Time Dependence Research Articles

Revisiting shear stress tensor evolution: Nonresistive magnetohydrodynamics with momentum-dependent relaxation time

This study aims to develop second-order relativistic viscous magnetohydrodynamics (MHD) derived from kinetic theory within an extended relaxation time approximation (momentum/energy dependent) for the collision kernel. The investigation involves a detailed examination of shear stress tensor evolution equations and associated transport coefficients. The Boltzmann equation is solved using a Chapman-Enskog-like gradient expansion for a charge-conserved conformal system, incorporating a momentum-dependent relaxation time. The derived relativistic nonresistive, viscous second-order MHD equations for the shear stress tensor reveal significant modifications in the coupling with dissipative charge current and magnetic field due to the momentum dependence of the relaxation time. By utilizing a power law parametrization to quantify the momentum dependence of the relaxation time, the anisotropic magnetic field-dependent shear coefficients in the Navier-Stokes limit have been investigated. The resulting viscous coefficients are seen to be sensitive to the momentum dependence of the relaxation time. Published by the American Physical Society 2024

Polygenic hazard score models for the prediction of Alzheimer's free survival using the lasso for Cox's proportional hazards model.

The prediction of the susceptibility of an individual to a certain disease is an important and timely research area. An established technique is to estimate the risk of an individual with the help of an integrated risk model, that is, a polygenic risk score with added epidemiological covariates. However, integrated risk models do not capture any time dependence, and may provide a point estimate of the relative risk with respect to a reference population. The aim of this work is twofold. First, we explore and advocate the idea of predicting the time-dependent hazard and survival (defined as disease-free time) of an individual for the onset of a disease. This provides a practitioner with a much more differentiated view of absolute survival as a function of time. Second, to compute the time-dependent risk of an individual, we use published methodology to fit a Cox's proportional hazard model to data from a genetic SNP study of time to Alzheimer's disease (AD) onset, using the lasso to incorporate further epidemiological variables such as sex, APOE (apolipoprotein E, a genetic risk factor for AD) status, 10 leading principal components, and selected genomic loci. We apply the lasso for Cox's proportional hazards to a data set of 6792 AD patients (composed of 4102 cases and 2690 controls) and 87 covariates. We demonstrate that fitting a lasso model for Cox's proportional hazards allows one to obtain more accurate survival curves than with state-of-the-art (likelihood-based) methods. Moreover, the methodology allows one to obtain personalized survival curves for a patient, thus giving a much more differentiated view of the expected progression of a disease than the view offered by integrated risk models. The runtime to compute personalized survival curves is under a minute for the entire data set of AD patients, thus enabling it to handle datasets with 60,000-100,000 subjects in less than 1 h.

Time-dependent characteristics of analytical measurands.

Biological variation is a relevant component of diagnostic uncertainty. In addition to within-subject andbetween-subject variation, preanalytical variation also includes components that contribute to biological variability. Among these, daily recurring, i.e.,diurnal physiological variation is of particular importance, as it contains both a random and a non-random component ifthe exact time of blood collection is not known. We introduce four time-dependent characteristics (TDC) of diurnal variations for measurands to assess the relevance and extent of time dependence on the evaluation of laboratory results. TDC address (i)a threshold for considering diurnality, (ii) the expected relative changes per time unit, (iii) the permissible time interval between two blood collections at different daytimes within which the expected time dependence does not exceed a defined analytical uncertainty, and (iv) a rhythm-expanded reference change value. TDC and their importance will be exemplified by the measurands aspartate aminotransferase, creatine kinase, glucose, thyroid stimulating hormone, and total bilirubin. TDCs are calculated for four time slots that reflect known blood collection schedules, i.e.,07:00-09:00, 08:00-12:00, 06:00-18:00, and 00:00-24:00. The amplitude and the temporal location of the acrophase are major determinates impacting the diagnostic uncertainty and thus the medical interpretation, especially within the typical blood collection time from 07:00 to 09:00. We propose to check measurands for the existence of diurnal variations and, if applicable, to specify their time-dependent characteristics as outlined in our concept.

Effect and mechanism of time-dependent and economical expansion materials in improving the active roof-contact for cemented paste backfill

During the backfilling process, there is often a problem of no roof-contact, and the time and state of roof-contact cannot be predicted, seriously affecting the backfilling safety and efficiency. Therefore, the expansion effect, mechanism, and time dependence of the expansion agents used to achieve roof-contact were studied through expansion ratio tests, strength tests, and microscopic analysis. The expansion ratio of the MgO-type expansion agent (MEA) can meet the requirement of backfilling, and the unconfined compressive strength (UCS) of the expansive cemented paste backfill (ECPB) was attenuated compared to that of ordinary cemented paste backfill (CPB). Through scanning electron microscope (SEM) and mercury intrusion porosimetry (MIP) of the MgO-type ECPB, it is found that the ECB produces Mg(OH)2 crystals, which improves the compensation space inside the ECPB. MIP analysis results also show that the ECPB has higher porosity and more macropores, which is the reason for the strength attenuation of the ECPB. It is found that the expansion ratio and sedimentation ratio of fresh ECPB are time-dependent, and they both conform to logarithmic function. Afterwards, through the dynamic relationship between the sedimentation and expansion of fresh ECPB, the synthetic criterion of roof-contact based on the time-dependent model of expansion ratio and sedimentation ratio was established. The theoretical shortest roof-contact time of different experimental groups was obtained. Finally, through a comparative analysis of backfilling costs, the lowest cost and reasonable backfilling scheme were obtained. It is of great value for judging the effectiveness of roof contact, optimizing the backfilling proportion scheme, ensuring backfilling safety, and saving backfilling and mining costs.

Plume-scale confinement on thermal convection

Despite the ubiquity of thermal convection in nature and artificial systems, we still lack a unified formulation that integrates the system's geometry, fluid properties, and thermal forcing to characterize the transition from free to confined convective regimes. The latter is broadly relevant to understanding how convection transports energy and drives mixing across a wide range of environments, such as planetary atmospheres/oceans and hydrothermal flows through fractures, as well as engineering heatsinks and microfluidics for the control of mass and heat fluxes. Performing laboratory experiments in Hele-Shaw geometries, we find multiple transitions that are identified as remarkable shifts in flow structures and heat transport scaling, underpinning previous numerical studies. To unveil the mechanisms of the geometrically controlled transition, we focus on the smallest structure of convection, posing the following question: How free is a thermal plume in a closed system? We address this problem by proposing the degree of confinement [Formula: see text]-the ratio of the thermal plume's thickness in an unbounded domain to the lateral extent of the system-as a universal metric encapsulating all the physical parameters. Here, we characterize four convective regimes different in flow dimensionality and time dependency and demonstrate that the transitions across the regimes are well tied with [Formula: see text]. The introduced metric [Formula: see text] offers a unified characterization of convection in closed systems from the plume's standpoint.

The cosmological collider in R 2 inflation

Starobinsky's R 2 inflation manifests a best-fit scenario for the power spectrum of primordial density fluctuations. Observables derived from the slow-roll picture of the R 2 model in the Einstein frame relies on the conformal transformation of the metric, which inevitably induces a unique exponential-type couplings of the rolling scalaron with all matter fields during inflation. The “large-field” nature of the R 2 model further invokes non-negligible time and scale dependence to the matter sector through such an exponential coupling, modifying not only the dynamics of matter perturbations on superhorizon scales but also their decay rates. In this work, we identify the simplest observable of the cosmological collider physics built in the background of R 2 inflation, focusing on the so-called “quantum primordial clock” signals created by the non-local propagation of massive scalar perturbations. Our numerical formalism based on the unique conformal coupling can have extended applications to (quasi-)single-field inflationary models with non-trivial couplings to gravity or models that originated from the f(R) modification of gravity.

Real-time multivariate statistical monitoring of biopharmaceutical processes with no prior product-specific history

Biologics drug substance manufacturing normally comprises several processing steps including cell culture, purification, etc. Real-time Multivariate Statistical Process Monitoring (RT-MSPM) is an integral need in order to achieve early fault detection and prevention to guarantee robust and efficient process performance. As a part of RT-MSPM framework, Batch Evolution Models (BEMs), which take into account the transient phase of a batch prior to reaching full maturity (steady state), are the standard methods for real-time early fault detection in batch processes. Prior product-specific knowledge and training dataset are critical in order to model time (batch maturity) dependencies. Unlike traditional settings, modern biopharmaceutical manufacturing and clinical facilities use modular designs to enable simultaneous production of multiple medicines and quickly pivot from producing one medicine to another where no prior product-specific historical data might be available. In this article, first, a framework is proposed to detect the steady state operation of a manufacturing scale cell culture bioreactor. This is critical to achieve the ultimate goal to demonstrate feasibility of developing a continuous statistical process monitoring framework to monitor the steady state operation of a batch with no prior product specific history. Steady state time series data from previous step are processed following a systematic approach. The requirements for statistical properties of the processed time series in order to leverage data from different products to monitor a new product are outlined. The new framework establishes a guideline to develop models using datasets from other products with different recipes to monitor new products with no prior product-specific history. A novel software product is developed to test the framework. The framework is successfully applied for real-time monitoring of fast-rate sensors of a manufacturing cell culture bioreactor.

Systematic experimental and model-based evaluation of the synergistic effects of alloy composition and damage rate on the formation of Cr-rich precipitates in Fe–Cr–Al alloys under ion irradiation

Fourteen Fe–Cr–Al alloys with systematically varied Cr and Al compositions were irradiated at 350∘C to 0.24 dpa by 10.5 MeV self-ions as model alloys for the Fe–Cr–Al (oxide dispersion strengthened: ODS) alloys being developed as accident tolerant fuel (ATF) cladding for light water reactors. Three dose rates (8×10−6, 8×10−5, and 8×10−4 dpa/s) were selected to predict the formation behavior of Cr-rich precipitates (CrRP) under neutron irradiation conditions. The effects of Cr, Al composition, and dose rate on the CrRP formation behavior were evaluated using a three-dimensional atom probe (3DAP) analysis. The results showed that the CrRP number density, volume fraction, and Cr concentration increase with increasing Cr composition, decreasing Al composition, and decreasing dose rate. Multiple regression analysis showed that in addition to these primary effects, there was an interaction between them on the CrRP volume fraction: (1) the higher the Al composition, the smaller the increase in the CrRP volume fraction with increasing Cr composition, and (2) the lower the Cr composition, the smaller the increase in the CrRP volume fraction with the decreasing Al composition and dose rate. It was also highlighted that to understand the dose rate effect on the CrRP formation behavior under neutron irradiation, it is useful to examine the irradiation time dependence, including the effective use of thermal aging data as a limit to the zero dose rate, in addition to the the dose-dependency perspective. In addition to the systematic database of CrRP-related quantities established in this study, these considerations should contribute to further developing and validating numerical prediction models.

Time-series weather prediction in the Red sea using ensemble transformers

Accurately predicting Sea Surface Temperature (SST) and Wind Speed (WS) in the Red Sea is crucial for maritime safety, climate research, and ecosystem monitoring. However, modeling SST and WS is challenging due to the region’s complex and dynamic oceanic and atmospheric processes. This study introduces advanced predictive models based on Transformers to enhance the accuracy of SST and WS predictions by capturing time dependencies and modeling sequential data. A novel stacked architecture, named StackPred, improves the performance of individual Transformer models. Additionally, wavelet-based multiscale filtering is applied during preprocessing to separate relevant signals from noise, further enhancing prediction accuracy. The prediction performance is validated using publicly available SST and WS data from ten different locations in the Red Sea. Results consistently demonstrate the superiority of the proposed stacked deep learning models over existing techniques, including LSTM (Long Short-Term Memory), BiLSTM (Bidirectional LSTM), GRU (Gated Recurrent Unit), BIGRU (Bidirectional GRU), and single Transformers. Moreover, integrating wavelet denoising with StackPred significantly improves predictive performance compared to using data without denoising. The StackPred model achieves strong performance with an average R2 score of 99.83 for predicting SST and 99.96 for WS.

ASSESSMENT OF THE CORROSION-MECHANICAL PROPERTIES OF THE LEFT MATERIALS AND FORECASTING THE SAFETY OF GAS TURBINE PARTS

Purpose. Determination of the possibility of using the temperature-time parametric dependences of Miller-Larson, Manson-Haferd, and Sherby-Dorn for long-term prediction of the strength characteristics of parts subjected to oxidation and high-temperature sulfide-oxidation effects. Research methods. Long-term strength studies were performed on samples of ВЖЛ-12У and ЗМІ-3У alloys in synthetic ash (66.2 % Na2SO4, 20.4 % Fe2O3, 8.3 % NiO, 3.3 % CaO, 1.8 % V2O5) and an oxidizing environment at temperatures of 800 °C and 850 °C. The Miller-Larson, Manson-Haferd, and Sherby-Dorn temperature-time parametric dependences were used to predict the tensile strength of materials in an oxidizing and corrosive environment. The microstructure of the samples was studied using an optical microscope MIM-8M. Results. The results obtained indicate a high level of corrosion resistance of ЗМІ-3У samples at 800 °C and 850 °C and the possibility of determining the tensile strength of the material for a period of 1000, 5000, and 10000 hours by the calculation method. Tests of ВЖЛ-12У alloy samples in synthetic ash showed a discrepancy between the experimental time to fracture and the calculated value, regardless of the parametric method, which indicates a direct dependence of long-term strength on the degree of corrosion damage to the surface of the samples. Scientific novelty. The possibility of using the Miller-Larson, Manson-Haferd, and Sherby-Dorn temperature-time parametric dependences for long-term prediction of the strength characteristics of parts in an oxidizing environment has been confirmed. In a sulfide-oxide environment, the use of parametric methods to determine strength characteristics for up to 10,000 hours is possible only for corrosion-resistant alloys. Intensive corrosion damage to ВЖЛ-12У alloy leads to accelerated deformation, which limits the use of temperature and time dependencies for effective prediction of the time of failure of parts made of this material. Practical value. Determining a reliable method for predicting the strength characteristics of heat-resistant alloys in an oxidizing and corrosive environment allows reducing the time and financial costs of conducting lengthy field studies.

Mechanism and rate of anomalous extraction of chloride salts from water to 1,2-dichloroethane

Open circuit potential (OCP) measurements, potentiostatic pulse (PP) amperometry and cyclic voltammetry (CV), were used to investigate and to sort by rate the anomalous extraction of the chloride salts RCl of the cations R+ = tetrabutylammonium (TBA+), tetrapentylammonium (TPeA+), tetrahexylammonium (THexA+), tetraheptylammonium (THepA+) and bis(triphenyl-phosphoranylidene)ammonium (BA+) from water to 1,2-dichloroethane (DCE). A tentative mechanism is proposed comprising (a) the diffusion-controlled transport of the ion-pairs (RCl)ip from the aqueous to the organic solvent phase providing a major contribution to the chloride extraction, (b) decomposition of the multiple ion-pairs or clusters (RCl)ipx, which are formed by agglomeration of the single ion-pairs (RCl)ip in the aqueous phase (w), and (c) the exponential decay of the ion-pairs (RCl)ip accumulated on the organic solvent side of the interface at the beginning of the OCP measurements. This model enables to simulate successfully the experimental time dependence of the chloride concentration. A conclusion is made that the effect of the composition of the organic solvent electrolyte RX, where X- = tetraphenylborate (TPB-) or tetrakis(pentafluorophenyl) borate (TB-), on the rate and extent of the anomalous accumulation of the chloride anion in the phase (o) of the two-phase liquid system LiCl(w)/RX(o) can be related to the hydrophobicity of the electrolytes RCl and RX. The latter property can be characterized by the standard Gibbs energy of transfer from the aqueous (w) to the organic solvent (o) phase. The accumulation of the chloride anion in the phase (o) appears to be promoted by the decreasing value of the transfer Gibbs energy of RCl in the sequence TBACl > TPeACl > THexACl > THepACl > BACl, while the decreasing value of the transfer Gibbs energy of RX in the sequence TBATPB > TPeATPB > THexATPB > THepATPB > BATPB > BATB starts to block the cycle combining the energetically unfavorable extraction of RX from the phase (o) to the phase (w) with the energetically favorable extraction of RCl in the opposite direction. IR spectroscopy provides evidence of the formation of the water clusters in the organic solvent phase equilibrated with the aqueous phase in the presence of the tetraalkylammonium cation in both phases, which are supposed to drive the anomalous accumulation of the chloride anion in the phase (o).

ANALYSIS OF ROUTING PROTOCOLS CHARACTERISTICS IN AD-HOC NETWORK

Background. Wireless ad-hoc networks are becoming increasingly prevalence in remote areas, in extreme environments, even in military operations, and in scenarios where setting up infrastructure networks is not possible. Research of ad-hoc routing protocols problems allows improving the efficiency of their operation in conditions of high variability in packet loss or instability of network operation when the speed of users changes. Objective. The purpose of the paper is analysis of packet loss dependency from a network operation time, study of a user speed influence on a network efficiency, and research of network operation efficiency with different routing protocols. Methods. The method of routing protocols efficiency evaluation is the simulation of their operation in an ad-hoc network on a test data set and research of a network indicators dependency in time under different loads and changing mobility of users. Results. The conducted research demonstrated that user’s mobility at different speeds significantly affects the network operation as a whole. The instability of users' positions leads to a significant increase in route search time and packet transmission time. Among researched GPSR, DSDV, and AODV protocols, the latter proved to be the best because it has the lowest percentage of data loss and the lowest average time of message send and receive operations. Conclusions. The work is dedicated to the actual problem of developing and setting parameters of ad-hoc network. Received research results indicate the need to choose the optimal routing protocol depending on specific application conditions, such as user movement speed and network stability. The proposed solutions can be the first stage of complex processing of packets in the mobile network and justify the choice of AODV protocol as a basis for further improvement.

Investigation of the temperature dependence of the dielectric relaxation of chlorobenzene, bromobenzene and iodobenzene

This paper deals with the investigation results of temperature dependence of complex permittivity’sε∗ = έ − iε˝ of chloro, bromo and iodo- benzene at wavelength 11,50 cm and 12,80 cm within the temperature range 20 ÷ -80˚. It is established that dielectric properties of given liquids are characteristic of one relaxation time. The dielectric spectra were studied taking into account other frequencies given in the literature. In all investigated liquids, a jump appears in the real and imaginary parts of the complex permittivity at the point of the phase transition. The temperature dependence of the dielectric relaxation time of molecules in the liquid state has been determined. It was found that with an increase in the amount of the halogen substituent, an increase in the relaxation time occurs. Macroscopic and molecular relaxation times were calculated from the experimental values. The thermodynamic quantities characterizing the process of dielectric relaxation are calculated. The activation enthalpy of dielectric relaxation processes is compared. The studies were carried out using the dielectric spectroscopy method. This method allows a more detailed study of the dielectric properties of the objects of study due to the large equilibrium (“static”) dielectric constant of the object. It has been determined that the height of the potential barrier separating the two equilibrium positions of a polar molecule is greatest in the state of a pure polar liquid and decreases with dilution in a non-polar solvent.

Analytical description of the ionic relaxation in the presence of surface adsorption

The temporal evolution of the surface electric field in a cell in the presence of ionic adsorption is investigated. The analysis is performed in the framework of the Poisson–Nernst–Planck model, based on the conservation of particles and the equation of Poisson for the actual electric potential across the cell, assuming that only the ions of a given sign are mobile. The adsorption is described using a kinetic equation of Langmuir’s type. The simple case of small adsorption is considered, in which the saturation effect can be neglected, and the fundamental equations of the model can be linearized. In this framework, the effective relaxation time describing the dynamics of the system is evaluated, as well as the profiles of the ions and the electric field. The case in which the sample is a half-space is first considered. A more realistic situation where the sample is a slab of thickness d, limited by two identical or different electrodes, is analyzed too. The difference in electric potential due to the adsorption phenomenon between the electrodes is determined. Our analysis shows that its time dependence, when the electrodes have different adsorption properties, is not monotonic.

Deconvoluting Monomer- and Dimer-Specific Distance Distributions between Spin Labels in a Monomer/Dimer Mixture Using T1-Edited DEER EPR Spectroscopy.

Double electron-electron resonance (DEER) EPR is a powerful tool in structural biology, providing distances between pairs of spin labels. When the sample consists of a mixture of oligomeric species (e.g., monomer and dimer), the question arises as to how to assign the peaks in the DEER-derived probability distance distribution to the individual species. Here, we propose incorporating an EPR longitudinal electron relaxation (T1) inversion recovery experiment within a DEER pulse sequence to resolve this problem. The apparent T1 between dipolar coupled electron spins measured from the inversion recovery time (τinv) dependence of the peak intensities in the T1-edited DEER-derived probability P(r) distance distribution will be affected by the number of nitroxide labels attached to the biomolecule of interest, for example, two for a monomer and four for a dimer. We show that global fitting of all the T1-edited DEER echo curves, recorded over a range of τinv values, permits the deconvolution of distances between spin labels originating from monomeric (longer T1) and dimeric (shorter T1) species. This is especially useful when the trapping of spin labels in different conformational states during freezing gives rise to complex P(r) distance distributions. The utility of this approach is demonstrated for two systems, the β1 adrenergic receptor and a construct of the huntingtin exon-1 protein fused to the immunoglobulin domain of protein G, both of which exist in a monomer-dimer equilibrium.

Mesoscopic elasticity controls dynamin-driven fission of lipid tubules

Mesoscale physics bridges the gap between the microscopic degrees of freedom of a system and its large-scale continuous behavior and highlights the role of a few key quantities in complex and multiscale phenomena, like dynamin-driven fission of lipid membranes. The dynamin protein wraps the neck formed during clathrin-mediated endocytosis, for instance, and constricts it until severing occurs. Although ubiquitous and fundamental for life, the cooperation between the GTP-consuming conformational changes within the protein and the full-scale response of the underlying lipid substrate is yet to be unraveled. In this work, we build an effective mesoscopic model from constriction to fission of lipid tubules based on continuum membrane elasticity and implicitly accounting for ratchet-like power strokes of dynamins. Localization of the fission event, the overall geometry, and the energy expenditure we predict comply with the major experimental findings. This bolsters the idea that a continuous picture emerges soon enough to relate dynamin polymerization length and membrane rigidity and tension with the optimal pathway to fission. We therefore suggest that dynamins found in in vivo processes may optimize their structure accordingly. Ultimately, we shed light on real-time conductance measurements available in literature and predict the fission time dependency on elastic parameters.

Lessons learned: avoiding bias via multi-state analysis of patients’ trajectories in real-time

ObjectivesMany studies have attempted to determine the disease severity and patterns of COVID-19. However, at the beginning of the pandemic, the complex patients’ trajectories were only descriptively reported, and many analyses were worryingly prone to time-dependent-, selection-, and competing risk biases. Multi-state models avoid these biases by jointly analysing multiple clinical outcomes while taking into account their time dependency, including current cases, and modelling competing events. This paper uses a publicly available data set from the first wave in Israel as an example to demonstrate the benefits of analysing hospital data via multi-state methodology.MethodsWe compared the outcome of the data analysis using multi-state models with the outcome obtained when various forms of bias are ignored. Furthermore, we used Cox regression to model the transitions among the states in a multi-state model. This allowed for the comparison of the covariates’ influence on transition rates between the two states. Lastly, we calculated expected lengths of stay and state probabilities based on the multi-state model and visualised it using stacked probability plots.ResultsCompared to standard methods, multi-state models avoid many biases in the analysis of real-time disease developments. The utility of multi-state models is further highlighted through the use of stacked probability plots, which visualise the results. In addition, by stratification of disease patterns by subgroups and visualisation of the distribution of possible outcomes, these models bring the data into an interpretable form.ConclusionTo accurately guide the provision of medical resources, this paper recommends the real-time collection of hospital data and its analysis using multi-state models, as this method eliminates many potential biases. By applying multi-state models to real-time data, the gained knowledge allows rapid detection of altered disease courses when new variants arise, which is essential when informing medical and political decision-makers as well as the general population.

Edge-dependent anomalous topology in synthetic photonic lattices subject to discrete step walks

Anomalous topological phases, where edge states coexist with topologically trivial Chern bands, can only appear in periodically driven lattices. When the driving is smooth and continuous, the bulk-edge correspondence is guaranteed by the existence of a bulk invariant known as the winding number. However, in lattices subject to periodic discrete step walks the existence of edge states does not only depend on bulk invariants but also on the boundary. This is a consequence of the absence of an intrinsic time dependence or micromotion in discrete step walks. We report the observation of edge states and a simultaneous measurement of the bulk invariants in anomalous topological phases in a two-dimensional synthetic photonic lattice subject to discrete step walks. The lattice is implemented using time multiplexing of light pulses in two coupled fibre rings, in which one of the dimensions displays real-space dynamics and the other one is parametric. The presence of edge states is inherent to the periodic driving and depends on the properties of the boundary in the implemented two-band model with zero Chern number. We provide a suitable expression for the topological invariants whose calculation does not rely on micromotion dynamics. Published by the American Physical Society 2024

An Agile Adaptive Biased-Randomized Discrete-Event Heuristic for the Resource-Constrained Project Scheduling Problem

In industries such as aircraft or train manufacturing, large-scale manufacturing companies often manage several complex projects. Each of these projects includes multiple tasks that share a set of limited resources. Typically, these tasks are also subject to time dependencies among them. One frequent goal in these scenarios is to minimize the makespan, or total time required to complete all the tasks within the entire project. Decisions revolve around scheduling these tasks, determining the sequence in which they are processed, and allocating shared resources to optimize efficiency while respecting the time dependencies among tasks. This problem is known in the scientific literature as the Resource-Constrained Project Scheduling Problem (RCPSP). Being an NP-hard problem with time dependencies and resource constraints, several optimization algorithms have already been proposed to tackle the RCPSP. In this paper, a novel discrete-event heuristic is introduced and later extended into an agile biased-randomized algorithm complemented with an adaptive capability to tune the parameters of the algorithm. The results underscore the effectiveness of the algorithm in finding competitive solutions for this problem within short computing times.

Spatial and temporal dynamics of thermal motion of a chain of liquid lead nanoinclusions attached to a fixed dislocation segment in an aluminum matrix

Thermal motion of a chain of liquid lead nanoinclusions attached to a dislocation segment fixed at its ends in the aluminum-based alloy was studied in situ using TEM in the temperature range from 442 °C to 497 °C. The projections of points of the trajectories of the inclusions onto the dislocation line were analyzed. The evidence for the collective interaction of all the inclusions and their spatially correlated collective thermal motion was obtained. Also, moderate temporal autocorrelation of thermal motion of the inclusions and a very weak temporal cross-correlation of thermal motion of the inclusions in all pairs was shown. The FFT phase spectra of the time dependencies of the inclusions positions on the dislocation segment give the evidence for the phase synchronization of thermal oscillations of the inclusions. It is shown that the thermal oscillations of the terminal inclusion attached to the dislocation node and elevation of temperature lead to decrease in the level of synchronization of thermal oscillations of the inclusions in the chain. It is indicated that the development of the process of desynchronization of thermal oscillations of the inclusions manifests itself by an increase in the density of phase steps in the initially linear unwrapped phase spectra accompanying by an increase in the interaction of the steps.