Stochastic Changes Research Articles

ЕНЕРГЕТИЧНА ЕФЕКТИВНІСТЬ ВІТРОГІДРОНАСОСНОЇ СТАНЦІЇ ЗНАЧНОЇ ПОТУЖНОСТІ

Розвиток відновлюваних джерел енергії в Україні характеризується стрімкими темпами. Станом на вересень 2020 року встановлена потужність вітроелектричних (ВЕС) та фотоелектричних (ФЕС) станцій складає біля 6 ГВт, що відповідає майже 20% максимального навантаження електроенергетичної системи на чинний момент часу. Тому на сьогодні набуває актуальності задача акумулювання стохастичного надходження електроенергії ВЕС та ФЕС в електроенергетичну систему, зумовлена неузгодженістю графіків генерування та споживання потужності. Ідея застосування гідроакумулювальних електростанцій (ГАЕС) для накопичення стохастичного надходження енергії ВЕС і ФЕС починає знаходити своє практичне втілення. В Іспанії вже декілька років функціонує вітродизельна електростанція для подачі води в басейн-акумулятор ГАЕС потужністю 11 МВт. Досвід експлуатації цього комплексу засвідчив суттєве зменшення його енергетичної ефективності, зумовлене стохастичним характером надходження енергії вітру. Тому на часі вирішення задачі визначення енергетичної ефективності процесу перетворення кінетичної енергії вітру в потенційну енергію води, накопиченої в басейні-акумуляторі, з урахуванням наявності пульсацій швидкості вітру . В даній роботі виконана оцінка енергетичної ефективності потужної гідронасосної станції при електроживленні двигунів насосів від вітроелектричної установки з урахуванням пульсацій швидкості вітру та кількості гідроелектричних агрегатів у складі станції. Визначення кількісних значень оцінюваних параметрів базувалось на результатах математичного моделювання динаміки навантажувальних режимів роботи вітрогідронасосної станції з урахуванням стохастичної зміни швидкості вітру. Математична модель являє собою систему нелінійних диференційних рівнянь, що описує взаємодію двох інерційних складових єдиної аероелектрогідродинамічної системи. Визначено раціональне співвідношення кількості гідронасосів в складі насосної станції для досягнення максимальних значень коефіцієнта використання встановленої потужності вітрогідронасосної станції. Бібл. 29, рис. 6.

Pricing EIA with cliquet-style guarantees under time-changed Lévy models by frame duality projection

This paper presents an efficient and accurate method for pricing equity-indexed annuities (EIAs) with cliquet-style payoff structures under time-changed Lévy processes. We apply a square-root process to depict the activity rate process in stochastic time change, which enables us to use some Fourier transform methods to price EIAs. As the complexity of payoff structures, we make use of frame duality projection associated with the quadrature rule and the spectral filtering to realize our algorithm. Numerical experiments are reported to demonstrate the accuracy and efficiency of our approach.

Analysis of queue estimation process at signalized intersections under low connected vehicle penetration rates

This study investigates the factors affecting estimation accuracy of queue length at signalized intersections under low penetration of connected vehicles. A shockwave-based algorithm is proposed to estimate the maximum queue length and residual queue on a cycle-by-cycle basis. Simulation data collected from three consecutive signalized intersections were used to extract trajectories of connected vehicles under five different market penetration rates and two different traffic conditions (under-saturated and moderate). The results confirm that the queue length estimation process is probabilistic and affected by the stochastic changes in traffic conditions. This probabilistic nature is defined by a queue formation coverage index (QI) that proved to significantly affect the queue length estimation accuracy. Overall, the results show that the accuracy of the queue estimates is acceptable when a QI value of at least 50% is achieved. In such limited data environments, the QI showed potential to help as an assessment tool to evaluate the obtained queue estimates.

Combination of transition probability distribution and stable Lorentz distribution in stock markets

It is well known that the stock price is a stochastic series of time. The probability distribution of the stock price changes should be stable. However, the empirically observed probability distribution of log-returns is not Gaussian and has power-law tails. We present a combination of Lorentz stable distribution and transition probability distribution description for the stock index changes. The Lorentz stable distribution describes the stochastic changes of stock prices and the transition distribution presents features of stock price transiting from S(t) to S(t+Δt) for small time interval. By making use of the Fokker–Planck equation, we give the explicit expression of the transition probability distribution for the stock price changes. The two stage formalism is in agreement with empirical observations on high frequency time series of the S&P 500 Index.

A near-real-time approach for monitoring forest disturbance using Landsat time series: stochastic continuous change detection

Forest disturbances greatly affect the ecological functioning of natural forests. Timely information regarding extent, timing and magnitude of forest disturbance events is crucial for effective disturbance management strategies. Yet, we still lack accurate, near-real-time and high-performance remote sensing tools for monitoring abrupt and subtle forest disturbances. This study presents a new approach called ‘Stochastic Continuous Change Detection (S-CCD)’ using a dense Landsat data time series. S-CCD improves upon the ‘COntinuous monitoring of Land Disturbance (COLD)’ approach by incorporating a mathematical tool called the ‘state space model’, which treats trends and seasonality as stochastic processes, allowing for modeling temporal dynamics of satellite observations in a recursive way. The quantitative accuracy assessment is evaluated based on 3782 Landsat-based disturbance reference plots (30 m) from a probability sampling distributed throughout the Conterminous United States. Validation results show that the overall accuracy (best F1 score) of S-CCD is 0.793 with 20% omission error and 21% commission error, slightly higher than that of COLD (0.789). Two disturbance sites respectively associated with wildfire and insect disturbances are used for qualitative map-based analysis. Both quantitative and qualitative analyses suggest that S-CCD achieves fewer omission errors than COLD for detecting those disturbances with subtle/gradual spectral change. In addition, S-CCD facilitates a better real-time monitoring, benefited by its complete recursive manner and a shorter lag for confirming disturbance than COLD (126 days vs. 166 days for alerting 50% disturbance events), and reached up to ~4.4 times speedup for computation. This research addresses the need for near-real-time monitoring and large-scale mapping of forest health and offers a new approach for operationally performing change detection tasks from dense Landsat-based time series.

Robust Discovery of Candidate DNA Methylation Cancer Drivers

Robust Discovery of Candidate DNA Methylation Cancer Drivers

Population extinction on a random fitness seascape.

We explore the role of stochasticity and noise in the statistical outcomes of commonly studied population dynamics models within a space-independent (mean-field) perspective. Specifically, we consider a distributed population with logistic growth at each location, subject to "seascape" noise, wherein the population's fitness randomly varies with location and time. Despite its simplicity, the model actually incorporates variants of directed percolation, and directed polymers in random media, within a mean-field perspective. Probability distributions of the population can be computed self-consistently, and the extinction transition is shown to exhibit novel critical behavior with exponents dependent on the ratio of the strengths of migration and noise amplitudes. The results are compared and contrasted with the more conventional choice of demographic noise due to stochastic changes in reproduction.

A "Switch" in Time through Genes Aligned: Unraveling the Genomic Landscape of HSC Development.

Seeking to define the "switch" from fetal to adult hematopoiesis, Li etal. (2020) performed extensive genomic and epigenomic profiling of hematopoietic stem and progenitor cells across ontogeny (as explored in this issue of Cell Stem Cell). Gradual and stochastic changes in genomic and epigenomic regulation suggest the absence of any specific regulator.

Angiogenesis and vessel co-option in a mathematical model of diffusive tumor growth: The role of chemotaxis

This work considers the propagation of a tumor from the stage of a small avascular sphere in a host tissue and the progressive onset of a tumor neovasculature stimulated by a pro-angiogenic factor secreted by hypoxic cells. The way new vessels are formed involves cell sprouting from pre-existing vessels and following a trail via a chemotactic mechanism (CM). Namely, it is first proposed a detailed general family of models of the CM, based on a statistical mechanics approach. The key hypothesis is that the CM is composed by two components: i) the well–known bias induced by the angiogenic factor gradient; ii) the presence of stochastic changes of the velocity direction, thus giving rise to a diffusive component. Then, some further assumptions and simplifications are applied in order to derive a specific model to be used in the simulations. The tumor progression is favored by its acidic aggression towards the healthy cells. The model includes the evolution of many biological and chemical species. Numerical simulations show the onset of a traveling wave eventually replacing the host tissue with a fully vascularized tumor. The results of simulations agree with experimental measures of the vasculature density in tumors, even in the case of particularly hypoxic tumors.

Models of Organization and Management of Passenger Public Urban Transport Systems

The paper gives an overview of the model of organization in the management of public urban passenger transport systems (JGTP), which are applied in world cities as well as in some cities in the region. These are complex systems with components of economic, technical, technological and organizational nature, as well as elements of planning, arrangement and organization of space and impact on the environment and its protection, at the same time, as a public service, it is a specific network of various organizational and spatial entities. Systems are open transport systems with stochastic state change.

Avian Reproduction in a Warming World

Weather influences both the distribution and life-history strategies of birds. Temperature ranks amongst the more important weather parameters in this regard since warming springs in temperate and high latitudes and more frequent heat-waves globally have caused major changes in breeding phenology and negatively affected adult and juvenile survival, respectively. Both long-term and stochastic changes in temperature can have fundamental consequences for avian reproduction even when the effects are not lethal, such as via thermal constraints on parental provisioning and chick growth. To date, most of what we know about temperature effects on nestling development and parental effort during reproduction is based on correlative data. In addition, an increasing amount of evidence indicates that temperature change also significantly affects birds that breed in cooler temperate areas, which so far has been somewhat overlooked. Therefore, in this perspective piece, we outline the existing literature on temperature effects on nestling development and parental behavior, with an emphasis on what needs to be done to address the causal effects of temperature change on avian reproduction under climate change. We finish by providing an outlook over future avenues of research, and give suggestions of some specific areas that might be especially promising in developing this field of research. (Less)

AlphaBeta: computational inference of epimutation rates and spectra from high-throughput DNA methylation data in plants

Stochastic changes in DNA methylation (i.e., spontaneous epimutations) contribute to methylome diversity in plants. Here, we describe AlphaBeta, a computational method for estimating the precise rate of such stochastic events using pedigree-based DNA methylation data as input. We demonstrate how AlphaBeta can be employed to study transgenerationally heritable epimutations in clonal or sexually derived mutation accumulation lines, as well as somatic epimutations in long-lived perennials. Application of our method to published and new data reveals that spontaneous epimutations accumulate neutrally at the genome-wide scale, originate mainly during somatic development and that they can be used as a molecular clock for age-dating trees.

H ∞ consensus of multi-agent systems with semi-Markovian switching topologies and mode-dependent delays

This paper addresses leader-following consensus of multi-agent systems with semi-Markovian switching topologies and time-varying delays. Unlike the classic Markovian switching topologies, the transition rates are time-varying in the semi-Markovian switching topologies, which can better model the switching of topologies due to inevitable stochastic changes. Moreover, compared with existing works on multi-agent systems with switching topologies and time delays, the delays in the paper are dependent on the switching modes. By designing the distributed mode-dependent consensus protocol and constructing Lyapunov functional, sufficient conditions in terms of LMIs are derived to ensure that leader-following consensus is asymptotically achieved in the mean square. Finally, a numerical example is provided to show the effectiveness of the main results.

Grapho-analytical studies of deformation in deformed thin-walled contours

Increasing the levels of operational reliability of technical means of modern production involves, in particular, the optimization of the deformation parameters of individual components of these tools. The main deformation-operational feature of such structures as elastic shells of the pneumatic periphery of mobile vehicles, and individual links of long-link cargo chains is a stochastic change of their shape in contact with the deformed environment. The basis for the optimization of the operational reliability of deformed thin-walled circuits of such structures under power load is to determine the ratios of their geometric parameters, in which the process of deformation under load does not transform their initial shape from “folded” (out-of-bounds) state to “foldless” state toroidal surfaces, which should be described using the Cassini family of ovals. Based on the established regularities of changing the configuration of the meridian of soft elastic shell and flat closed structures, which are deformed by external loads, three main conditions of using model typical contours of Cassini ovals as graph-analytical models of elastic shells of pneumatic mobile periphery chains. These conditions of graph-analytical modelling include: closedness and continuity of the curvature of the toroidal surface; generalization of the initial shape of the surfaces of toroidal contours; reduction of variable geometric shapes of contours to a single generalized equation. The results of the given grapho-analytical researches allow to define design structural and geometrical parameters of tires of engines of mobile means and separate links of cargo chains with the increased operational indicators of reliability of their work.

An Interaction-Free Quantum Measurement-Driven Engine

Recently highly-efficient quantum engines were devised by exploiting the stochastic energy changes induced by quantum measurement. Here we show that such an engine can be based on an interaction-free measurement, in which the meter seemingly does not interact with the measured object. We use a modified version of the Elitzur-Vaidman bomb tester, an interferometric setup able to detect the presence of a bomb triggered by a single photon without exploding it. In our case, a quantum bomb subject to a gravitational force is initially in a superposition of being inside and outside one of the interferometer arms. We show that the bomb can be lifted without blowing up. This occurs when a photon traversing the interferometer is detected at a port that is always dark when the bomb is located outside the arm. The required potential energy is provided by the photon (which plays the role of the meter) even though it was not absorbed by the bomb. A natural interpretation is that the photon traveled through the arm which does not contain the bomb -- otherwise the bomb would have exploded -- but it implies the surprising conclusion that the energy exchange occurred at a distance despite a local interaction Hamiltonian. We use the weak value formalism to support this interpretation and find evidence of contextuality. Regardless of interpretation, this interaction-free quantum measurement engine is able to lift the most sensitive bomb without setting it off.

Mutual relevance of investor sentiment and finance by modeling coupled stochastic systems with MARS

Stochastic differential equations (SDEs) rapidly become one of the most well-known formats in which to express such diverse mathematical models under uncertainty such as financial models, neural systems, behavioral and neural responses, human reactions and behaviors. They belong to the main methods to describe randomness of a dynamical model today. In a financial system, different kinds of SDEs have been elaborated to model various financial assets. On the other hand, economists have conducted research on several empirical phenomena regarding the behaviour of individual investors, such as how their emotions and opinions influence their decisions. All those emotions and opinions are described by the word Sentiment. In finance, stochastic changes might occur according to investors’ sentiment levels. In our study, we aim to represent the mutual effects between some financial process and investors’ sentiment with constructing a coupled system of non-autonomous SDEs, evolving in time. These equations are hard to assess and solve. Therefore, we express them in a simplified manner by discretization and Multivariate Adaptive Regression Splines (MARS) model. MARS is a strong method for flexible regression and classification with interactive variables. Hereby, we treat time as another spatial variable. Eventually, we present a modern application with real-world data. This study finishes with a conclusion and an outlook towards future studies.

Maximum Power Point Tracking of Variable-Speed Wind Turbines Using Self-Tuning Fuzzy PID

This paper designs a new controller to increase efficiency of maximum power point tracking (MPPT) at nominal wind speed based on adaptive PID controller where its coefficients are optimized using a fuzzy controller. PID controllers are widely used in linear systems due to their simple structure and proper response. Due to stochastic changes of wind speed, wind turbines generally have nonlinear nature. In addition, turbines have different dynamic structures regarding their construction conditions. Thus, using a controller which can preserve system stability considering changes of system parameters and obtain reach steady state in the shortest possible time is necessary. In this method, information adopted from wind speed and nonlinear turbine model are used to identify system using closed loop identification. In the following, Hill climbing search (HCS) algorithm is used to determine optimal operating point of the turbine in the nominal wind speed range, online. Advantage of perturb and observe (P&O) methods includes simple structure and adaptability with different stochastic and nonlinear systems. The designed controller minimizes the error between output power of the turbine and the optimized power. This controller is simulated practically on a 3KW wind turbine. Simulation results indicate efficiency and robustness of the designed controller.

Regional Infoveillance of COVID-19 Case Rates: Analysis of Search-Engine Query Patterns.

BackgroundTimely allocation of medical resources for coronavirus disease (COVID-19) requires early detection of regional outbreaks. Internet browsing data may predict case outbreaks in local populations that are yet to be confirmed.ObjectiveWe investigated whether search-engine query patterns can help to predict COVID-19 case rates at the state and metropolitan area levels in the United States.MethodsWe used regional confirmed case data from the New York Times and Google Trends results from 50 states and 166 county-based designated market areas (DMA). We identified search terms whose activity precedes and correlates with confirmed case rates at the national level. We used univariate regression to construct a composite explanatory variable based on best-fitting search queries offset by temporal lags. We measured the raw and z-transformed Pearson correlation and root-mean-square error (RMSE) of the explanatory variable with out-of-sample case rate data at the state and DMA levels.ResultsPredictions were highly correlated with confirmed case rates at the state (mean r=0.69, 95% CI 0.51-0.81; median RMSE 1.27, IQR 1.48) and DMA levels (mean r=0.51, 95% CI 0.39-0.61; median RMSE 4.38, IQR 1.80), using search data available up to 10 days prior to confirmed case rates. They fit case-rate activity in 49 of 50 states and in 103 of 166 DMA at a significance level of .05.ConclusionsIdentifiable patterns in search query activity may help to predict emerging regional outbreaks of COVID-19, although they remain vulnerable to stochastic changes in search intensity.

CGGBP1-regulated cytosine methylation at CTCF-binding motifs resists stochasticity

BackgroundThe human CGGBP1 binds to GC-rich regions and interspersed repeats, maintains homeostasis of stochastic cytosine methylation and determines DNA-binding of CTCF. Interdependence between regulation of cytosine methylation and CTCF occupancy by CGGBP1 remains unknown.ResultsBy analyzing methylated DNA-sequencing data obtained from CGGBP1-depleted cells, we report that some transcription factor-binding sites, including CTCF, resist stochastic changes in cytosine methylation. By analysing CTCF-binding sites we show that cytosine methylation changes at CTCF motifs caused by CGGBP1 depletion resist stochastic changes. These CTCF-binding sites are positioned at locations where the spread of cytosine methylation in cis depends on the levels of CGGBP1.ConclusionOur findings suggest that CTCF occupancy and functions are determined by CGGBP1-regulated cytosine methylation patterns.

Metoda szacowania trwałości lotniczych napędów hydraulicznych

Throughout previous practice, estimating the life of aviation hydraulic drive assemblies has been utilizing a variant, which requires conducting long-lasting studies of the drive assemblies until they move to the unfitness state. Such studies, which enable estimating life a posteriori, are costly and long-lasting. Hence the need to look for new strategies for estimating life. The article presents a method of estimating the durability of a hydraulic drive assembly based on the control of its change in technical condition. Inspection of the technical condition enables timely detection of the condition before the emergency hydraulic assembly. The novelty of the method is to use, to detect the condition before the emergency team, the principle of determining the pre-emptive control parameter tolerance. Pre-emptive tolerances are a set of control parameter values between threshold levels and pre-emergency (allowable) levels. The intensity of depletion of durability (intensity of aging, wear) is random. The paper presents a stochastic description of the control parameter change and the resulting empirical relationships between the control parameter verification time probability density (verification periodicity) and the control parameter value change probability density. The inter-relations between these two functions were described. It also presents empirical relationships enabling the determination of the permissible value for the control parameters and the periodicity of the control parameter checks after exceeding the limit value. An example of estimating the life of a hydraulic piston pump on-board an aircraft operated in the Polish Air Forces was shown. The permissible values and the time for the first control parameter verification after exceeding the limit value were determined for selected control parameters of the hydraulic pump. The proposed method binds life (fitness time) with the physical wear mechanisms concerning the assemblies. It can be applied in work aimed at determining the resource life of technical equipment. Furthermore, it enables utilizing technical equipment according to a technical state strategy with monitoring the parameters.