Two-state Model Research Articles

Controlled protein adsorption on a silica microparticle.

In the present study, controlled protein adsorption on a rigid silica microparticle is investigated numerically using classical Langmuir and two-state models under electrokinetic flow conditions. The instantaneous particle locations are simulated along a straight microchannel using an arbitrary Lagrangian-Eulerian framework in the finite element method for the electrophoretic motion of the charged particle. Within the scope of the parametric study, the strength of the external electric field (E), particle diameter (Dp ), the zeta potential of the particle (ζp ), and the location of the microparticle away from the channel wall (H) are systematically varied. The results are also compared to the data of pressure-driven flow having a parabolic flow profile at the inlet whose maximum magnitude is set to the particle's electrophoretic velocity magnitude. The validation studies reveal that the code developed for the particle motion in the present simulations agrees well with the experimental results. It is observed that protein adsorption can be controlled using electrokinetic phenomena. The plug-like flow profile in electrokinetics is beneficial for a microparticle at every spatial location in the microchannel, whereas it is not valid for the pressure-driven flow. The electric field strength and the zeta potential of the particle accelerate the protein adsorption. The wall shear stress and shear rate are good indicators to predict the adsorption process for electrokinetic flow.

CALPHAD modeling based on Gibbs energy functions from zero kevin and improved magnetic model: A case study on the Cr–Ni system

The third-generation thermodynamic database that adopts the physics-based models over a wide temperature range is being developed in an attempt to increase the predictability and reliability of the CALPHAD (Calculation of Phase Diagrams) method. As a case study, this work used the new CALPHAD models to reoptimize Cr, Ni, and the Cr–Ni system. For pure elements, the Gibbs free energy of solid phases was described by a model considering various physical contributions, and the amorphous and liquid phases were described together by the two-state model. For Cr–Ni solution phases, thermodynamic modeling of the magnetic phase diagram was supported by ab initio calculations. This work demonstrated the way of performing thermodynamic assessment using the third-generation Gibbs free energy functions with the improved description of magnetic properties.

Pricing effects of the electricity market reform in Brazil

We examine electricity market reform in Brazil. From 1998 until 2004, the largely hydro-powered market featured a forward market in which bilateral contracts were negotiated. In March 2004, this was partially replaced by a centralised clearing of forward positions, with the objective of stabilising electricity prices. We develop a theoretical model for the Brazilian forward electricity market, showing how generator entry would be affected by the two regimes. We then model monthly prices using a two-state Markov Switching model, allowing offtakes to affect prices, volatility and transition probabilities. Consistent with our theory, we show that while the reforms decreased volatility in some regions and states, the market became both more likely to enter a high price state, and more likely to remain in that state for a protracted period.

The Folding Pathway of 6aJL2.

One-third of the reported cases of light chain amyloidosis are related to the germ line λ6 family; remarkably, healthy individuals express this type of protein in just 2% of the peripheral blood and bone marrow B-cells. The appearance of the disease has been related to the inherent properties of this protein family. A recombinant representative model for λ6 proteins called 6aJL2 containing the amino acid sequence encoded by the 6a and JL2 germ line genes was previously designed and synthesized to study the properties of this family. Previous work on 6aJL2 suggested a simple two-state folding model at 25 °C; no intermediate could be identified either by kinetics or by fluorescence and circular dichroism equilibrium studies, although the presence of an intermediate that is populated at ∼2.4 M urea was suggested by size exclusion chromatography. In this study we employed classic equilibrium and kinetic experiments and analysis to elucidate the detailed folding mechanism of this protein. We identify species that are kinetically accessible and/or are populated at equilibrium. We describe the presence of intermediate and native-like species and propose a five-species folding mechanism at 25 °C at short incubation times, similar to and consistent with those observed in other proteins of this fold. The formation of intermediates in the mechanism of 6aJL2 is faster than that proposed for a Vκ light chain, which could be an important distinction in the amyloidogenic potential of both germ lines.

The Finite Size Effects and Two-State Paradigm of Protein Folding.

The coil to globule transition of the polypeptide chain is the physical phenomenon behind the folding of globular proteins. Globular proteins with a single domain usually consist of about 30 to 100 amino acid residues, and this finite size extends the transition interval of the coil-globule phase transition. Based on the pedantic derivation of the two-state model, we introduce the number of amino acid residues of a polypeptide chain as a parameter in the expressions for two cooperativity measures and reveal their physical significance. We conclude that the measure, defined as the ratio of van ’t Hoff and calorimetric enthalpy is related to the degeneracy of the denatured state and describes the number of cooperative units involved in the transition; additionally, it is found that the widely discussed is just the necessary condition to classify the protein as the two-state folder. We also find that , a quantity not limited from above and growing with system size, is simply proportional to the square of the transition interval. This fact allows us to perform the classical size scaling analysis of the coil-globule phase transition. Moreover, these two measures are shown to describe different characteristics of protein folding.

Conflict and Sensitivity Analysis of Vehicular Stability Using a Two-State Linear Bicycle Model

Vehicle parameters and operation conditions play a critical role in vehicular handling and stability. This study aimed to evaluate vehicle stability based on cornering tire stiffness integrated with vehicle parameters. A passenger vehicle is considered in which a two-state linear bicycle model is developed in the Matlab/Simulink. The effect of the vehicle parameters on lateral vehicle stability has been investigated and analyzed. The investigated parameters included CG longitudinal position, wheelbase, and tire cornering stiffness. Furthermore, the effects of load variation and vehicle speed were addressed. Based on a Fishhook steering maneuver, the lateral stability criteria represented in lateral acceleration, yaw rate, vehicle sideslip angle, tire sideslip angles, and the lateral tire force were analyzed. The results demonstrated that the parameters that affect the lateral vehicle stability the most are the cornering stiffness coefficient and the CG longitudinal location. The findings also indicated a positive correlation between vehicle properties and lateral handling and stability.

Spherical-deformed mixing in Zr94

I have applied a simple two-state mixing model to $E2$ strengths from a recent $^{94}\mathrm{Zr}(n,{n}^{\ensuremath{'}}\ensuremath{\gamma})$ experiment in order to obtain the mixing amplitudes between spherical and deformed basis states in $^{94}\mathrm{Zr}$. The fits also provide the transition matrix elements connecting the basis states.

Stochastic Resonance in Thermally Bistable Josephson Weak Links and Micro-SQUIDs

Constriction-based Josephson weak-links display a thermal bi-stability between two states exhibiting zero and finite voltages. This manifests in experiments either as hysteresis in weak-links current voltage characteristics or as random telegraphic signal in voltage. In the latter case, a noise-driven amplification of a sinusoidal excitation of the device is observed, at frequencies matching the characteristic switching frequency in telegraphic signal, a phenomenon known as stochastic resonance. The observed behavior is understood using a two-state model of stochastic resonance and is exploited to illustrate an enhanced signal-to-noise-ratio in a micro-SQUID as a magnetic field sensor.

Second-order Markov chain models of rainfall in Ibadan, Southwest Nigeria

Understanding the dynamics of rainfall is important for maximizing the agricultural potential, environmental planning, as well as policy development. In this study, a two-state second-order Markov chain model was developed for the annual and daily occurrence of different rainfall sequences in Ibadan, southwestern Nigeria. The annual variation was adapted to a sine series model. The model was able to account for more than 30% of the observed variation. Markov chain approach to modelling rainfall in tropical region is unique because it considers the “memory” – previous rainfall events, which is lacking in other methods. The daily occurrences showed patterns consistent with tropical regions. Results from this study is significant for economic, health and environmental planning in the location.

Negative Interdomain Coupling of Dystrophin Spectrin Repeats

Spectrin repeat domains are a highly conserved biological motif found in many human structural proteins. Dystrophin contains 24 tandem spectrin repeats which provide structural support through mediating interactions between intracellular actin filaments and the extracellular matrix. However, the molecular mechanism by which dystrophin provides this support is unknown. Understanding this underlying structure/function relationship is important because mutations in dystrophin directly cause muscular dystrophy. Thus far, the following constructs have been expressed in E. coli, purified using chromatography, and thermodynamically characterized: S17, S17-18, S17-19. Parameters were determined through globally fitting thermal denaturation signals from Fluorescence Spectroscopy (FS), Circular Dichroism (CD), and Fluorescence Lifetime Spectroscopy (FLT) to a two-state model of unfolding. Fits were constrained using ΔCp values determined using Differential Scanning Calorimetry (DSC). This parameterization then allowed for determination of the free energy of stability (ΔGunfolding) of each construct. Results indicate that the ΔGunfolding of S17 is nearly double that of S17-19. This pronounced non-additivity indicates that tandem spectrin repeats mutually destabilize each other, termed negative coupling. Additionally, the comparison of Electron Paramagnetic Resonance (EPR) spectra of S17 and S17-19 indicate that the trimer exhibits greater local confirmational flexibility, consistent with decreased stability. To further test this negative coupling hypothesis, we are purifying S19 for thermodynamic characterization. This will allow for the comparison of the sum of S19 and S17-18's ΔGunfolding values with that of the trimer, helping further reveal the energetic and structural basis of dystrophin's mechanism.

Portfolio rebalancing in times of stress

This paper investigates time variation in the dynamics of international portfolio equity flows. We extend the empirical model of Hau and Rey (2004) by embedding a Markov regime-switching model into the structural VAR. The model is estimated using monthly data from 1995 to 2018, on equity returns, exchange rate returns, and equity flows between the United States and advanced and emerging market economies. We find that the data favor a two-state model where coefficients and shock volatilities switch jointly. In the VAR for flows between the United States and emerging market economies, the estimated states match periods of low and high financial stress, both in terms of the timing of regime switching and in terms of their volatility characteristics. Our main result is that for equity flows between the United States and emerging markets rebalancing dynamics differ between episodes of high and low levels of financial stress. A switch from the low- to the high-stress regime is associated with capital outflows from emerging markets. Once in the high-stress regime, the response of capital flows to exchange rates and stock prices is smaller than in normal (low-stress) periods.

Mechanism model-based and data-driven approach for the diagnosis of solid oxide fuel cell stack leakage

Safety and reliability are key objectives for the efficient operation of solid oxide fuel cell (SOFC) power generation systems. Out of many possible faults, the gas leakage of SOFC stack remains a critical issue that leading to efficiency reduction or even degradation. Therefore, the real-time monitoring and diagnosis of gas leakage in the power generation systems are not only an important premise to improve the efficiency, but also can develop the corresponding fault-tolerant strategy for ensuring the system performance. Motivated by this fact, an on-line fault diagnosis scheme based on mechanism model and data-driven method is proposed to monitor and diagnose the gas leakage of the stack. Firstly, the two-state mechanism model of the SOFC stack is established, which can effectively describe the temperature of the fuel layer and air layer. Then, easily-measured stack inputs and outputs are selected, and a novel gas leakage state estimator combined with unscented Kalman filter (UFK) is developed to reconstruct the leakage state. Furthermore, an adaptive thresholds generator is designed to enhance the robustness of the diagnostic scheme. The performance of the fault diagnosis scheme under different leakage scenarios is evaluated, and the simulation results demonstrate the effectiveness of the proposed scheme. The sudden stack fuel leakage failure that occurred in the stable power generation experiment further illustrates the practicability of the scheme. The proposed fault diagnosis scheme has good practicability and can guide the next step compensates for leakage.

The third generation Calphad description of Al–C including revisions of pure Al and C

New descriptions of pure Al and liquid C were developed and used to describe the Al–C system for the third generation of Calphad databases. The stable phases of the elements are described with a single expression for the entire temperature range. The expression is based on the Einstein model and an important parameter is therefore the Einstein temperature. For the metastable phases, the difference in entropy between stable and metastable phases is used to calculate the Einstein temperature for the metastable allotrope. In this way we avoid breaking the third law of thermodynamics, which would be the consequence if the SGTE lattice stabilities were used. The liquid-amorphous phase for the pure substances and for the binary is described with the two-state model. For the pure substances, we introduce a zero-point entropy that is related to the entropy of melting. The heat capacity of the liquid of the pure substances approaches 3R at high temperatures if the electronic contribution is subtracted. The Al–C system has one stable carbide, Al4C3, which is described with a model equivalent to that used for the solid unary phases but with two Einstein functions. In Al–C, the FCC phase is stable and its metastable end-member, Al1C1, is described with a new model, here called the hybrid model, as it combines the Einstein model (giving the harmonic contribution) and the Neumann–Kopp relationship (adding the additional contributions) to describe the heat capacity. Its Einstein temperature is estimated and its formation energy is obtained from DFT calculations. The total energy of the end-members of the metastable phases BCC(Al1C3) and HCP(Al1C0.5) is calculated with DFT and their Einstein temperatures are estimated using the mass-effect model. The Al–C system was chosen because it is a simple system without magnetism and the results show that the proposed models can reproduce experimental information well. When only one temperature range is used to describe the solid phases, they may be re-stabilized at high temperatures and the recently presented equal-entropy criterion (EEC) is used to exclude solid phases with higher entropy than the liquid.

Light Driven Mechanism of Carbon Dioxide Reduction Reaction to Carbon Monoxide on Gold Nanoparticles: A Theoretical Prediction.

Insightful understanding of the light driven CO2 reduction reaction (CO2RR) mechanism on gold nanoparticles is one of the important issues in the plasmon mediated photocatalytic study. Herein, time-dependent density functional theory and reduced two-state model are adopted to investigate the photoinduced charge transfer in interfaces. According to the excitation energy and orbital coupling, the light driven mechanism of CO2RR on gold nanoparticles can be described as follows: the light induces electron excitation and then transfers to the physisorbed CO2, and CO2 can relax to a bent structure adsorbed on gold nanoparticles, and the adsorbed C-O bonds are dissociated finally. Moreover, our calculated results demonstrate that the s, p, and d electron excitations of gold nanoparticles are the major contribution for the CO2 adsorption and the C-O dissociation process, respectively. This work would promote the understanding of the light driven electron transfer and photocatalytic CO2RR on the noble metal.

Static and regime-dependent herding behavior: An emerging market case study

We contribute to behavioral finance literature by demonstrating the relative superiority of a dynamic regime-sensitive approach in unraveling herding phenomenon. Employing daily data in Bursa Malaysia from 1995 to 2016, we first apply two orthodox techniques: cross-sectional standard deviation of returns (CSSD) model of Christie and Huang (2005) and the cross-sectional absolute dispersion (CSAD) model of Chang et al. (2000). The ensuing results appear inconsistent, with only one model capturing herding. In contrast, the dynamic approach with a two-state Markov Switching model reveals that herding is a heavily regime-dependent and non-linear phenomenon. A deeper dive via sectoral decompositions shows that the financial sector and large- and mid-capitalization segments are more herding-prone.

Structure and Dynamics of Ribonuclease A during Thermal Unfolding: The Failure of the Zimm Model.

Disordered regions as found in intrinsically disordered proteins (IDP) or during protein folding define response time to stimuli and protein folding times. Neutron spin-echo spectroscopy is a powerful tool to directly access the collective motions of the unfolded chain to enlighten the physical origin of basic conformational relaxation. During the thermal unfolding of native ribonuclease A, we examine the structure and dynamics of the disordered state within a two-state transition model using polymer models, including internal friction, to describe the chain dynamics. The presence of four disulfide bonds alters the disordered configuration to a more compact configuration compared to a Gaussian chain that is defined by the additional links, as demonstrated by coarse-grained simulation. The dynamics of the disordered chain is described by Zimm dynamics with internal friction (ZIF) between neighboring amino acids. Relaxation times are dominated by mode-independent internal friction. Internal friction relaxation times show an Arrhenius-like behavior with an activation energy of 33 kJ/mol. The Zimm dynamics is dominated by internal friction and suggest that the characteristic motions correspond to overdamped elastic modes similar to the motions observed for folded proteins but within a pool of disordered configurations spanning the configurational space. For IDP, internal friction dominates while solvent friction and hydrodynamic interactions are smaller corrections.

Reconciling kinetic and thermodynamic models of bacterial transcription.

The study of transcription remains one of the centerpieces of modern biology with implications in settings from development to metabolism to evolution to disease. Precision measurements using a host of different techniques including fluorescence and sequencing readouts have raised the bar for what it means to quantitatively understand transcriptional regulation. In particular our understanding of the simplest genetic circuit is sufficiently refined both experimentally and theoretically that it has become possible to carefully discriminate between different conceptual pictures of how this regulatory system works. This regulatory motif, originally posited by Jacob and Monod in the 1960s, consists of a single transcriptional repressor binding to a promoter site and inhibiting transcription. In this paper, we show how seven distinct models of this so-called simple-repression motif, based both on thermodynamic and kinetic thinking, can be used to derive the predicted levels of gene expression and shed light on the often surprising past success of the thermodynamic models. These different models are then invoked to confront a variety of different data on mean, variance and full gene expression distributions, illustrating the extent to which such models can and cannot be distinguished, and suggesting a two-state model with a distribution of burst sizes as the most potent of the seven for describing the simple-repression motif.

The Benefits of Receiver Clock Modelling in Satellite Timing

Satellite timing is an effective and convenient method that has been widely accepted in the time community. The key to satellite timing is obtaining a clean receiver clock offset. In this paper, instead of regarding the receiver clock offset as white noise, a two-state stochastic clock model involving three kinds of noise was conceived and used in PPP filter estimation. The influence of clock type and sampling time on satellite timing performance was first analysed. In addition, the kinematic scheme and static scheme were both investigated for meeting the demands of multi-occasional users. The values show that the model works well for both the kinematic scheme and static scheme; in contrast to that of the white noise model, the timing stability is enhanced at all the sampling times. For the six stations, especially when the averaging time is less than 1000 s, the average stability improvement values of the kinematic scheme are 75.53, 43.24, 75.00, 69.05, 40.57, and 25.45%, and the average improvement values of the static scheme are 65.49, 77.94, 56.71, 60.78, 64.41, and 39.41%. Furthermore, the enhancement magnitude is related to clock type. For a high-stability clock, the improvement of the kinematic scheme is greater than that of the static scheme, whereas for a low-stability clock, the improvement of the kinematic scheme is less than that of the static scheme.

Estimation of semi-Markov multi-state models: a comparison of the sojourn times and transition intensities approaches.

Semi-Markov models are widely used for survival analysis and reliability analysis. In general, there are two competing parameterizations and each entails its own interpretation and inference properties. On the one hand, a semi-Markov process can be defined based on the distribution of sojourn times, often via hazard rates, together with transition probabilities of an embedded Markov chain. On the other hand, intensity transition functions may be used, often referred to as the hazard rates of the semi-Markov process. We summarize and contrast these two parameterizations both from a probabilistic and an inference perspective, and we highlight relationships between the two approaches. In general, the intensity transition based approach allows the likelihood to be split into likelihoods of two-state models having fewer parameters, allowing efficient computation and usage of many survival analysis tools. Nevertheless, in certain cases the sojourn time based approach is natural and has been exploited extensively in applications. In contrasting the two approaches and contemporary relevant R packages used for inference, we use two real datasets highlighting the probabilistic and inference properties of each approach. This analysis is accompanied by an Rvignette.

Research on evaluation method of energy supply reliability of regional energy Internet

This paper studies the reliability evaluation technology of regional energy Internet and represents a reliability evaluation method considering the optimal load reduction strategy. The application scenario of regional Energy Internet with power system as the core is built. The specific form is that multiple Integrated Energy systems are connected to the superior distribution network through the tie line. The reliability evaluation index system of power system and regional energy Internet is introduced. Based on the modelling of components in the regional energy Internet application scenario in this paper, the operation model and two-state Markov model are mainly established for the renewable energy power generation devices, energy coupling devices and energy storage devices in IES. The optimal load reduction models based on load classification are established for the faults of distribution network lines and the faults of IES internal components connected to the distribution network in regional energy Internet respectively. Through the construction of different application scenarios, the load reduction situation under different faults and different component parameters is analysed, and the corresponding reliability index calculation and result analysis are carried out.