-self-consistent t-matrix approximation. The resulting approach, dubbed mLPDA (modified LPDA), can be used whenever inhomegeneity and fluctuations effects simultaneously play an important role.

The relationship between daily blood glucose fluctuation and readmission in patients with acute coronary syndrome

Abstract Background Although the comprehensive diagnos and treatment of patients with acute coronary syndrome(ACS) has been greatly improved,the morbidity and mortality are still high. Previous literature has reported that about 70-75% of patients diagnosed with acute coronary syndrome have abnormal blood glucose metabolism1,and there existed gender differences. At present, most research results showed that elevated blood glucose is related to the prognosis of ACS. However, further intervention studies indicated that simply strengthen the reducement of blood glucose did not improve prognosis of these patients2. Glucose fluctuations, another dimension of blood glucose, reflect acute changes in blood glucose. However, there are few studies on the effect of blood glucose fluctuation on the prognosis of patients with ACS. Purpose This study aimed to explore the relationship between seven daily fluctuations of blood glucose and readmission in ACS patients. Methods In this study, a total of 664 patients admitted to our University from January 1, 2019 to December 31, 2019 were included and their blood glucose was monitored seven times a day during their hospitalization. The coefficient of variation of blood glucose (CV) was calculated from the results of seven daily blood glucose monitoring to represent the daily fluctuation of blood glucose. Univariate and multivariate regression analyses were performed to determine whether CV was an independent risk factor for re-hospitalization. In addition, the area under the curve (AUC) was used to evaluate the predictive efficacy of CV for outcome events. Finally, we performed a subgroup analysis based on gender and diabetes status to assess the association between CV and readmission in each subgroup. Results After a median follow-up of 21 months, the rate of readmission was 38.4%. Unstable angina pectoris (71.4%) and heart failure (16.4%) were the most common reasons for readmission. Patients with greater CV levels typically exhibited lower fasting blood glucose, higher post breakfast blood glucose, and higher admission blood glucose.The readmission rate increased with the increasing blood glucose variability after the cox regression analysis. Moreover, independent of glycated hemoglobin,CV could predict the risk of readmission in patients with ACS.When using 26.66% as the cutoff point of CV, the study population was divided into two groups and showed a significant differentiation for rehospitalization.In subgroup analysis, there was no significant association between seven daily blood glucose fluctuations and readmission in female and non-diabetes mellitus patients with acute coronary syndrome. Conclusions Besides some normal blood glucose index,seven daily fluctuations of blood glucose was associated with readmission in ACS patients. ACS patients who were male and combined with diabetes were more likely to be readmitted if their CV levels were greater.

The Impact of Lead Time Variability on Supply Chain Management

Purpose: The impact of lead time variability on supply chain management (SCM) is a critical factor affecting operational efficiency, cost management, and service delivery. This study examines how variations in lead time affect key aspects of supply chain performance, including inventory management, production scheduling, and order fulfillment. Methodology: A mixed-methods approach is adopted, combining quantitative analysis through simulation modeling and qualitative insights derived from case studies of companies in the manufacturing and retail sectors. The simulation model accounts for different levels of lead time variability and its influence on stockouts, excess inventory, and overall supply chain responsiveness. Case studies are used to illustrate real-world challenges and strategies employed by businesses to mitigate the effects of lead time fluctuations. Findings: Findings indicate that higher lead time variability leads to increased inventory costs, stockouts, and delays in product deliveries. Companies that rely heavily on just-in-time (JIT) systems are particularly vulnerable to these fluctuations, whereas firms with flexible inventory strategies or buffer stock perform better in managing variability. Additionally, the study reveals that advanced demand forecasting and more resilient supplier relationships can significantly reduce the negative impact of lead time uncertainty. The analysis also highlights the importance of integrating lead time variability into the broader risk management framework of supply chains. Unique Contribution to Theory, Practice and Policy: Based on these findings, recommendations include implementing more robust demand forecasting systems, optimizing safety stock levels, diversifying suppliers, and using advanced inventory management technologies. Moreover, it is advised that businesses foster stronger communication and collaboration with suppliers to reduce variability and improve lead time predictability. Future research should explore the potential of real-time data and AI-driven supply chain management systems to further mitigate lead time variability's impact on SCM.

Effect of carbon price fluctuation on shore power system: a risk transmission analytics model

Effect of carbon price fluctuation on shore power system: a risk transmission analytics model

Fatigue Assessment of Pier Structures Under Dynamic Forces

Pier structures in port and fishing harbor facilities require dynamic analyses during the design phase to account for external dynamic forces because of their high flexibility. Dynamic forces are frequently approximated as equivalent static forces for design purposes in practical engineering applications, but the fluctuational effects induced by these dynamic forces can be neglected. As the frequency range of wave forces acting on pier structures (0.05–1.0 Hz) significantly overlaps with the typical natural frequency range of pier structures (0.25–4.0 Hz), the response of a pier structure can be amplified because of the dynamic effects of the waves. In this study, we conducted a dynamic analysis by applying wave forces—a representative dynamic load—to a pier structure. The results were compared with those from a static analysis. A fatigue life assessment, which is often overlooked in static analyses, was also performed. The findings indicated that the concrete at the connection between the upper pier and steel piles exhibited a fatigue life of 27.3 years. The steel piles exhibited fatigue lives of 27.1 and 8.3 years depending on the weld details, falling short of the expected structural durability. Based on these results, recommendations for pier structures are proposed.

Warming could shift the phenological responses of benthic microalgae in temperate intertidal zones

Intertidal mudflats colonized by sediment-dwelling microphytobenthos deliver a wide range of ecosystem services. Here we simulate the response of microphytobenthos, located on a temperate tidal mudflat along the French Atlantic coast in Northwestern Europe, exposed to changes in light, temperature, and sea level conditions predicted by the Intergovernmental Panel on Climate Change. Without sea level rise, microphytobenthos benefit from the balancing effect of net primary production fluctuations, experiencing an increase in winter and a decrease in summer. Under the worst emissions scenario, microphytobenthos bloom up to 14 days earlier in spring and 5 days later in fall, thereby extending the low-level microphytobenthos biomass period by an additional 3 weeks in summer. Sea level rise reduces light exposure leading to a pronounced decline in microphytobenthos under the medium-low emissions and worst emissions scenarios. We provide evidence that the anticipated warmer climate and sea level rise will have an impact on microphytobenthos, potentially triggering cascading effects across the entire food web and disrupting ecosystem services.

Micro-mechanisms of digitalization-driven financing for renewable energy: Growing capital pools and shifting flows

Recent facts from China suggest that the advancement of digitalization is altering the market expectations regarding renewable energy. Limited studies have offered evidence encompassing the stock effect of digitalization that enhanced corporate financing and the flow effect that initiated speculative behavior. However, a comprehensive discourse remains insufficient. This paper investigates the synergetic effects of digitalization's stock and flow on renewable energy financing, employing the business data of all listed companies in China from 2003 to 2023. The results demonstrate that: (1) Digitalization's stock has expanded the potential fund pool for renewable energy financing, yet it is challenging to influence the flow of funds; digitalization's flow has triggered a flood of funds into the renewable energy industry, but this relies on the new investors attracted by the stock. (2) The synergetic effect governs the systematic influence of digitalization on renewable energy financing and mitigates the measurement bias when considering only a single effect. (3) We further contemplate the indirect effects of renewable energy market expansion, technological progress, and global energy market fluctuations, alleviating concerns regarding the omitted variable bias. The results of the differential regression and generalized method of moments also indicate the robustness of the conclusion.

Dispersive vacuum as a decoherence amplifier of an Unruh–DeWitt detector

Abstract Recently, interest has been growing in studies on discrete or "pixelated'' space-time that, through modifications in the dispersion relation, can treat the vacuum as a dispersive medium. Discrete spacetime considers that spacetime has a cellular structure on the order of the Planck length, and if this is true we should certainly have observable effects. In this paper, we investigated the effects caused by the dispersive vacuum on the decoherence process of an Unruh-DeWitt detector, our setup consists of a uniformly accelerated detector, initially in a qubit state, which interacts with a massless scalar field during a time interval finite. We use dispersion relations drawn from doubly special relativity and Hořava-Lifshitz gravity, with these modifications the vacuum becomes dispersive and has a corresponding refractive index. We calculate the probability transition rates, the probability of finding the detector in the ground state, and the quantum coherence variation. Our results indicate that the decoherence process occurs more quickly in cases with changes in the dispersion relation in the regime of high accelerations and interaction time. Additionally, the decoherence increases as the vacuum becomes more dispersive due to the increase in the order of modification in the dispersion relation, and this happens because the dispersive vacuum amplifies the effects of quantum fluctuations that are captured by the detector when interacting with the field.

Relations Between Distinct Dimensions of Physical Activity and Preschoolers' ADHD Symptoms.

This study examined the unique and interactive effects of PA volume and within-person fluctuations in PA volume (i.e., intraindividual variability in PA volume; PA-var) on preschoolers' (N = 141; 47.5% girls) ADHD symptoms. Preschoolers wore accelerometers during the school day over a 2-week period. Teachers reported on children's hyperactive, impulsive, and inattentive symptoms on the ADHD Rating Scale-IV Preschool Version. In the context of regression models, higher levels of PA-var were linked with lower levels of impulsive symptoms. Higher levels of PA volume were linked with higher levels of hyperactive and inattentive symptoms, but only when PA fluctuation (i.e., PAvar) was relatively low. Post hoc analyses with teacher-reported impairment as the outcome revealed a significant interaction such that the positive association between PA volume and impairment was stronger at lower, as compared to higher, levels of PA-var. Larger fluctuations in preschoolers' PA volume may indicate lower risk for displaying impulsive symptoms. Moreover, preschoolers with high levels of PA that remain relatively consistent throughout the day may be at increased risk for exhibiting hyperactive and inattentive symptoms and related impairment, suggesting they are unable to regulate their activity to meet expectations in the school environment.

Rupture energy coupling of alkali washing tower cylinder

The energy generated by the container during the explosion induces destructive effects on the surrounding objects and itself, such as deformation, compression, rupture, etc. The explosive energy is one of the richest pieces of evidence in the analysis of the accident cause, and therefore a comprehensive analysis of the accident explosive energy is essential for determining accident properties. Considering the rupture accident of an alkali washing tower in an aromatic hydrocarbon plant as an example, the destructive energy and the rupture internal pressure are estimated to ascertain the explosive properties of the accident by analyzing the field damage characteristics. This study aims to conduct a comprehensive analysis and calculation of the energy associated with an alkali washing tower rupture accident. The objective is to determine the cause of the accident, which can be attributed to the combined effect of wall thickness reduction and fluctuations of production process parameters. The findings of this analysis will serve as a scientific basis for the examination of similar accidents and the formulation of safety protection measures.