Three-state Process Research Articles

Mutual aid insurance with a three-state Markov chain

ABSTRACT Mutual aid insurance is a collective type of insurance where the policyholders share the potential losses or risks that they may face. In this paper, we establish a mathematical structure for mutual aid insurance through a three-state (good, bad and death) process, which is driven by an inhomogeneous Markov chain. The objective of maximizing an individual's lifetime utility is achieved by addressing a stochastic control problem that involves both mutual aid insurance and life insurance. We obtain the explicit expressions for optimal consumption, investment strategies, and life insurance premiums by employing the corresponding Hamilton-Jacobi-Bellman equation. In the end, we carry out a numerical analysis to show the significance of mutual aid insurance and demonstrate the optimal mutual aid insurance premium.

The effect of chrysin binding on the conformational dynamics and unfolding pathway of human serum albumin

Studies on the interactions between ligands and proteins provide insights into how a possible medication alters the structures and activities of the target or carrier proteins. The natural flavonoid aglycone Chrysin (CHR) has demonstrated anti-inflammatory, antioxidant, antiapoptotic, neuroprotective, and antineoplastic effects, both in vitro and in vivo. In this work, we investigated the impact of CHR binding on the as-yet-unexplored conformation, dynamics, and unfolding mechanism of human serum albumin (HSA). We determined CHR binding to HSA domain-II with the association constant (Ka) of 2.70 ± 0.21 × 105 M−1. The urea-induced sequential unfolding mechanism of HSA was used to elucidate the debatable binding location of CHR. CHR binding induced both secondary and tertiary structural alterations in the protein as studied by far-UV circular dichroism and intrinsic fluorescence spectroscopy. Red edge excitation shift (REES) indicated a decrease in conformational dynamics of the protein on the complex formation. This suggested an ordered compact and spatial arrangement of the CHR-boundmolecule. The binding of CHR was found to significantly modulate the urea-induced unfolding pathway of HSA. Urea-induced unfolding pathway of HSA became a two-state process (N-U) from a three-state process (N-I-U). The interaction of CHR is found to increase the thermal stability of the protein by ∼4 °C. This study focuses on the fundamental sciences and demonstrates how prospective medication compounds can alter the dynamics and stability of protein structure.

Condition-based maintenance considering imperfect inspection for a multi-state system subject to competing and hidden failures

Unexpected failures may cause huge economic losses and bring about uncontrolled risks and damage to humans and the environment. Condition-based maintenance is considered one of the most effective maintenance methods, which can reduce and eliminate possible failures and consequently ensure the safety and operating process effectiveness of systems. Inspection quality is an important factor affecting the effect of condition-based maintenance since imperfect inspection may result in inappropriate maintenance decisions. However, the factor of imperfect inspection is rarely considered when maintaining multi-state systems subjected to competing and hidden failures. In this paper, a periodical inspection policy is utilized to identify all states of a system subject to a three-state degradation process and random shocks. Inspections for all system states are considered imperfect. Upon the inspection outcome, the system may be replaced by a failure-based corrective replacement once it is detected as failed, or is renewed by a defect-based preventive replacement if a defect is identified. Moreover, an age-based preventive replacement is also required if the system is still normal up to the preset number of inspections. Subsequently, a condition-based maintenance model is constructed based on the probabilities of different renewal scenarios. Eventually, the applicability and effectiveness of the proposed model are verified by a numerical example. The results indicate that minimizing the constructed maintenance model can achieve the optimal inspection interval, which is greatly influenced by the factor of imperfect inspection. This research can provide references for decision-makers to optimize inspection and maintenance strategies.

Design of Multilevel Storage Medium through Sb2Te3/Ga2Sb3 Phase-Change Heterostructure

The phase-change heterojunction Sb2Te3/Ga2Sb3 thin films with different thickness ratios and periods were designed and prepared by the magnetron sputtering technique. The multi-level resistance states of phase-change heterojunction Sb2Te3/Ga2Sb3 film were investigated from the perspective of material and device. As for the constant thickness ratio, both the phase transition temperature and electrical resistance increase with the decrease of periods. Especially, the heterojunction [Sb2Te3(7 nm)/Ga2Sb3(3 nm)]3 film experiences the twice resistance jumps at 208 and 290 °C, respectively, exhibiting the obvious triple-resistance states. The phase structure and vibrational modes of [Sb2Te3(7 nm)/Ga2Sb3(3 nm)]3 film during the different crystallization stages were observed by the structural characterization. X-ray diffraction and Raman spectroscopy verified the changes in the phase structure and vibrational modes of the film, respectively. The [Sb2Te3(7 nm)/Ga2Sb3(3 nm)]3 film has a lower surface roughness than the pure Sb2Te3, which was proved by atomic force microscopy. Phase change memory devices based on the [Sb2Te3(7 nm)/Ga2Sb3(3 nm)]3 films were fabricated to evaluate the electrical properties and verify the three-state process of the heterostructure. All the results show that the phase-change heterostructure Sb2Te3/Ga2Sb3 films have the potential to achieve triple-state storage by tuning the thickness ratios and periods, which is conducive to improving the information storage density.

Unsynchronous conformational transitions induced by the asymmetric adsorption-response of an active diblock copolymer in an inert brush.

To exploit the chemical asymmetry of diblock copolymer chains on the design of high-performance switch sensors, we propose an analytically tractable model system which contains an adsorption-responsive diblock copolymer in an otherwise inert brush, and study its phase transitions by using both analytical theory and self-consistent field calculations. The copolymer chain is chemically asymmetric in the sense that the two blocks assume different adsorption strengths, which is characterized by the defined adsorption ratio. We found that the conformation states, the number of stable phases, and transition types are mainly controlled by the length of each block and the adsorption ratio. In particular, when the length of the ungrafted block is longer than the brush chains, and the adsorption ratio is smaller than a critical value, the copolymer chain shows three thermodynamically stable states, and undergoes two unsynchronous transitions, where the two blocks respond to the adsorption in a different manner, when the adsorption changes from weak to sufficiently strong. For this kind of three-state transition, the transition point, transition barrier, and transition width are evaluated by using the self-consistent field method, and their scaling relationship with respect to the system parameters is extracted, which matches reasonably well with the predictions from the analytical theory. The self-consistent field calculations also indicate that the conformational transitions involved in the three-state transition process are sharp with a low energy barrier, and interestingly, barrier-free transitions are observed. Our finding shows that the three-state transitions not only specify a region where high performance unsynchronous switch sensors can be exploited, but may also provide a useful model understanding the unsynchronous biological processes.

A surprisingly simple three-state generic process for reversible protein denaturation by trifluoroethanol

Despite the rich knowledge of the influence of 2,2,2-trifluoroethanol (TFE) on the structure and conformation of peptides and proteins, the mode(s) of TFE-protein interactions and the mechanism by which TFE reversibly denatures a globular protein remain elusive. This study systematically examines TFE-induced equilibrium transition curves for six paradigmatic globular proteins by using basic fluorescence and circular dichroism measurements under neutral pH conditions. The results are remarkably simple. Low TFE invariably unfolds the tertiary structure of all proteins to produce the obligate intermediate (I) which retains nearly all of native-state secondary structure, but enables the formation of extra α-helices as the level of TFE is raised higher. Inspection of the transitions at once reveals that the tertiary structure unfolding is always a distinct process, necessitating the inclusion of at least one obligate intermediate in the TFE-induced protein denaturation. It appears that the intermediate in the minimal unfolding mechanism N⇌I⇌D somehow acquires higher α-helical propensity to generate α-helices in excess of that in the native state to produce the denatured state (D), also called the TFE state. The low TFE-populated intermediate I may be called a universal intermediate by virtue of its α-helical propensity. Contrary to many earlier suggestions, this study dismisses molten globule (MG)-like attribute of I or D.

Bi-level bayesian control scheme for fault detection under partial observations

Due to limitations of sensor techniques and system structures, the internal states of most complex devices are unobservable. Only partial observations can be monitored at discrete time epochs, which poses great challenges for fault detection and prediction. To facilitate the development of advanced approaches, this paper proposes a bi-level Bayesian control scheme for detecting faults of complex devices under partial observations. The deterioration of an operational system is modeled as a hidden three-state multivariate Markov process, in which the parameter estimates are obtained by an expectation maximization (EM) algorithm. Based on the multivariate Markov process, a bi-level Bayesian control scheme is presented to monitor the Bayesian posterior probability of the system in a warning state and uses two levels of sampling frequency to dynamically detect impending failures. The decision variables of the bi-level fault detection scheme are optimized and solved in a semi-Markov decision process (SMDP) framework. The particularity of this work is that two phases of system deterioration are considered into detection scheme design to avoid unnecessary false alarms. Using partially observed multivariate data from discrete monitoring, the proposed approach is validated to be capable of detecting the early fault occurrences. By comparing with other advanced methods, the superiority of the proposed model is demonstrated.

PH Effects on the Stability and Folding of Monomeric Caspases

Caspases are an ancient class of cysteinyl proteases that play an integral part in cell development and apoptosis as an evolutionarily conserved function. During apoptosis, the intracellular pH decreases from 7.4 to ~ 6.8 and cytosolic acidification affects the activation of caspase‐3 and pH‐dependent conformational changes affect the rate of auto maturation in the dimeric procaspase‐3, which in turn influences the ability of this enzyme to execute the cell. Proteins are required to fold correctly and attain their native conformation which is vital for protein function and the survival of the organism. The protein folding landscape is sculpted through evolution and there exists an evolutionary selection for functional residues by selecting residues that stabilize the interactions to attain the native conformation while repressing the selection of non‐native interactions that take place during folding. Through the course of evolution, how these proteins fold to the native conformation to contribute to the fitness of the organism while maintaining or altering the energy landscape that is guided by trade‐offs between the stability and the activity of the protein remains elusive. To understand how the energy landscapes changed over time, we resurrected an ancestral caspase (existed about 650 milllion years ago) and we examined the folding pathways of caspases from Cnidarians, specifically corals. We studied the equilibrium unfolding of caspases from O.faveolata (species susceptible to disease) and P.astreoides (species resistant to disease) as a function of pH (between pH 3 and pH 10.5) to examine the changes in the context of stability and folding. The data shows that these monomeric proteins have a high secondary structure at the native state and unfold via a three‐state process closer to the physiological pH (pH 6.5~pH8.5), via an intermediate state which is aggregation prone. However, outside of this pH range, the native protein loses its secondary structure and exists in an intermediate state which is stable. Due to this, these proteins undergo a two‐state unfolding mechanism wherein, the protein transitions from an intermediate state to the unfolded state, reversibly. Overall, the free energy change for these primitive coral caspases is ~12.5kcal/mol, which is higher than what is observed for human caspases. This higher stability might be due to the decrease in the activity and the presence of certain stabilizing residues that are not observed in the human caspases.

Boron complexes of π-extended nitroxide ligands exhibiting three-state redox processes and near-infrared-II (NIR-II) absorption properties

Persistent radicals have attracted increasing attention owing to their fascinating properties, including multi-step redox and long-wavelength absorption characteristics. In this study, boron complexes with π-extended nitroxide ligands were synthesised via Buchwald-Hartwig amination reactions of the corresponding boron-nitroxide complex and diarylamines. These nitroxide complexes exhibited two-step and reversible one-electron oxidation processes, suggesting stable redox triads involving anionic aminoxide, neutral nitroxide-radical, and cationic oxoammonium ligands. Cationic boron complexes of the nitroxide radical ligands were obtained via chemical oxidation of the aminoxide complexes and structurally characterised. The cationic nitroxide-radical complexes exhibited strong absorptions at approximately 1100 nm, demonstrating their potential as near-infrared (NIR)-II-active functional dyes.

A logistic function to track time-dependent fish population dynamics

This paper uses a two-parameter logistic function to model the dynamics of length-at-maturation for the Barents Sea capelin over the past 47 years. We estimate the function parameters using a combination of length-age data from scientific surveys, and commercial catch statistics.Using temporal variability in the function parameters, we demonstrate that the time series of stock biomass defines a three-state Markov process, that qualitatively represent high, moderate, and collapse states of the stock biomass. We make inference about transition times between the states by calculating the mean passage times for the Markov process.Our analyses also show that maturation intensity is higher at low stock size (leading to shorter lengths at maturation), compared to when biomass levels are either high or moderately high. Our results are central to management of this stock, as uncertainty in estimating the proportion of maturing biomass affects harvest decisions and ultimately, the sustainability of the stock.

Quantitative Modeling and Analytical Calculation of Anelasticity for a Cyber-Physical System

This paper investigates resource provisioning in cyber-physical systems (CPSs) by developing a new definition of anelasticity. A flat semi-dormant multicontroller (FSDMC) model is established on a special type of CPS platform named arbitrated networked control system with dual communication channels. A novel, quantitative, and formal definition of anelasticity for the FSDMC is proposed. A new finite capacity M/M/c queuing system with N-policy and asynchronous multiple working vacations of partial servers is established, and the FSDMC is modeled as a quasi-birth-and-death process to obtain the stationary probability distribution of the system. Based on the queueing model, we quantify various performance indices of the system to build a nonlinear cost-performance ratio (CPR) function. An optimization model is presented to minimize the CPR. A particle swarm optimization (PSO) algorithm is used to find the optimum solution of the optimization model and obtain the optimal configuration values of the system parameters under stability condition. By changing the system parameters, the sensitivity of the system performance indices and the CPR are analyzed, respectively. The unexpected workload varies randomly over time. Thus, an M/M/1/K queue is constructed in a Markovian environment by employing a three-state, irreducible Markov process. In this queue, the conditional average queue length and the probabilities of the three-state process are calculated. Then, the anelasticity value of the system is precisely determined. When the average arrival rate exceeds the average service rate in the queueing system, an optimal CPR unchanged adaptive algorithm based on PSO is designed to dynamically adjust the controller service rate. Extensive numerical results show the usefulness and effectiveness of the proposed techniques and exhibit that the system can maintain elastic invariance in adaptive adjustment parameters.

A fuzzy control system for assembly line balancing with a three-state degradation process in the era of Industry 4.0

ABSTRACT The assembly line balancing problem is always explored using the assumption that the processing ability of each workstation is constant. However, the initial workload balance can be easily broken by the changing processing condition of the machines, due to degradation. In the context of Industry 4.0, real-time information related to the machine health state is available. The aim is to improve the performance of the assembly process by making full use of the obtained real-time information. This research is the first exploration of real-time assembly line balancing with the changing health states of machines and the trigger point of adjustments to the assembly line. In this study, a fuzzy control system is developed to determine when to re-balance the assembly line and how to adjust the production rates to smooth the workloads of the workstations. The numerical results show that the assembly line with the proposed fuzzy control system satisfies the demand for most cases, and achieves higher utilisation of machines and lower buffer levels. Therefore, the real-time information brought by Industry 4.0 can be used to improve the performance of an assembly line.

Industrial equipment reliability estimation: A Bayesian Weibull regression model with covariate selection

A three-state continuous-time semi-Markov process is used to model the degradation of an industrial equipment. The transition times are assumed Weibull-distributed and influenced by a set of covariates. A Weibull Regression Model is developed within the Bayesian probability framework, to account for the influence of these covariates and estimate the model parameters with the related uncertainty, on the basis of few data and expert judgment. The number of covariates is reduced by a two-step selection procedure derived from the condition monitoring engineering practice. The developed model enables estimating reliability and time-dependent state probabilities for a component degrading in given operational and ambient conditions, represented by a vector of covariates. The model is illustrated by way of a real case study concerning the degradation process affecting diaphragm valves used in the biopharmaceutical industry.

NmrLineGuru: Standalone and User-Friendly GUIs for Fast 1D NMR Lineshape Simulation and Analysis of Multi-State Equilibrium Binding Models

The ability of high-resolution NMR spectroscopy to readout the response of molecular interactions at multiple atomic sites presents a unique capability to define thermodynamic equilibrium constants and kinetic rate constants for complex, multiple-step biological interactions. Nonetheless, the extraction of the relevant equilibrium binding and rate constants requires the appropriate analysis of not only a readout that follows the equilibrium concentrations of typical binding titration curves, but also the lineshapes of NMR spectra. To best take advantage of NMR data for characterizing molecular interactions, we developed NmrLineGuru, a software tool with a user-friendly graphical user interface (GUI) to model two-state, three-state, and four-state binding processes. Application of NmrLineGuru is through stand-alone GUIs, with no dependency on other software and no scripted input. NMR spectra can be fitted or simulated starting with user-specified input parameters and a chosen kinetic model. The ability to both simulate and fit NMR spectra provides the user the opportunity to not only determine the binding parameters that best reproduce the measured NMR spectra for the selected kinetic model, but to also query the possibility that alternative models agree with the data. NmrLineGuru is shown to provide an accurate, quantitative analysis of complex molecular interactions.

Unfolding of Acinetobacter baumannii MurA proceeds through a metastable intermediate: A combined spectroscopic and computational investigation

Peptidoglycan (PG) is the main constituent of the bacterial cell wall. The enzyme UDP‑N‑acetylglucosamine enolpyruvyl transferase (MurA) catalyzes the transfer of enolpyruvate from phosphoenolpyruvate to uridinediphospho‑N‑acetylglucosamine, which is the first committed step of PG biosynthesis. In this study, we have systematically examined the urea-induced unfolding of Acinetobacter baumannii MurA (AbMurA) using various optical spectroscopic techniques and molecular dynamics (MD) simulations. The urea-induced unfolding of AbMurA was a three-state process, where a metastable intermediate conformation state is populated between 3.0 and 4.0 M. Above 6.0 M urea, AbMurA gets completely unfolded. The transition from the native structure to the partially unfolded metastable state involves ~30% loss of native contacts but little change in the radius of gyration or core hydration properties. The intermediate-to-unfolded state transition was characterized by a large increase in the radius of gyration. MD trajectories simulated in different unfolding conditions suggest that urea destabilizes AbMurA structure weakening hydrophobic interactions and the hydrogen bond network. We observed a clear correlation between both in vitro and in silico studies. To our knowledge, this is also the first report on unfolding/stability analysis of any MurA enzyme.

Protein folding: Molecular dynamics simulations and in vitro studies for probing mechanism of urea- and guanidinium chloride-induced unfolding of horse cytochrome-c

Urea- and guanidinium chloride (GdmCl)-induced denatured states of horse cytochrome-c (cyt-c) are structurally identical. It is then expected that estimates of ∆G0N→U (Gibbs free energy change in the absence of denaturants) from GdmCl- and urea-induced denaturation curves should be identical, if denaturation induced by them follows a two-state mechanism. That denaturation of cyt-c by urea or GdmCl follows a two-state mechanism is reported by some in vitro studies while other in vitro studies reported contradictory observations. Molecular dynamic (MD) simulation is a technique that could reveal the mechanism of unfolding/folding of proteins in the absence and presence of chemical denaturants at the amino acid residue level. We therefore performed multiple unconstrained MD simulations of cyt-c (PDB ID: 1HRC) in water and aqueous mixtures of GdmCl and urea for the period of 0-500 ns at 300, 400 and 450 K, which showed that denaturation of cyt-c by urea and GdmCl is a two-state and three-state process, respectively. To corroborate these findings, we measured urea- and GdmCl-induced denaturation curves of different optical properties (circular dichroism at 222, 405 and 416 nm and absorbance at 405 nm) and analyzed them for ∆G0N→U. These studies supported conclusions reached from MD simulation studies.

Volatility dependences of stock markets with structural breaks

ABSTRACTWe develop a Vector Heterogeneous Autoregression model with Continuous Volatility and Jumps (VHARCJ) where residuals follow a flexible dynamic heterogeneous covariance structure. We employ the Bayesian data augmentation approach to match the realised volatility series based on high-frequency data from six stock markets. The structural breaks in the covariance are captured by an exogenous stochastic component that follows a three-state Markov regime-switching process. We find that the stock markets have higher volatility dependence during turmoil periods and that breakdowns in volatility dependence can be attributed to the increase in market volatilities. We also find positive correlations between the Asian stock markets, the European stock market, and the UK stock market. The US stock market has positive correlations with all other markets for most of the sample periods, indicating the leading position of US stock market in the global stock markets. In addition, the proposed three-state VHARCJ model with Dynamic Conditional Correlation (DCC) and break structure under student-t distribution has a superior density forecast performance as compared to the competing models. The forecast models with structural breaks outperform those without structural breaks based on the log predicted likelihood, the log Bayesian factor, and the root mean square loss function.

Optimal Bayesian control policy for gear shaft fault detection using hidden semi-Markov model

Abstract A new optimal Bayesian control approach is presented to predict early fault of a partially observable gear shaft system subject to deterioration and random failure. The gear shaft system deterioration process is modeled as a three-state continuous time hidden semi-Markov process. States 0 and 1 are unobservable and represent the good and warning system states, respectively. Only state 2 is assumed to be observable and represents the failure state. The general Erlang distribution is considered for modeling the sojourn time in each of the hidden states, which is closer to the actual deterioration process modeling of the gear shaft system than the exponential sojourn time distribution assumed in a hidden Markov model (HMM). The optimal maintenance policy represented by a multivariate Bayesian control scheme based on a hidden semi-Markov model (HSMM) is developed. The objective is to maximize the long-run expected average availability per unit time. An effective computational algorithm is designed in the semi-Markov decision process (SMDP) framework to obtain the optimal control limit and the optimal average availability. Using multidimensional data obtained from condition monitoring, the proposed approach can not only predict early fault occurrence of the gear shaft, but also update the remaining useful life (RUL) at each sampling epoch. A comparison with other maintenance policies is given, which illustrates the effectiveness of the proposed approach.

Probing Denatured State Conformational Bias in a Three-Helix Bundle, UBA(2), Using a Cytochrome c Fusion Protein.

Previous work with the four-helix-bundle protein cytochrome c' from Rhodopseudomonas palustris using histidine-heme loop formation methods revealed fold-specific deviations from random coil behavior in its denatured state ensemble. To examine the generality of this finding, we extend this work to a three-helix-bundle polypeptide, the second ubiquitin-associated domain, UBA(2), of the human DNA excision repair protein. We use yeast iso-1-cytochrome c as a scaffold, fusing the UBA(2) domain at the N-terminus of iso-1-cytochrome c. We have engineered histidine into highly solvent accessible positions of UBA(2), creating six single histidine variants. Guanidine hydrochloride denaturation studies show that the UBA(2)-cytochrome c fusion protein unfolds in a three-state process with iso-1-cytochrome c unfolding first. Furthermore, engineered histidine residues in UBA(2) strongly destabilize the iso-1-cytochrome c domain. Equilibrium and kinetic histidine-heme loop formation measurements in the denatured state at 4 and 6 M guanidine hydrochloride show that loop stability decreases as the size of the histidine-heme loop increases, in accord with the Jacobson-Stockmayer equation. However, we observe that the His27-heme loop is both more stable than expected from the Jacobson-Stockmayer relationship and breaks more slowly than expected. These results show that the sequence near His27, which is in the reverse turn between helices 2 and 3 of UBA(2), is prone to persistent interactions in the denatured state. Therefore, consistent with our results for cytochrome c', this reverse turn sequence may help to establish the topology of this fold by biasing the conformational distribution of the denatured state.

Highly Porous Polymer Structures Fabricated via Rapid Precipitation from Ternary Systems

In this study, we present a versatile fabrication route for producing polymeric foams which is different from common phase inversion processes. Highly porous (up to ∼86%) polylactic acid (PLA) structures are produced via a rapid precipitation process wherein nonsolvent hexane is directly incorporated into PLA–dichloromethane solutions. Despite many advantages, this method is underutilized due to a complex correlation between thermodynamics and kinetics during solidification making it challenging to control and understand. We describe the phase separation of these systems as a three-state process which contributes to the current knowledge and understanding of the nonsolvent induced solid–liquid phase separation process. Also, we show that the shish-kebab morphologies formed in certain foams may result in an increase in their compressive modulus. The flexibility of this fabrication route allows for producing highly porous PLA structures for various applications such as acoustic and tissue engineering.