Transition Function Research Articles

Hybrid Neural State-Space Modeling for Supervised and Unsupervised Electrocardiographic Imaging.

State-space modeling (SSM) provides a general framework for many image reconstruction tasks. Error in a priori physiological knowledge of the imaging physics, can bring incorrectness to solutions. Modern deep-learning approaches show great promise but lack interpretability and rely on large amounts of labeled data. In this paper, we present a novel hybrid SSM framework for electrocardiographic imaging (ECGI) to leverage the advantage of state-space formulations in data-driven learning. We first leverage the physics-based forward operator to supervise the learning. We then introduce neural modeling of the transition function and the associated Bayesian filtering strategy. We applied the hybrid SSM framework to reconstruct electrical activity on the heart surface from body-surface potentials. In unsupervised settings of both in-silico and in-vivo data without cardiac electrical activity as the ground truth to supervise the learning, we demonstrated improved ECGI performances of the hybrid SSM framework trained from a small number of ECG observations in comparison to the fixed SSM. We further demonstrated that, when in-silico simulation data becomes available, mixed supervised and unsupervised training of the hybrid SSM achieved a further 40.6% and 45.6% improvements, respectively, in comparison to traditional ECGI baselines and supervised data-driven ECGI baselines for localizing the origin of ventricular activations in real data.

A Dynamic Scheduling Method for Logistics Supply Chain Based on Adaptive Ant Colony Algorithm

To reduce the dynamic scheduling cost of logistics supply chain and improve customer satisfaction, this paper proposes a dynamic scheduling method for logistics supply chain based on adaptive ant colony algorithm. First, determine the goal of dynamic scheduling in the logistics supply chain. Second, considering supplier satisfaction, transportation costs, and maximum delivery distance constraints, a dynamic scheduling model for logistics supply chain is constructed. Then by smoothing the pheromones and designing a transition function, adjusting factors are introduced to update the pheromone rules. Finally, based on the adaptive ant colony algorithm, the solution of the dynamic scheduling function of the logistics supply chain is solved to achieve the dynamic scheduling of the current logistics supply chain. The experimental results show that after 19 iterations, the method can search for the optimal route A1 group with a length of 33.85 km, with fewer iterations and shorter paths. The total cost is 114,290 yuan, and the degree of cargo loss is low, with a maximum of only 0.14%. The task completion time is short, customer satisfaction is above 0.85, and the scheduling accuracy is 99.9%. It can effectively control costs, improve customer satisfaction, and accurately arrange logistics supply chains.

Управление процессом обслуживания высокотехнологичного оборудования с использованием сетей Петри

The paper considers the management of the maintenance process of high-tech equipment. The mechanism of operation, maintenance and repair of equipment elements and the availability of highly qualified personnel capable of performing certain types of work are described. The functioning of the Petri net reflects the process of using and maintaining high-tech equipment. The Petri net explores events that correlate certain transitions. The conditions for triggering transitions are considered, and the connections between positions and transitions are described. Each position of the selected set corresponds to the types of high-tech equipment being analyzed, the routine maintenance work performed and the teams carrying out these works. To simulate the processes of functioning of the Petri net, a transition function is formed, which allows determining new network states obtained when a transition is triggered. The rules of operation of the Petri net are described. Allowed transitions are implemented, which have non-zero values in each position at the label input. The transition is triggered not necessarily at the nearest allowed time. The change in the state of the Petri net and its labeling during the implementation of various transitions and changes in the order of their implementation is investigated. When performing any transition, the labeling of the Petri net in question changes. The labels in each position at the input of the implemented transition are reduced by one, and in each output position they increase by one, and the addition of chips at the output positions and decrease at the input positions occur simultaneously. A matrix approach is used to describe the process of functioning of a Petri net. The equipment in question can be aircraft, vehicles, machine tools, etc. As a result, the mechanism of operation, maintenance and repair of equipment elements is considered in the form of parallel processes that occur in the system under consideration independently of each other.

Parabolic Schrödinger networks

A Schrödinger network Nq={X,ζ,q} is an infinite graph with a set of vertices X and edges that are countably infinite, a transition function ζ(a,b)≥0 and a function q(a) on X. A perturbed Laplace operator Δq is defined as Δql(a)=Δl(a)−q(a)l(a). A solution h(a) to the equation Δqh(a)=0 is termed a q-average function, and a q-superaverage function v(a) satisfies Δqv(a)≤0. The network is called q-hyperbolic if there exists a function s(a)>0, q-superaverage on X; otherwise, it is a q-parabolic network, also mentioned as a parabolic Schrödinger network. In this paper, we develop a theory of function on parabolic Schrödinger networks by using potential-theoretic techniques associated with q-superaverage and q-average functions, which are similar to the function theory on parabolic Riemannian manifolds.

Mitochondrial dysfunction-associated alveolar epithelial senescence is involved in CdCl2-induced COPD-like lung injury

An earlier study found that respiratory cadmium chloride (CdCl2) exposure caused COPD-like lung injury. This study aimed to explore whether mitochondrial dysfunction-mediated alveolar epithelial senescence is involved in CdCl2-induced COPD-like lung injury. Adult C57BL/6 mice were exposed to CdCl2 (10 mg/L) aerosol for six months. Beta-galactosidase-positive cells, p21 and p16 were increased in CdCl2-exposed mouse lungs. The in vitro experiments showed that γ-H2AX was elevated in CdCl2-exposed alveolar epithelial cells. The cGAS-STING pathway was activated in CdCl2-exposed alveolar epithelial cells and mouse lungs. Cxcl1, Cxcl9, Il-10, Il-1β and Mmp2, several senescence-associated secretory phenotypes (SASP), were upregulated in CdCl2-exposed alveolar epithelial cells. Mechanistically, CdCl2 exposure caused SIRT3 reduction and mitochondrial dysfunction in mouse lungs and alveolar epithelial cells. The in vitro experiment found that Sirt3 overexpression attenuated CdCl2-induced alveolar epithelial senescence and SASP. The in vivo experiments showed that Sirt3 gene knockout exacerbated CdCl2-induced alveolar epithelial senescence, alveolar structure damage, airway inflammation and pulmonary function decline. NMN, an NAD+ precursor, attenuated CdCl2-induced alveolar epithelial senescence and SASP in mouse lungs. Moreover, NMN supplementation prevented CdCl2-induced COPD-like alveolar structure damage, epithelial-mesenchymal transition and pulmonary function decline. These results suggest that mitochondrial dysfunction-associated alveolar epithelial senescence is involved in CdCl2-induced COPD-like lung injury.

Random Vibration Analysis of Double Deck Rocking Self-Centering Pier Under Seismic Excitation

This paper investigates nonlinear random vibration of double deck rocking self-centering pier structure subjected to seismic excitation. First of all, a novel type of double deck rocking self-centering pier that offers better resilience is designed. The stochastic dynamical model of the system is then established, in which the seismic excitation is viewed as Kanai–Tajimi filtered white noise and the self-centering restoring force is characterized by classical flag-shaped hysteretic model. Subsequently, the self-centering restoring force is decomposed into equivalent quasi-linear elastic and damping forces by adopting the harmonic balance (HB) scheme. Following this, the stochastic averaging (SA) technique is implemented to derive the averaged Itô equation. The steady-state response probability density with respect to the amplitudes is solved from the averaged Fokker–Planck–Kolmogorov (FPK) equation. Finally, the effects of system parameters on the stochastic response of the double deck rocking self-centering pier structure are performed, and validated by the Monte Carlo simulation (MCS). In addition, with the help of the Laplace transform, the transition function as well as conditional power spectral density are achieved, which are combined with the steady-state probability density to obtain the power spectral density response. This research will contribute to the optimal seismic design of double-deck rocking self-centering piers.

Financial fragility, regime change, and monetary policy in an open economy – A model and empirical application to emerging market countries

July 20, 2023 (Revised April 15, 2024) The experiences of the 1997–98 Asian Financial Crisis and the 2008–09 Global Financial Crisis encouraged economists to develop new open-economy dynamic finance-macro models. Such models allow for nonlinearities -- to study the effects of contractionary currency devaluation -- in contrast to models of expansionary currency devaluation. The generic dynamic model of the finance-macro link in this paper includes the dynamics of the inflation rates, output gap, and financial variables (credit flows, risk premia, and exchange rates). The theoretical model with nonlinearities shows that there can be resilient or non-resilient outcomes of the dynamics. The level of resilience is however dependent on some empirical vulnerabilities. Relevant empirics show the risk premium is related not only to domestic real macro and financial variables, but also to the exchange rate and the foreign currency reserves. Econometrically, this paper explores the regime-dependent interaction of the output gap and financial variables in a two-regime non-linear Logistic Vector Smooth Transition Auto-Regressive (LVSTAR) model with a logistic-type transition function. This empirical study reveals that the financial variables of emerging economies show regime-dependent responses to external shocks. Therefore, a positive shock to the risk premia in a negative output gap regime entails an exchange rate depreciation, and accelerating contractions. Overall, however, a diversity of EM economies are examined in terms of their response to external shocks and their resilience levels. This research also has implications for international portfolio holdings.

Filter generators with variable transition functions over finite fields of characteristic 2

Filter generators are a traditional basis for creating synchronous stream ciphers. They are built with the help of linear shift registers (usually over a field of two elements) and nonlinear complexity functions, which are subject to a number of requirements in terms of the generators security against known attacks. Intensive researches of filter generators during the last decades show that meeting these requirements without degrading the performance of the generators is a very difficult task. Despite a large number of publications devoted to the construction of complexity functions with known “good cryptographic properties”, the usage of such functions in practice often becomes unacceptable due to the bulkiness of their constructions, which slows down the functioning of the corresponding generators, especially during software implementation. The way to overcome the noted difficulties by using an additional secret parameter that determines the appearance of the generator transitions’ function is proposed. Such a modification makes it possible to increase the security of generator (compared to traditional filter generators) against known attacks without increasing the length of its initial state. In particular, a specific version of a generator construction with a complexity function, which is determined with the help of substitutions used in the “Kalyna” encryption scheme, is considered. A lower estimate of the output sequences periods of the proposed generators was obtained. A research of their security to known attacks, in particular, Babbage-Golic balancing attack; an attack associated with a small number of terms in the polynomial representation of the complexity function (which negatively affects the value of the equivalent linear complexity of the output sequences of the generator); a natural correlation attack associated with the specifics of the proposed generator construction scheme; algebraic attacks of the Courtois-Mayer type were also conducted. At the end of the article, it is indicated how to choose the components of the proposed generators to ensure their security at a predetermined level.

Translations of Cellular Automata for Efficient Simulation

Cellular automata can be described in many different ways, one of which is to use a special purpose description language. Here, the language CDL is used as the source for translations into Java or C code for computer simulations. Several coding styles are generated automatically: The state transition function can be coded as Java, as C with stubs for integration into a Java simulation environment, as a lookup table, or as Java code consisting of boolean functions which allow the parallel simulation of 32 or 64 cells on one processor. The coding styles are compared for several examples and it is found that the boolean function style (also called multispin-coding) realized in Java is often, but not always, significantly more efficient than even native C code.

Adaptive fault-tolerant control for ascent HSV with wing damage and function constraints on states

In this article, a fault-tolerant tracking control technique is developed for the ascent of hypersonic vehicles (HSV) experiencing wing damage and time-varying state constraints. The difficulty of control problem lies in handling state constraints associated with both state and time, while determining the unknown control directions of the multi-input multi-output (MIMO) nonlinear system. The presence of constraints in both state and time complicates the design of the control algorithm. This paper proposes the construction of a novel state transition function to establish a new unconstrained system, thereby eliminating the conservative feasibility conditions of Barrier Lyapunov Function (BLF) and integral BLF methods when dealing with time-varying constraints. The fusion of time-varying scaling functions and Nussbaum-type functions not only resolves the issue of unknown control directions in the MIMO nonlinear system but also enhances the transient and steady-state performance of the closed-loop system. Neural Networks are employed to approximate the unknown nonlinear functions. Using Lyapunov stability theory, it is proven that state constraints are not violated, and all signals in the closed-loop system are bounded. Simulation results demonstrate the merits of the designed fault-tolerant control (FTC) algorithm.

Overdispersed Nonlinear Regression Models

In this paper we propose nonlinear regression models in the biparametric family of distributions. In this class of models we propose two new classes of overdispersed nonlinear regression models: the first, defined from the overdispersion family of distributionsproposed by Dey, Gelfand, and Peng (1994), and the second from a class of compound distributions. For these models, we develop a Bayesian method in which samples of the posterior distributions are obtained by applying an iterated Metropolis-Hastings algorithmobtained by assuming two groups of parameters, defined by the mean and dispersion regression structures. In the first subclass of models, to improve the performance of the iterated Metropolis-Hastings algorithm, we develop worked variables from the applicationof Fisher scoring algorithm, to build the kernel transition function. A Bayesian method to fit compound regression models is also proposed. Finally, we present an application to neonatal mortality dataset to illustrate the use of the proposed models and the perfor-mance of the Bayesian method to fit the proposed models.

DETERMINATION OF THE CLASS B FIRE EXTINGUISHING PARAMETERS USING SPRAYED WATER

Sprayed water is a versatile tool for localising and extinguishing fires of various types. When water evaporates, its volume increases by 1700 times, resulting in the dilution of combustible components with non-combustible water vapour. The study aims to determine the parameters of extinguishing class B fires using sprayed water by obtaining analytical dependencies for these parameters. The paper derives an expression for the extinguishing temperature of class B fires when extinguished with sprayed water, using Semenov’s conditions. The process of liquid combustion is considered as diffusion. The study shows that the extinguishing temperature of this type of fire is a function of the activation energy of the burning liquid and the initial temperature (at the time of sprayed water supply) of the flame. A parameter of this function is the universal gas constant. The authors constructed a graph showing the area of change in the fire extinguishing temperature. The difference between the initial flame temperature and the fire extinguishing temperature belongs to the range of (80÷120) °C. Using the transition function of class B fire, the study derives an expression for its extinguishing time, which depends on the initial flame temperature, activation energy, and the multiplicative component in the form of a fire time constant. For the relative extinguishing time, the authors constructed the area of change in this parameter depending on the activation energy and the initial temperature. It shows that the value of the extinguishing time of such a fire is (0.28÷0.32) of the value of the constant fire time. The paper presents an expression for the minimum value of the intensity of the sprayed water supply, which ensures extinguishing a class B fire. This intensity of the supply of sprayed water, reduced to the value of the fire transmission coefficient, is determined by the initial temperature of the flame and the activation energy of the liquid that burns. The authors constructed the area of change of this fire extinguishing parameter. It shows that the minimum value of the intensity of the supply of sprayed water belongs to the range (3.8÷7.8) per unit of the fire transmission coefficient. Keywords: fire, fire parameters, sprayed water.

The emotional sight of neoliberalized port infrastructure in the city of Poti, Georgia

ABSTRACT This article traces an ethnography-based analysis of the historical Poti port as it has been socially imagined through the lenses of ideological transformations. Situated at a nexus of Black Sea trading infrastructure, the city of Poti has been known as the gateway of Georgia, between Asia and Europe. The port, in its current location since the late nineteenth century, has been an economic asset to colonial powers (Russian Tsarist, Soviet state-socialist) and neoliberal economic agendas. Its infrastructure, which encompasses a specific field of trading and transit functions, encapsulates a social layer while affecting the daily lives of inhabitants. People’s reflections on either development or decay can evoke emotional perceptions of and reflections on this urban infrastructure. Living and producing infrastructure, gazing at constructed landscapes and associating oneself with particular spatial reflections all have an immersive effect on the city’s morale, evoking feelings of pride, shame and uncertainty. Thus, I aim to present in what sense the port is attached in people’s reflections to these emotional domains. I contend that specific neoliberal ideological experiences set the area of Poti port morally and socially apart from the inhabitants’ everyday reflections.

Effects and mechanisms of sciadonic acid on colonic transit function through regulating 5-HT4/cAMP/PKA/AQP4 signaling pathway in STC model mice

Torreya grandis (T. grandis) oil has been reported to alleviate symptoms of slow transit constipation (STC). However, the impact of sciadonic acid (SA), a distinctive fatty acid found in T. grandis oil, on the pathological progression of STC remains unclear. This study aimed to evaluate the effect of SA on STC and uncover the underlying mechanisms. The STC model was established by feeding Balb/c mice with loperamide. After 2 weeks of intervention, SA significantly improved weight loss and intestinal motility decline induced by STC, along with enhancing plasma indices and reducing colon pathological damage. SA effectively reversed the STC-induced decrease in the 5-HT4/cAMP/PKA/AQP4 signaling pathway genes and expression. Furthermore, 16S rRNA analysis demonstrated that SA mitigated the imbalance of the intestinal microbiota induced by STC, by reducing the ratio of Firmicutes to Bacteroidetes (F/B) and increasing the abundance of beneficial bacteria such as Akkermansia. In conclusion, SA intervention alleviated colonic dysfunction in STC mice. The activation of the SA-mediated 5-HT4/cAMP/PKA/AQP4 signaling pathway may serve as a potential target for STC treatment. These findings suggest that SA holds promise as a treatment option for STC and could potentially be extended to other related gut diseases for further investigation.

Automatically generated state observers – toolchain and validation with real measurements

State estimation of wind turbines is the basis for many advanced control strategies and analysis applications such as condition monitoring, fault diagnosis, and much more. It depends on the application and its goals, which states of the real turbine are relevant. Therefore, estimators with different levels of detail and sets of states suitable for the problem at hand are needed. This paper describes a toolchain that generates custom-tailored code for an extended Kalman filter. The aim is to create computationally highly efficient estimators for a wide range of applications. Automatic generation of source code allows for agile experimentation and reduces the risk of time-consuming implementation errors. The new contributions are the selection and combination of all parts of the toolchain, the extension of the integration algorithm to include the Jacobian of the transition function, and the adaptation of an efficient covariance auto-tuning algorithm. Four different models are validated in a three-stage process, including measurement data from a real turbine.

Testing MOND on Small Bodies in the Remote Solar System

Modified Newtonian dynamics (MOND), which postulates a breakdown of Newton's laws of gravity/dynamics below some critical acceleration threshold, can explain many otherwise puzzling observational phenomena on galactic scales. MOND competes with the hypothesis of dark matter, which successfully explains the cosmic microwave background and large-scale structure. Here we provide the first solar system test of MOND that probes the subcritical acceleration regime. Using the Bekenstein–Milgrom “aquadratic Lagrangian” (or AQUAL) formulation, we simulate the evolution of myriads of test particles (planetesimals or comets) born in the trans-Neptunian region and scattered by the giant planets over the lifetime of the Sun to heliocentric distances of 102–105 au. We include the effects of the Galactic tidal field and passing stars. While Newtonian simulations reproduce the distribution of binding energies of long-period and Oort-cloud comets detectable from Earth, MOND-based simulations do not. This conclusion is robust to plausible changes in the migration history of the planets, the migration history of the Sun, the MOND transition function, effects of the Sun's birth cluster, and the fading properties of long-period comets. For the most popular version of AQUAL, characterized by a gradual transition between the Newtonian and MOND regimes, our MOND-based simulations also fail to reproduce the orbital distribution of trans-Neptunian objects in the detached disk (perihelion q > 38 au). Our results do not rule out some MOND theories more elaborate than AQUAL, in which non-Newtonian effects are screened on small spatial scales, at small masses, or in external gravitational fields comparable in strength to the critical acceleration.

Enteric nervous system regeneration and functional cure of experimental digestive Chagas disease with trypanocidal chemotherapy

Digestive Chagas disease (DCD) is an enteric neuropathy caused by Trypanosoma cruzi infection. There is a lack of evidence on the mechanism of pathogenesis and rationales for treatment. We used a female C3H/HeN mouse model that recapitulates key clinical manifestations to study how infection dynamics shape DCD pathology and the impact of treatment with the front-line, anti-parasitic drug benznidazole. Curative treatment 6 weeks post-infection resulted in sustained recovery of gastrointestinal transit function, whereas treatment failure led to infection relapse and gradual return of DCD symptoms. Neuro/immune gene expression patterns shifted from chronic inflammation to a tissue repair profile after cure, accompanied by increased cellular proliferation, glial cell marker expression and recovery of neuronal density in the myenteric plexus. Delaying treatment until 24 weeks post-infection led to partial reversal of DCD, suggesting the accumulation of permanent tissue damage over the course of chronic infection. Our study shows that murine DCD pathogenesis is sustained by chronic T. cruzi infection and is not an inevitable consequence of acute stage denervation. The risk of irreversible enteric neuromuscular tissue damage and dysfunction developing highlights the importance of prompt diagnosis and treatment. These findings support the concept of treating asymptomatic, T. cruzi-infected individuals with benznidazole to prevent DCD development.

Evolutionary Probabilistic Analysis of Non-Smoothly Damped Stochastic Oscillator Under Modulated Random and Harmonic Excitations

This paper concerns the evolutionary transitional probability density functions (PDFs) and the mean upcrossing rates (MCRs) of responses of the non-smoothly damped stochastic oscillator under both modulated random and harmonic excitations. The damping expressed by a non-smooth function of velocity is considered in the stochastic dynamical systems. A procedure is presented by making the time-related weighted residue of the formulated Fokker–Planck–Kolmogorov (FPK) equation vanish in the weak sense. Thus, a group of stochastic ordinary differential equations regarding the undetermined parameters in the assumed solution can be formulated and solved numerically. Three cases are studied under different conditions. The achieved evolutionary transitional PDF and MCR solutions attest to the outstanding effectiveness of the presented procedure even in the tail ends of the PDF solutions. Moreover, the achieved solutions of the stochastic dynamical systems are found to have significant non-Gaussian behaviors due to the interaction of the random and harmonic excitations and the system nonlinearity. Notably, the presented procedure greatly improves the running efficiency when compared with Monte Carlo simulation.

Model-Free Nonstationary Reinforcement Learning: Near-Optimal Regret and Applications in Multiagent Reinforcement Learning and Inventory Control

We consider model-free reinforcement learning (RL) in nonstationary Markov decision processes. Both the reward functions and the state transition functions are allowed to vary arbitrarily over time as long as their cumulative variations do not exceed certain variation budgets. We propose Restarted Q-Learning with Upper Confidence Bounds (RestartQ-UCB), the first model-free algorithm for nonstationary RL, and show that it outperforms existing solutions in terms of dynamic regret. Specifically, RestartQ-UCB with Freedman-type bonus terms achieves a dynamic regret bound of [Formula: see text], where S and A are the numbers of states and actions, respectively, [Formula: see text] is the variation budget, H is the number of time steps per episode, and T is the total number of time steps. We further present a parameter-free algorithm named Double-Restart Q-UCB that does not require prior knowledge of the variation budget. We show that our algorithms are nearly optimal by establishing an information-theoretical lower bound of [Formula: see text], the first lower bound in nonstationary RL. Numerical experiments validate the advantages of RestartQ-UCB in terms of both cumulative rewards and computational efficiency. We demonstrate the power of our results in examples of multiagent RL and inventory control across related products. This paper was accepted by Omar Besbes, revenue management and market analytics. Funding: The research of D. Simchi-Levi and R. Zhu was supported by the MIT Data Science Laboratory. The research of W. Mao, K. Zhang, and T. Başar was supported in part by the U.S. Army Research Laboratory (ARL) Cooperative Agreement W911NF-17-2-0196, in part by the Office of Naval Research (ONR) [MURI Grant N00014-16-1-2710], and in part by the Air Force Office of Scientific Research (AFOSR) [Grant FA9550-19-1-0353]. K. Zhang also acknowledges support from U.S. Army Research Laboratory (ARL) [Grant W911NF-24-1-0085]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.02533 .

Unraveling two yellow fluorescence emission mechanisms and color-changing afterglow characteristics of Dy-doped Mg2SnO4 luminescent materials

In this work, Dy ion doped Mg2SnO4 (Mg2SnO4:Dy3+) with monochromatic yellow fluorescence and color-changing long afterglow properties are prepared by the high-temperature solid-phase method. Mg2SnO4:Dy3+ shows the best luminescence performance under the preparation conditions of 1550 °C and 0.02 Dy3+ concentration. The samples are able to achieve yellow fluorescence emission (λem = 575 nm) under 350 nm and 291 nm excitation, and the emission intensity of the samples under 350 nm excitation is much higher than that of 291 nm excitation. Under 254 nm excitation, the sample not only emits bright white fluorescence but also has the ability of obvious afterglow after excitation. Moreover, the afterglow also has the color change function of transition from bright white to yellow. The luminescence mechanism study shows that Mg2SnO4:Dy3+ contains two emission centers, Dy3+ and lattice defects. Combining the results of spectroscopic measurements with the Dy3+ energy level distribution data, two different fluorescence emission processes under 291 and 350 nm excitation as well as the afterglow discoloration mechanism due to 254 nm excitation are discussed in detail.