Initial Fluctuations Research Articles

Infrared temperature distribution characteristics and state assessment method of sandstone under tension and compression stress

Abnormalities in infrared radiation temperature (IRT) often accompany the loading In this investigation, stress experiments and splitting tests were conducted on sandstone to investigate the IRT characteristics of sandstone under various loading conditions. The results shows that the Maximum Infrared Radiation Temperature (MAXIRT) increases by up to 5 °C, while in splitting tests, the minimum infrared radiation temperature (MINIRT) decreases by approximately 1.5 °C. Compared to the average infrared radiation temperature (AIRT), MAXIRT is more sensitive to compressive stress, whereas (MINIRT) is more responsive to tensile stress. The correlation between IRT indicators and stress were further analyzed. The findings reveal a positive correlation between IRT and compressive stress. At low stress levels, the correlation coefficient fluctuates between −0.4 and 0.6, generally showing low correlation. As stress increases, the correlation coefficient rises, reaching above 0.8, indicating a high correlation. Tensile stress exhibits a negative correlation, with a consistent trend. Additionally, a statistical analysis of the frequency distribution of IRT under different stress conditions was conducted, followed by hypothesis testing. The results demonstrate that the probability distribution of IRT during loading follows a skewed normal distribution. The changes in skewness can be divided into three stages: initial fluctuation, stable variation, and abrupt failure. Under compressive stress, a right-skewed distribution is observed, with skewness exceeding 3.5 before fracture and reaching above 10 near fracture. Under tensile stress, a left-skewed distribution is noted, with skewness reaching −4.5 near fracture. These findings contribute to the assessment of rock stress states and provide early warning information for predicting rock failure.

Enhanced Depth Control and Stability in Submersible Pylon Inspection Robots Using IMU-Based Extended Kalman Filter and PID Control

The research developed a Submersible Pylon Inspection Robot (SPIR) to clean and inspect underwater structures automatically, facing challenges in stability and depth of operation. Integrating the Inertial Measurement Unit (IMU) with the Extended Kalman Filter (EKF), as well as implementing customized PID controls, aims to improve the accuracy and stability of SPIR in dynamic underwater environments. The results show that the SPIR control system can follow the reference depth at shallow depths well, but has difficulty maintaining stability at deeper depths. The position error graph on the Z-axis shows the initial fluctuation that decreases over time, reflecting the increased calibration. The use of drive motors also shows different working patterns, with some motors active in depth settings and others for stabilization. This study shows that the integration approach of IMU, EKF, and PID control can improve SPIR performance, although further adjustments are required to meet the extreme challenges in underwater environments.

Adaptive boundary control for a friction hoisting system during the loading process

This paper aims at the rope dynamic tension fluctuation (DTF) control in the friction hoisting system (FHS) during the loading process. The exact dynamic modelling of the tail and head ropes connected to the cage is considered. A disturbance observer is proposed to track the actual impact disturbance. The actuator acts at the friction wheel to pretension the system. The use of an adaptive neural network allows for the handling of system uncertainty. An appropriate control law is developed to stabilize the cage and suppress the rope DTF in FHS during the loading process. Numerical simulations and theoretical analysis are presented to prove the feasibility and effectiveness of the proposed control law. Numerical analysis results show that the head rope dynamic displacement fluctuation (DDF) and DTF amplitudes can be suppressed to at least 1/125 of their initial fluctuation amplitudes under the proposed control law.

Computational comparison of passive control for cavitation suppression on cambered hydrofoils in sheet, cloud, and supercavitation regimes

Cavitation is a transient, highly complex phenomenon found in numerous applications and can have a significant impact on the characteristics as well as the performance of the hydrofoils. This study compares the evolution of transient cavitating flow over a NACA4412(base) (NACA stands for National Advisory Committee for Aeronautics) cambered hydrofoil and over the same hydrofoil modified with a pimple and a finite (circular) trailing edge. The assessment covers sheet, cloud, and supercavitation regimes at an 8° angle of attack and the Reynolds number of 1×106, with cavitation numbers ranging from 0.9 to 0.2. The study aims to comprehensively understand the role of the rectangular pimple in controlling cavitation and its impact on hydrodynamic performance across these regimes. Numerical simulations were performed using a realizable model and the Zwart–Gerber–Belamri (ZGB) cavitation model to resolve turbulence and cavitation effects. The accuracy of the present numerical predictions has been verified both quantitatively and qualitatively with available experimental results. The present analysis includes the time evolution of cavities, temporal variation in total cavity volume, time-averaged total cavity volume, distributions of vapor volume fractions along the chord length, and their hydrodynamic performance parameters. Results demonstrate that rectangular pimples have significant impacts in the different cavitation regimes. In the sheet cavitation regime (σ=0.9), the NACA4412(pimpled) hydrofoil exhibits minimal cavity length and transient volume changes as compared to the NACA4412(base) hydrofoil. In the cloud cavitation regimes (σ=0.5), cavity initiation occurs differently, starting from the pimpled location for the NACA4412(pimpled) hydrofoil, unlike the initiation just downstream of the nose in the case of base hydrofoil. In the supercavitation regimes (σ=0.2), the cavity length remains comparable, but the NACA4412(pimpled) hydrofoil exhibits larger cavity volume evolution in both cloud and supercavitation regimes (σ=0.5 and σ=0.2) after initial fluctuations. Furthermore, hydrodynamic performance for the NACA4412(pimpled) hydrofoil shows 41%, 36%, and 17% lower lift coefficients, and 46%, 27%, and 9% lower drag coefficients in sheet, cloud, and supercavitation, respectively.

PLC Controlled Fuzzy Logic-Based Egg Hatching Machine

In response to the increasing food demand due to the growing global population, this study has designed a fully automated incubator machine based on a Programmable Logic Controller (PLC) to enhance efficiency in the egg production sector. To align with Industry 4.0 technologies, this machine controls temperature and humidity using fuzzy logic, one of the artificial intelligence methods. The incubator is capable of meeting the specific temperature and humidity needs for the incubation processes of various types of bird eggs. It has been tested under different conditions, and its performance has been examined in detail. The analysis results show that the fuzzy logic-based temperature and humidity control systems on the PLC successfully reached the set reference values and maintained them continuously and stably after initial fluctuations. In conclusion, the design and control of an automated incubation machine with a PLC-based fuzzy logic controller were successfully accomplished.

Virtual screening and molecular dynamics simulations of phytochemicals targeting cofactor-independent phosphoglycerate mutase in antimicrobial-resistant Mycoplasma genitalium.

Mycoplasma genitalium (M. genitalium) poses a significant challenge in clinical treatment due to its increasing antimicrobial resistance. This study investigates alternative therapeutic approaches by targeting the cofactor-independent phosphoglycerate mutase (iPGM) enzyme with phytochemicals derived from ethnobotanical plants. In silico screening identified several promising inhibitors, with 2-carboxy-D-arabinitol demonstrating the highest binding affinity (-9.77kcal/mol), followed by gluconic acid (-9.03kcal/mol) and citric acid (-8.68kcal/mol). Further analysis through molecular dynamics (MD) simulations revealed insights into the binding mechanisms and stability of these phytochemicals within the iPGM active site. The MD simulations indicated initial fluctuations followed by stability, with intermittent spikes in RMSD values. The lowest RMSF values confirmed the stability of the ligand-protein complexes. Key residues, including Ser-61, Arg-188, Glu-62, Asp-397, and Arg-260, were found to play crucial roles in the binding and retention of inhibitors within the active pocket. These findings suggest that the identified phytochemicals could serve as novel antimicrobial agents against M. genitalium by effectively inhibiting iPGM activity.

Mirror symmetry breakdown in the Kardar-Parisi-Zhang universality class.

The current/height fluctuation statistics of Kardar-Parisi-Zhang (KPZ) universality in 1+1 dimensions are sensitive to the initial state. We find that the averages over the initial states exhibit universal and scale-invariant patterns when conditioning on fluctuations. To establish universality of our findings, we demonstrate scale invariance at different times and heights using large-scale Monte Carlo simulations of the totally asymmetric simple exclusion process, which belongs to the KPZ universality class. Here we focus on current (or height) fluctuations in the steady-state regime described by the Baik-Rains distribution. The conditioned probability distribution of an initial-state order parameter shows a transition from uni- to bimodal. Bimodality occurs for negative current/height fluctuations that are dominated by superdiffusive shock dynamics. It is caused by two possible point-symmetric shock profiles and the KPZ mirror symmetry breakdown. Similar surprising relations between initial states and fluctuations might exist in other universality classes as well.

Collective flow and fluid behavior in p/d/3He+Au collisions at GeV*

Abstract By varying the intrinsic initial geometry, p/d/3He+Au collisions at the Relativistic Heavy Ion Collider (RHIC) provide a unique opportunity to understand the collective behavior and probe possible sub-nucleon fluctuations in small systems. In this study, we employed the hybrid model under TRENTo initial conditions to study the collective flow and fluid behavior in p/d/3He+Au collisions. With fine-tuned parameters, can describe the and data from the PHENIX and STAR collaborations. However, for certain parameter sets with initial sub-nucleon fluctuations, the hydrodynamic simulations already go beyond their limits with an average Knudsen number clearly larger than unity. Our calculations demonstrate that, for a meaningful evaluation of the fluid behavior in small systems, model simulations must also pay attention to the validity range of hydrodynamics.

Impact of initial fluctuations and nuclear deformations in isobar collisions

Impact of initial fluctuations and nuclear deformations in isobar collisions

IFKMHC: Implicit Fuzzy K-Means Model for High-Dimensional Data Clustering.

The graph-information-based fuzzy clustering has shown promising results in various datasets. However, its performance is hindered when dealing with high-dimensional data due to challenges related to redundant information and sensitivity to the similarity matrix design. To address these limitations, this article proposes an implicit fuzzy k-means (FKMs) model that enhances graph-based fuzzy clustering for high-dimensional data. Instead of explicitly designing a similarity matrix, our approach leverages the fuzzy partition result obtained from the implicit FKMs model to generate an effective similarity matrix. We employ a projection-based technique to handle redundant information, eliminating the need for specific feature extraction methods. By formulating the fuzzy clustering model solely based on the similarity matrix derived from the membership matrix, we mitigate issues, such as dependence on initial values and random fluctuations in clustering results. This innovative approach significantly improves the competitiveness of graph-enhanced fuzzy clustering for high-dimensional data. We present an efficient iterative optimization algorithm for our model and demonstrate its effectiveness through theoretical analysis and experimental comparisons with other state-of-the-art methods, showcasing its superior performance.

Thermalization and Hydrodynamics in an Interacting Integrable System: The Case of Hard Rods

We consider the relaxation of an initial non-equilibrium state in a one-dimensional fluid of hard rods. Since it is an interacting integrable system, we expect it to reach the Generalized Gibbs Ensemble (GGE) at long times for generic initial conditions. Here we show that there exist initial conditions for which the system does not reach GGE even at very long times and in the thermodynamic limit. In particular, we consider an initial condition of uniformly distributed hard-rods in a box with the left half having particles with a singular velocity distribution (all moving with unit velocity) and the right half particles in thermal equilibrium. We find that the density profile for the singular component does not spread to the full extent of the box and keeps moving with a fixed effective speed at long times. We show that such density profiles can be well described by the solution of the Euler equations almost everywhere except at the location of the shocks, where we observe slight discrepancies due to dissipation arising from the initial fluctuations of the thermal background. To demonstrate this effect of dissipation analytically, we consider a second initial condition with a single particle at the origin with unit velocity in a thermal background. We find that the probability distribution of the position of the unit velocity quasi-particle has diffusive spreading which can be understood from the solution of the Navier–Stokes (NS) equation of the hard rods. Finally, we consider an initial condition with a spread in velocity distribution for which we show convergence to GGE. Our conclusions are based on molecular dynamics simulations supported by analytical arguments.

Initial Public Offer (IPO) And Stock Market Performance

The success of initial public offers (IPOs) in India is the subject of this master's thesis. It centres on the performance of companies following an IPO, with an emphasis on listing gains and long-term performance (in relation to the market average). With a thorough examination of one of the largest initial public offerings (LICs), the thesis makes use of data from 40 IPOs that were listed on the National Stock Exchange (NSE) between January 2022 and December 2023. In order to determine whether the initial price fluctuations are substantial and long-lasting, it computes anomalous returns.By offering insights into the variables influencing IPO performance, the study hopes to assist investors, businesses, and policymakers. This can assist investors in making well-informed investment decisions, companies in making better decisions about going public, and legislators in developing efficient laws for the Indian IPO market.Because it explicitly targets the Indian market and takes into account a number of variables influencing IPO performance, the research is novel. Both domestic and foreign participants in the Indian financial system can benefit from knowing this information. KEY WORDS: INDIAN IPO, LISTING GAINS, POST-LISTING PERFORMANCE, STOCK MARKET.

Morphology of Galaxies in JWST Fields: Initial Distribution and Evolution of Galaxy Morphology

Abstract A recent study from the Horizon Run 5 (HR5) cosmological simulation has predicted that galaxies with log M * / M ⊙ ≲ 10 in the cosmic morning (10 ≳ z ≳ 4) dominantly have disk-like morphology in the ΛCDM universe, which is driven by the tidal torque in the initial fluctuations of matter. For a direct comparison with observation we identify a total of about 19,000 James Webb Space Telescope (JWST) galaxies with log M * / M ⊙ > 9 at z = 0.6–8.0 utilizing deep JWST/NIRCam images of publicly released fields, including North Ecliptic Pole Time-Domain Fields, Next Generation Deep Extragalactic Exploratory Public survey, Cosmic Evolution Early Release Science Survey, Cosmic Evolution Survey, UltraDeep Survey, and SMACS J0723-7327. We estimate their stellar masses and photometric redshifts with the redshift dispersion of σ NMAD = 0.009 and an outlier fraction of only about 6%. We classify galaxies into three morphological types, disks, spheroids, and irregulars, applying the same criteria used in the HR5 study. The morphological distribution of the JWST galaxies shows that disk galaxies account for 60%–70% at all redshift ranges. However, in the high-mass regime ( log M * / M ⊙ ≳ 11 ), spheroidal morphology becomes the dominant type. This implies that the mass growth of galaxies is accompanied by a morphological transition from disks to spheroids. The fraction of irregulars is about 20% or less at all masses and redshifts. All the trends in the morphology distribution are consistently found in the six JWST fields. These results are in close agreement with the results from the HR5 simulation, particularly confirming the prevalence of disk galaxies at small masses in the cosmic morning and noon.

Tunable Superdiffusion in Integrable Spin Chains Using Correlated Initial States.

Although integrable spin chains host only ballistically propagating particles, they can still feature diffusive charge transfer. This diffusive charge transfer originates from quasiparticle charge fluctuations inherited from the initial state's magnetization Gaussian fluctuations. We show that ensembles of initial states with quasi-long-range correlations lead to superdiffusive charge transfer with a tunable dynamical exponent. We substantiate our prediction with numerical simulations and discuss how finite time and finite size effects might cause deviations.

Co-benefits and influencing factors exploration of air pollution and carbon reduction in China: Based on marginal abatement costs

This study addresses the pressing need for cost-effective emission reduction strategies that maximize co-benefits in terms of air pollution and carbon emissions. Our research contributes to the literature by accurately measuring these co-benefits, thereby facilitating their prompt realization in different regions. We employ an input-output framework that integrates carbon emissions and air pollution, allowing us to calculate marginal abatement costs using the shadow price of undesired output. Through this approach, we quantify the co-benefits and analyze the factors influencing them at both spatiotemporal and factor levels using spatial kernel density and geographical detectors. Our findings reveal several key insights: (1) under joint emission reduction efforts, we observe average annual reduction rates of 6.46% for marginal pollution and 6.10% for carbon reduction costs. Importantly, we document an increase in co-benefits from 0.50 to 0.86, characterized by an initial fluctuation followed by a linear increase. (2) the marginal cost difference for carbon emission and pollution reduction in western China was 179.45 and 155.08 respectively, compared to 321.51 and 124.70 in the Northeast, highlighting the crucial role of regional differences in shaping co-benefit outcomes. (3) we identify a negative spatial spillover effect between provinces, which diminishes over time, leading to heterogeneous effects when local provincial co-benefits exceed a threshold of 0.9. (4) during the adjustment period, we find that the industrial structure exerts significant single and interactive effects on co-benefits. Additionally, we highlight the critical role of environmental governance investment and government intervention as drivers of co-benefits in the current era. By offering the quantification of co-benefits under the marginal abatement costs, our study provides valuable scientific insights for planning and implementing effective synergy strategies.

Generation of normal distributions revisited

AbstractNormally distributed random numbers are commonly used in scientific computing in various fields. It is important to generate a set of random numbers as close to a normal distribution as possible for reducing initial fluctuations. Two types of samples from a uniform distribution are examined as source samples for inverse transform sampling methods. Three types of inverse transform sampling methods with new approximations of inverse cumulative distribution functions are also discussed for converting uniformly distributed source samples to normally distributed samples.

Experimental investigation of surface roughness/wettability pattern effect on crystallization fouling over falling-film flow

In many industries, including desalination, scaling in heat exchangers is a persistent issue, and most methods of scaling control involve environmentally hazardous chemical additives. Exploiting the effects of surface features and flow-imposed shear on salt deposition might introduce a new approach to scale management, opening the possibility of self-cleaning surfaces. In this work, we experimentally explore surface roughness and wettability patterns interaction with salt deposition and flow shear. Heat transfer and scale mass deposition on flat surfaces are measured during thin-film evaporation of calcium sulfate solution. A wide range of surface roughness (0.027–2.66 μm) is studied at fixed flow and heat flux conditions. Due to improved mixing, heat transfer is enhanced with rougher surfaces initially; however, degrades more quickly than smoother surfaces. Following a period of initial mass deposition fluctuation, a steady scaling stage is observed, with rough surfaces scaling more than smooth surfaces. Wettability patterned surfaces can suppress crystal nucleation without sacrificing overall surface wetting, resulting in antifouling performance and heat transfer enhancement. Scale mass deposition on a patterned surface is reduced by 60 %, and 27 % heat transfer improvement over the baseline surface is found. This study provides guidance to surface manipulation for heat transfer improvement and fouling mitigation.

First study of the initial gluonic fluctuations using UPCs with ALICE

Incoherent and dissociative J/ψ photoproduction is sensitive to fluctuations of the gluonic structure of the target. Thus, the measurement of Jψ photoproduction of the colliding hadron sheds light on the initial state of QCD and provides important constraints on the initial conditions used in hydrodynamical models of heavy-ion collisions. The first measurement of the transverse momentum dependence of both coherent and incoherent Jψ photoproduction in ultraperipheral Pb–Pb collisions at midrapidity is presented. These new results provide, a clear indication of subnucleonic fluctuations of the lead target. We also present the new measurement of dissociative Jψ photoproduction cross section as a function of energy, in p–Pb collisions at forward rapidity. Dissociative results do not show any indication of saturation and agree with previous data.

Phase field crystal models with applications to laser deposition: A review.

In this article, we address the application of phase field crystal (PFC) theory, a hybrid atomistic-continuum approach, for modeling nanostructure kinetics encountered in laser deposition. We first provide an overview of the PFC methodology, highlighting recent advances to incorporate phononic and heat transport mechanisms. To simulate laser heating, energy is deposited onto a number of polycrystalline, two-dimensional samples through the application of initial stochastic fluctuations. We first demonstrate the ability of the model to simulate plasticity and recrystallization events that follow laser heating in the isothermal limit. Importantly, we also show that sufficient kinetic energy can cause voiding, which serves to suppress shock propagation. We subsequently employ a newly developed thermo-density PFC theory, coined thermal field crystal (TFC), to investigate laser heating of polycrystalline samples under non-isothermal conditions. We observe that the latent heat of transition associated with ordering can lead to long lasting metastable structures and defects, with a healing rate linked to the thermal diffusion. Finally, we illustrate that the lattice temperature simulated by the TFC model is in qualitative agreement with predictions of conventional electron-phonon two-temperature models. We expect that our new TFC formalism can be useful for predicting transient structures that result from rapid laser heating and re-solidification processes.

ATLAS measurement of mean momentum fluctuations and correlations with the flow in Xe+Xe and Pb+Pb collisions

The thermal fluctuations in the QGP medium formed in heavy ion collisions present themselves as event-wise mean transverse momentum ([pT]) fluctuations in the final state. Recent studies have shown that the fluctuations are sensitive to radial flow, random thermal motion, and nuclear deformation. They can provide constraints on the extent of thermalization of the QGP droplet. Recently, correlations of [pT] with flow harmonic coefficients (vn) also gained interest, as they were found to be sensitive primarily to the initial state fluctuations. This talk presents precise measurements of up to 3rd order [pT] cumulants as a function of multiplicity and centrality with an emphasis on ultra-central collisions. These results have strong implications for understanding the impacts of the initial condition, medium thermalization, and medium properties on final state [pT] fluctuations.