Maximum approximate likelihood estimation of general continuous-time state-space models

Continuous-time state-space models (SSMs) are flexible tools for analysing irregularly sampled sequential observations that are driven by an underlying state process. Corresponding applications typically involve restrictive assumptions concerning linearity and Gaussianity to facilitate inference on the model parameters via the Kalman filter. In this contribution, we provide a general continuous-time SSM framework, allowing both the observation and the state process to be non-linear and non-Gaussian. Statistical inference is carried out by maximum approximate likelihood estimation, where multiple numerical integration within the likelihood evaluation is performed via a fine discretization of the state process. The corresponding reframing of the SSM as a continuous-time hidden Markov model, with structured state transitions, enables us to apply the associated efficient algorithms for parameter estimation and state decoding. We illustrate the modelling approach in a case study using data from a longitudinal study on delinquent behaviour of adolescents in Germany, revealing temporal persistence in the deviation of an individual's delinquency level from the population mean.

Electroencephalographic Evidence for Individual Neural Inertia in Mice That Decreases With Time

Previous studies have demonstrated that the brain has an intrinsic resistance to changes in arousal state. This resistance is most easily measured at the population level in the setting of general anesthesia and has been termed neural inertia. To date, no study has attempted to determine neural inertia in individuals. We hypothesize that individuals with markedly increased or decreased neural inertia might be at increased risk for complications related to state transitions, from awareness under anesthesia, to delayed emergence or confusion/impairment after emergence. Hence, an improved theoretical and practical understanding of neural inertia may have the potential to identify individuals at increased risk for these complications. This study was designed to explicitly measure neural inertia in individuals and empirically test the stochastic model of neural inertia using spectral analysis of the murine EEG. EEG was measured after induction of and emergence from isoflurane administered near the EC50 dose for loss of righting in genetically inbred mice on a timescale that minimizes pharmacokinetic confounds. Neural inertia was assessed by employing classifiers constructed using linear discriminant or supervised machine learning methods to determine if features of EEG spectra reliably demonstrate path dependence at steady-state anesthesia. We also report the existence of neural inertia at the individual level, as well as the population level, and that neural inertia decreases over time, providing direct empirical evidence supporting the predictions of the stochastic model of neural inertia.

The Detection, Genesis, and Modeling of Turbulence Intermittency in the Stable Atmospheric Surface Layer

Intermittent transitions between turbulent and non-turbulent states are ubiquitous in the stable atmospheric surface layer (ASL). Data from two field experiments in Utqiagvik, Alaska, and from direct numerical simulations are used to probe these state transitions so as to (i) identify statistical metrics for the detection of intermittency, (ii) probe the physical origin of turbulent bursts, and (iii) quantify intermittency effects on overall fluxes and their representation in closure models. The analyses reveal three turbulence regimes, two of which correspond to weakly turbulent periods accompanied by intermittent behavior (regime 1: intermittent, regime 2: transitional), while the third is associated with a fully turbulent flow. Based on time series of the turbulence kinetic energy (TKE), two non-dimensional parameters are proposed to diagnostically categorize the ASL state into these regimes; the first characterizes the weakest turbulence state, while the second describes the range of turbulence variability. The origins of intermittent turbulence activity are then investigated based on the TKE budget over the identified bursts. While the quantitative results depend on the height, the analyses indicate that these bursts are predominantly advected by the mean flow, produced locally by mechanical shear, or lofted from lower levels by turbulent ejections. Finally, a new flux model is proposed using the vertical velocity variance in combination with different mixing length scales. The model provides improved representation (correlation coefficients with observations of 0.61 for momentum and 0.94 for sensible heat) compared to Monin–Obukhov similarity (correlation coefficients of 0.0047 for momentum and 0.49 for sensible heat), thus opening new pathways for improved parametrizations in coarse atmospheric models.

Interfacial Confinement in Semi-Crystalline Shape Memory Polymer Towards Sequentially Dynamic Relaxations

Sequential glass and melting transitions in semi-crystalline shape memory polymers (SMPs) provide great opportunities to design and generate multiple shape-memory effects (SMEs) for practical applications. However, the complexly dynamic confinements of coexisting amorphous and crystalline phases within the semi-crystalline SMPs are yet fully understood. In this study, an interfacial confinement model is formulated to describe dynamic relaxation and shape memory behavior in the semi-crystalline SMPs undergoing sequential phase/state transitions. A confinement entropy model is first established to describe the glass transition behavior of amorphous phase within the SMPs based on the free volume theory, where the free volume is critically confined by the crystalline phase. An extended Avrami model is then formulated using the frozen volume theory to characterize the melting and crystallization transitions of the crystalline phase in the SMPs, whose interfacial confinement with the amorphous phase has been identified as the driving force for the supercooled regime. Furthermore, an extended Maxwell model is formulated to describe the effect of dynamic confinement of two phases on the multiple SMEs and shape recovery behaviors in the semi-crystalline SMPs. Finally, the effectiveness of the newly proposed model is verified using the experimental data reported in the literature. This study aims to provide a new methodology for the dynamic confinements and cooperative principles in the semi-crystalline SMP towards multiple SMEs.

Probing dissolved CO2(aq) in aqueous solutions for CO2 electro-reduction and storage

CO2 dissolved in aqueous solutions is of wide ranging importance from CO2 capture, storage and photo-/electro-reduction in the fight against global warming, to CO2 analysis in various liquids including natural waterbodies and consumer drinking products. Here we developed micro-scale infrared (IR) spectroscopy for in-situ dynamic monitoring and quantitating CO2(aq) in aqueous solutions with high time resolutions under various conditions including CO2 gas bubbling and high pressures. The quantized CO2(g) rotational state transitions were observed to quench when dissolved in water to form CO2(aq) solvated by water molecules, accompanied by increased H2O IR absorption. An accurate CO2 molar extinction coefficient ε was derived for in-situ CO2(aq) quantification up to 58 atm. For the first time, we directly measured CO2(aq) concentrations in electrolytes under CO2(g) bubbling and high pressure conditions. In KHCO3 electrolytes with CO2(aq) > ~ 1 M, CO2 electroreduction (CO2RR) to formate reaches > 98% Faradaic efficiencies on copper (Cu2O/Cu) based electrocatalyst. Further, we probed CO2 dissolution/desolvation kinetics important to energy and environmental applications dynamically, revealing large hysteresis and ultra-slow reversal of CO2(aq) supersaturation in water, with implications to CO2 capture, storage and supersaturation phenomena in natural water bodies.

Anomalous Josephson current through a topological noncoplanar ferromagnetic trilayer

We present an anomalous Josephson effect in a TI-based Josephson junction with a ferromagnetic insulator (FI) trilayer which has noncoplanar magnetizations. It is shown that there exist equal spin-singlet and -triplet correlations due to the magnetism-tuning chiral Dirac energy band structure combined with the spin precession and selective equal spin Andreev reflection by chiral Majorana modes (CMMs). The consequent anomalous Josephson supercurrent is exhibited, in which a 0-π or similar 0 - π state transition through phase shift is induced only by exchange field strengths of the first FI region, while the ϕ0 supercurrent and the maximum one gradually drop with the increase of exchange field strengths of the second and third FI regions without relative state transitions. The much different features are found by varying the lengths of trilayer. The Andreev bound states without hybridization for the CMM administrate these features, which could be used to probe and confirm the zero energy CMM. In addition, the corresponding free energies are presented and discussed.

Electron transfer via cytochrome b6f complex displays sensitivity to Antimycin A upon STT7 kinase activation.

The cytochrome b6f complex (b6f) has been initially considered as the ferredoxin-plastoquinone reductase (FQR) during cyclic electron flow (CEF) with photosystem I that is inhibited by antimycin A (AA). The binding of AA to the b6f Qi-site is aggravated by heme-ci, which challenged the FQR function of b6f during CEF. Alternative models suggest that PROTON GRADIENT REGULATION5 (PGR5) is involved in a b6f-independent, AA-sensitive FQR. Here, we show in Chlamydomonas reinhardtii that the b6f is conditionally inhibited by AA in vivo and that the inhibition did not require PGR5. Instead, activation of the STT7 kinase upon anaerobic treatment induced the AA sensitivity of b6f which was absent in stt7-1. However, a lock in State 2 due to persisting phosphorylation in the phosphatase double mutant pph1;pbcp did not increase AA sensitivity of electron transfer. The latter required a redox poise, supporting the view that state transitions and CEF are not coercively coupled. This suggests that the b6f-interacting kinase is required for structure-function modulation of the Qi-site under CEF favoring conditions. We propose that PGR5 and STT7 independently sustain AA-sensitive FQR activity of the b6f. Accordingly, PGR5-mediated electron injection into an STT7-modulated Qi-site drives a Mitchellian Q cycle in CEF conditions.

Effectiveness of Light-Quality and Dark-White Growth Light Shifts in Short-Term Light Acclimation of Photosynthesis in Arabidopsis

Photosynthesis needs to run efficiently under permanently changing illumination. To achieve this, highly dynamic acclimation processes optimize photosynthetic performance under a variety of rapidly changing light conditions. Such acclimation responses are acting by a complex interplay of reversible molecular changes in the photosynthetic antenna or photosystem assemblies which dissipate excess energy and balance uneven excitation between the two photosystems. This includes a number of non-photochemical quenching processes including state transitions and photosystem II remodeling. In the laboratory such processes are typically studied by selective illumination set-ups. Two set-ups known to be effective in a highly similar manner are (i) light quality shifts (inducing a preferential excitation of one photosystem over the other) or (ii) dark-light shifts (inducing a general off-on switch of the light harvesting machinery). Both set-ups result in similar effects on the plastoquinone redox state, but their equivalence in induction of photosynthetic acclimation responses remained still open. Here, we present a comparative study in which dark-light and light-quality shifts were applied to samples of the same growth batches of plants. Both illumination set-ups caused comparable effects on the phosphorylation of LHCII complexes and, hence, on the performance of state transitions, but generated different effects on the degree of state transitions and the formation of PSII super-complexes. The two light set-ups, thus, are not fully equivalent in their physiological effectiveness potentially leading to different conclusions in mechanistic models of photosynthetic acclimation. Studies on the regulation of photosynthetic light acclimation, therefore, requires to regard the respective illumination test set-up as a critical parameter that needs to be considered in the discussion of mechanistic and regulatory aspects in this subject.

Interplay between LHCSR proteins and state transitions governs the NPQ response in intact cells of Chlamydomonas during light fluctuations.

Photosynthetic organisms use sunlight as the primary energy source to fix CO2. However, in the environment, light energy fluctuates rapidly and often exceeds saturating levels for periods ranging from seconds to hours, which can lead to detrimental effects for cells. Safe dissipation of excess light energy occurs primarily by non-photochemical quenching (NPQ) processes. In the model green microalga Chlamydomonas reinhardtii, photoprotective NPQ is mostly mediated by pH-sensing light-harvesting complex stress-related (LHCSR) proteins and the redistribution of light-harvesting antenna proteins between the photosystems (state transition). Although each component underlying NPQ has been documented, their relative contributions to the dynamic functioning of NPQ under fluctuating light conditions remains unknown. Here, by monitoring NPQ throughout multiple high light-dark cycles with fluctuation periods ranging from 1 to 10 minutes, we show that the dynamics of NPQ depend on the frequency of light fluctuations. Mutants impaired in the accumulation of LHCSRs (npq4, lhcsr1, and npq4lhcsr1) showed significantly less quenching during illumination, demonstrating that LHCSR proteins are responsible for the majority of NPQ during repetitive exposure to high light fluctuations. Activation of NPQ was also observed during the dark phases of light fluctuations, and this was exacerbated in mutants lacking LHCSRs. By analyzing 77K chlorophyll fluorescence spectra and chlorophyll fluorescence lifetimes and yields in a mutant impaired in state transition, we show that this phenomenon arises from state transition. Finally, we quantified the contributions of LHCSRs and state transition to the overall NPQ amplitude and dynamics for all light periods tested and compared those with cell growth under various periods of fluctuating light. These results highlight the dynamic functioning of photoprotection under light fluctuations and open a new way to systematically characterize the photosynthetic response to an ever-changing light environment.

Devising matrix technology for forecasting the dynamics in the operation of a closed military logistics system

There is a tendency of intensive development of a new scientific area aimed at optimizing the processes of comprehensive ensuring the life of society and industrial processes of countries, specifically logistics, and its more important aspect, military logistics. This paper considers typical contradictions between the need and opportunities for additional development of the theory of processes involving this system. On the one hand, the military has important, dynamic, multifaceted processes for the comprehensive provision of their combat operations to analyze, which requires significant intensification of the development of methods and models for quantitative analysis of the effectiveness of the functioning of military logistics systems. On the other hand, there is now limited availability of theoretical developments and the practical application of the necessary, convenient, effective mathematical tools aimed at computerization of solving the problems of providing military scientific and technical problems in real time. Matrix technology for forecasting the dynamics of functioning of closed systems of military logistics of various military purposes is proposed. Matrix calculus makes it possible to obtain intermediate and ultimate results in a compact form and carry out complex and cumbersome calculations using effective algorithms. A method to precisely solve the system of linear differential equations describing processes of arbitrary type has been proposed. The method is based on the use of the operational calculus by Laplace. The possibilities of the method and procedures of forecasting are illustrated by solving practical military tasks that arise during the functioning of military logistics systems of varying complexity. These tasks differ in configuration, different numbers of possible states, and state transitions