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This paper is a description of the evolution of long-term research work on two-phase flows using parallel studies of dynamic image analysis and stochastic processes analysis. The state of current knowledge on the research of gas-solid and gas-liquid systems as well as a review of research relating to these issues are also presented. The work grants the principles of videogrammetric surveys based on stochastic analysis for a series of photographs taken with video techniques. The method applies the analysis of changes in selected features and parameters in the time domain. Especially in application to multiphase gas-liquid and solid-gas mixture flows, which are characterized by strong variabilities. Parameters such as flow patterns of the mixture were determined as time-space distributions of phase concentration, displacement velocities of separated two-phase structures, volume partitions of phases, and velocity field distributions are evaluated. The changes of certain parameters characterizing the flow in the time domain often hide more useful information. The subject of this study covers the basics of videogrammetry with a description of two-phase mixture motion for co-current flow in channels, mapping of the phase velocity field, also across the tube bundle in shell-and-tube apparatus, phase motion at the flow of a two-phase gas-liquid mixture in mini-channels, transport of liquids in air-lift pump and fluidization of solid particles. [ABSTRACT FROM AUTHOR]

Introduction: Accurately predicting the remaining mechanical equipment is of great significance for ensuring the safe operation of the equipment and improving economic efficiency. Methods: To accurately assess the mechanical equipment degradation, predict its remaining useful life, and ensure efficient, stable, and safe operation, a degradation and life prediction model for mechanical equipment based on multivariate stochastic processes is studied. The study innovatively predicts the remaining life of mechanical equipment using multivariate stochastic processes, and facilitates the correlation analysis between performance indicators based on the characteristics of Copula functions. Results and discussion: The results showed that the Root Mean Squared Error value of the prediction results based on the trivariate Wiener process was 2.58, which decreased by 46.91% and 35.82% compared with the univariate and bivariate Wiener processes, respectively. The prediction value based on the trivariate gamma process was 3.49, which decreased by 44.95% and 40.54% compared with the univariate and bivariate gamma processes, respectively. In conclusion, the degradation and life prediction model with multivariate stochastic processes can effectively assess the mechanical equipment degradation and predict its remaining useful life. This provides an important reference for the maintenance and management of mechanical equipment, improving equipment efficiency and extend its service life. [ABSTRACT FROM AUTHOR]

Background The application of foresight to the field of public health is limited. There is growing need to anticipate uncertain future trends and to plan for them. Foresight provides tools to experts and policymakers to discuss and plan for possible futures. Hence, the aim of this study is to illustrate how the foresight six-step approach can be applied in public health, and to provide recommendations on dealing with challenges, drawn from the Population Health Information Research Infrastructure (PHIRI) foresight exercise. Methods In this tutorial, we describe the six-step approach as part of foresight methodology and give examples of possible challenges. Step 1 comprises the formulation of study objectives. Step 2 focuses on developing a conceptual model and applying the Demographic Economic Sociocultural Technological Ecological and Political-Institutional (DESTEP) framework to identify and prioritize driving forces for the topic of interest. In Step 3, a time horizon and spatial level are defined. Step 4 discusses scenario logics. Steps 5 and 6 discuss different types of scenarios and associated tools for analyses. Possible challenges encountered whilst applying the foresight methodology at each of the steps, were drawn from experiences during PHIRI foresight exercise. Results Challenges associated with applying the foresight six-step approach included: formulating concise objectives, developing a conceptual model, understanding driving forces and uncertainty and difficulties in building scenarios. Conclusions Understanding concepts used in the six-step approach and how they relate to each other remained difficult. Support from foresight experts, conducting more foresight exercises, tutorials and guidelines can enhance understanding and support building capacity. [ABSTRACT FROM AUTHOR]

Any reliable biomarker has to be specific, generalizable, and reproducible across individuals and contexts. The exact values of such a biomarker must represent similar health states in different individuals and at different times within the same individual to result in the minimum possible false-positive and false-negative rates. The application of standard cut-off points and risk scores across populations hinges upon the assumption of such generalizability. Such generalizability, in turn, hinges upon this condition that the phenomenon investigated by current statistical methods is ergodic, i.e., its statistical measures converge over individuals and time within the finite limit of observations. However, emerging evidence indicates that biological processes abound with nonergodicity, threatening this generalizability. Here, we present a solution for how to make generalizable inferences by deriving ergodic descriptions of nonergodic phenomena. For this aim, we proposed capturing the origin of ergodicity-breaking in many biological processes: cascade dynamics. To assess our hypotheses, we embraced the challenge of identifying reliable biomarkers for heart disease and stroke, which, despite being the leading cause of death worldwide and decades of research, lacks reliable biomarkers and risk stratification tools. We showed that raw R-R interval data and its common descriptors based on mean and variance are nonergodic and non-specific. On the other hand, the cascade-dynamical descriptors, the Hurst exponent encoding linear temporal correlations, and multifractal nonlinearity encoding nonlinear interactions across scales described the nonergodic heart rate variability more ergodically and were specific. This study inaugurates applying the critical concept of ergodicity in discovering and applying digital biomarkers of health and disease. [ABSTRACT FROM AUTHOR]

Dysbiosis in the gut microbiota has been intimately implicated in shrimp (Litopenaeus vannamei, Penaeidae) diseases. However, considering the variety of shrimp diseases and the variability in experimental conditions, studies addressing common features of the gut microbiota−shrimp disease relationship are limited. Through an unbiased subject‐level meta‐analysis framework, 463 shrimp gut bacterial communities from 27 studies were re‐analysed, including six lifestages and eight diseases of shrimp, with the causal agents of viral, bacterial, eukaryotic, and unknown pathogens. Shrimp lifestages and diseases were the predominant factors governing the gut microbiota. After ruling out the top lifestage‐ and disease‐specific discriminatory amplicon sequence variants (ASVs) from the gut microbiota, the top 27 disease common‐discriminatory ASVs were identified, contributing to an overall accuracy of 95.9% in diagnosing shrimp health status. By using these optimisation procedures, the accuracy of our diagnosis model was unbiased by shrimp lifestage, specific disease, sampling size, hypervariable region and sequencing platform. The shrimp eight diseases consistently and significantly increased the relative importance of stochasticity, the relative abundance of pathogenic potentials and diversified core ASVs, whereas decreased the diversity and stability of gut microbiota. Collectively, these findings illustrate the effectiveness of meta‐analysis in determining the robust and common features of the shrimp gut microbiota in response to diverse diseases. In particular, disease common‐discriminatory ASVs could accurately diagnose shrimp health status, although the data are divergent in biotic and technical variances. [ABSTRACT FROM AUTHOR]

Any reliable biomarker has to be specific, generalizable, and reproducible across individuals and contexts. The exact values of such a biomarker must represent similar health states in different individuals and at different times within the same individual to result in the minimum possible false-positive and false-negative rates. The application of standard cut-off points and risk scores across populations hinges upon the assumption of such generalizability. Such generalizability, in turn, hinges upon this condition that the phenomenon investigated by current statistical methods is ergodic, i.e., its statistical measures converge over individuals and time within the finite limit of observations. However, emerging evidence indicates that biological processes abound with nonergodicity, threatening this generalizability. Here, we present a solution for how to make generalizable inferences by deriving ergodic descriptions of nonergodic phenomena. For this aim, we proposed capturing the origin of ergodicity-breaking in many biological processes: cascade dynamics. To assess our hypotheses, we embraced the challenge of identifying reliable biomarkers for heart disease and stroke, which, despite being the leading cause of death worldwide and decades of research, lacks reliable biomarkers and risk stratification tools. We showed that raw R-R interval data and its common descriptors based on mean and variance are nonergodic and non-specific. On the other hand, the cascade-dynamical descriptors, the Hurst exponent encoding linear temporal correlations, and multifractal nonlinearity encoding nonlinear interactions across scales described the nonergodic heart rate variability more ergodically and were specific. This study inaugurates applying the critical concept of ergodicity in discovering and applying digital biomarkers of health and disease. [ABSTRACT FROM AUTHOR]

A class of infinite dimensional Ornstein-Uhlenbeck processes that arise as solutions of stochastic partial differential equations with noise generated by measure-valued catalytic processes is investigated. It will be shown that the catalytic Ornstein-Uhlenbeck process with super-Brownian catalyst in one dimension arises as a high density fluctuation limit of a super-Brownian motion in a super-Brownian catalyst with immigration. The main tools include Laplace transformations of stochastic processes, analysis of a non-linear partial differential equation and techniques on continuity and regularity based on properties of the Sobolev spaces. [ABSTRACT FROM AUTHOR]

Walking exhibits stride-to-stride variations. Given ongoing perturbations, these variations critically support continuous adaptations between the goal-directed organism and its surroundings. Here, we report that stride-to-stride variations during self-paced overground walking show cascade-like intermittency—stride intervals become uneven because stride intervals of different sizes interact and do not simply balance each other. Moreover, even when synchronizing footfalls with visual cues with variable timing of presentation, asynchrony in the timings of the cue and footfall shows cascade-like intermittency. This evidence conflicts with theories about the sensorimotor control of walking, according to which internal predictive models correct asynchrony in the timings of the cue and footfall from one stride to the next on crossing thresholds leading to the risk of falling. Hence, models of the sensorimotor control of walking must account for stride-to-stride variations beyond the constraints of threshold-dependent predictive internal models. [ABSTRACT FROM AUTHOR]

The High Energy Rapid Modular Ensemble of Satellites (HERMES) is a constellation of 3U nano-satellites for high energy astrophysics. The HERMES nano-satellites' components have been designed, verified, and tested to detect and localize energetic astrophysical transients, such as short gamma-ray bursts (GRBs), which are the electromagnetic counterparts of gravitational wave events, thanks to novel miniaturized detectors sensitive to X-rays and gamma-rays. The space segment is composed of a constellation of CubeSats in low-Earth orbit (LEO), ensuring an accurate transient localization in a field of view of several steradians exploiting the triangulation technique. To achieve this goal, guaranteeing a solid support to future multi-messenger astrophysics, HERMES shall determine its attitude and orbital states with stringent requirements. The scientific measurements bind the attitude knowledge within 1 deg ( 1 σ a ) and the orbital position knowledge within 10 m ( 1 σ o ). These performances shall be reached considering the mass, volume, power, and computation constraints of a 3U nano-satellite platform. Thus, an effective sensor architecture for full-attitude determination was developed for the HERMES nano-satellites. The paper describes the hardware typologies and specifications, the configuration on the spacecraft, and the software elements to process the sensors' data to estimate the full-attitude and orbital states in such a complex nano-satellite mission. The aim of this study was to fully characterize the proposed sensor architecture, highlighting the available attitude and orbit determination performance and discussing the calibration and determination functions to be implemented on-board. The presented results derived from model-in-the-loop (MIL) and hardware-in-the-loop (HIL) verification and testing activities and can serve as useful resources and a benchmark for future nano-satellite missions. [ABSTRACT FROM AUTHOR]

This paper is devoted to electric arc furnace (EAF) modeling using a random differential equation based on the power balance equation. The proposed approach broadens and improves the model through the introduction of stochastic processes in place of existing coefficients. The paper presents a method which enables the estimation of EAF model coefficients with the help of measurement data - voltage and current waveforms recorded during the melting stage of an EAF work cycle. The estimation process is conducted with a Monte Carlo method and genetic algorithm, which is applied iteratively to each of the defined frames of the input signal. The estimated coefficients have been analyzed with respect to their time variability as well as the probability distributions of their values and increments. The results have been extensively visualized. Next, the identification of the stochastic processes representing the model coefficients has been carried out. Based on the previous results and autocorrelation functions, the density functions and parameters of discrete-time stochastic processes were identified. The paper presents solutions validated with statistical tests. [ABSTRACT FROM AUTHOR]

Many real data exhibit periodic behavior. The periodic autoregressive moving average (PARMA) is one of the most common and useful model to describe these data. In the classical case, the PARMA model is considered by the assumption of Gaussian (or finite-variance) distribution of the noise. However, the Gaussian distribution seems to be unsuitable in many real applications, especially when the corresponding data exhibit impulsive-like behavior. Therefore, the extensions of the classical PARMA models are considered and the Gaussian distribution of the noise is replaced by the so-called heavy-tailed distribution. One of the most known distribution that can be used here is the α - stable one. In this paper, we introduce a new estimation technique for the parameters of the multidimensional periodic autoregressive time series of order 1 (i.e., PAR(1)), which is based on fractional lower-order covariance, the alternative dependence measure adequate for α - stable distributed models. From theoretical point of view, the use of this technique is justified as in this case the classical measure (i.e., covariance) is not defined. The practical aspect of this technique is discussed. The efficiency of the technique on simulated data is demonstrated using the Monte Carlo approach in different contexts, including the sample size and index of stability α of the noise's distribution. Lastly, we present the real data analysis. [ABSTRACT FROM AUTHOR]

This editorial provides an overview of twenty scientific articles published in the special issue of Thermal Science. The papers were selected from among 601 contributions presented at the 14th Conference on Sustainable Development of Energy, Water and Environment Systems (SDEWES 2019), held October 1-6, 2019 in the city of Dubrovnik, Croatia. The topics covered in the special issue include: Energy savings in the building sector; Advanced combustion techniques and fuels; Combined heat and mass transfer of fluid-flow; and Sustainability issues in industrial and power plants: challenges and viable solutions. The editorial also emphasised the papers recently published in the Special Issues of leading scientific journals dedicated to the series of SDEWES Conferences. [ABSTRACT FROM AUTHOR]

Probability density function (PDF) control strategy investigates the controller design approaches where the random variables for the stochastic processes were adjusted to follow the desirable distributions. In other words, the shape of the system PDF can be regulated by controller design.Different from the existing stochastic optimization and control methods, the most important problem of PDF control is to establish the evolution of the PDF expressions of the system variables. Once the relationship between the control input and the output PDF is formulated, the control objective can be described as obtaining the control input signals which would adjust the system output PDFs to follow the pre-specified target PDFs. Motivated by the development of data-driven control and the state of the art PDF-based applications, this paper summarizes the recent research results of the PDF control while the controller design approaches can be categorized into three groups: (1) system model-based direct evolution PDF control; (2) model-based distribution-transformation PDF control methods and (3) data-based PDF control. In addition, minimum entropy control, PDF-based filter design, fault diagnosis and probabilistic decoupling design are also introduced briefly as extended applications in theory sense. [ABSTRACT FROM AUTHOR]

Heart failure (HF) is a complex syndrome which can be the exit of different etiologies which lead to a common clinical picture. Treatment outcome is modest and new insights into pathophysiology are needed to improve effectively diagnosis, prognosis, and therapy. As a complex disease, it can really benefit from the new approach provided by molecular medicine where information about the cell program can deeply change the patient management. The comprehension of molecular mechanisms relies on new technologies which are able to provide data at the different levels of the cell workflow. A proper processing of these data is as essential as the generation of data itself, together with an integrative approach able to exploit observations at different scales, starting from the molecular levels up to an effective assessment of phenotype with cardiovascular and systemic parameters. In this paper, evidences concerning current understanding of HF, passing from one scale to another, are reported, to underline how functional genomics and systems biology perspective, fostered by the combination of biotechnologies and bioinformatic methods, may transform the concepts of diagnosis and, consequently, of treatment, toward the fulfillment of the invoked patient-specific medicine. [ABSTRACT FROM PUBLISHER]

This index covers all technical items - papers, correspondence, reviews, etc. - that appeared in this periodical during the year, and items from previous years that were commented upon or corrected in this year. Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name. The primary entry includes the co-authors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages. Note that the item title is found only under the primary entry in the Author Index. [ABSTRACT FROM AUTHOR]

This index covers all technical items - papers, correspondence, reviews, etc. - that appeared in this periodical during the year, and items from previous years that were commented upon or corrected in this year. Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name. The primary entry includes the co-authors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages. Note that the item title is found only under the primary entry in the Author Index. [ABSTRACT FROM AUTHOR]

This paper analyses the comminution process. There are two random functions: the selection function and the breakage function in the stochastic model based on population balance. Introducing the energy balance, applying the maximum informational entropy method and taking into consideration the normalized condition, enables us to formulate and solve the variational problem and determine the breakage function by Lagrange’s multipliers method. The above determination of the breakage function is an original new method. The sought form of the breakage function is an argument of the constrained extremum of an integral functional with two indirect conditions. The obtained form of the breakage function was applied to the equation of the population balance. This leads to the prediction of the particle size distribution of the single comminution product with an additional assumption concerning the form of the selection function. [ABSTRACT FROM AUTHOR]

The article describes computational approaches for analyzing physiological time series. It focuses on the analysis of interbeat intervals in human subjects. The article shows that the application of the methods could potentially lead to a novel diagnostic tool for distinguishing healthy individuals from those with congestive heart failure.

Spectral analysis of a 10-min electroencephalogram (EEG) record has made it possible to describe the behavior of EEG rhythms as a dynamic spectrum and find a distinct periodic pattern in this behavior. The data on the dynamic spectra of long EEGs offer a new insight into the estimation of the stability of EEG electrical processes in healthy subjects, inter- and intrahemispheric relationships between the electrical activities of different cortical regions, and estimation of phase relations, which were previously performed on the basis of comparison between single EEG spectral patterns. [ABSTRACT FROM AUTHOR]

Methods for tracking the dynamics of the blood flow microcirculation obtained by laser-Doppler flowmetry (LDF) technique are described. It was shown that LDF signals have complex dynamics. It was mainly characterized by fractal structures and chaos, though multiperiodic, trend-like and stochastic components were also established. Procedures for (i) describing the dynamic structure and (ii) tracking the dynamic changes in time of LDF data are proposed. Examples illustrating the efficiency of these procedures are given using both simulated and LDF data collected in experiments with reactive hyperemia. Irrespective of the universality of the methods, the procedures should be specified according to the problem-oriented clinical and experimental studies. [ABSTRACT FROM AUTHOR]

This article proposes a configurationality parameter based solely on the issue of criteriality for fulfillment of the fundamental function of syntax, which is the establishment of linkage between lexemes and their grammatical relations. The two alternative linking systems discussed here are structural and morphological (S-systems and M-systems). S-systems are found in all language, whereas M-systems are found only in certain languages, and there only in isolated pockets which co-occur with specificity gaps in the respective S-system. In the past, observations about the authenticity and idiomaticness of the language of the Gothic Bible have been based on the examination of very limited phenomena as well as on subjective impressions. A general methodology is suggested here for thorough comparison of the Gothic with the Greek original. Application of this methodology to four sample chapters reveals significant and consistent variation in certain areas, although very little variation is found in the area of word order. The latter fact, along with some other considerations, suggests that Gothic had an M-system somewhat comparable to that of Koine Greek. [ABSTRACT FROM PUBLISHER]

Optical microscopy has for centuries been a key tool to study living cells with minimum invasiveness. The advent of single molecule techniques over the past two decades has revolutionized the field of cell biology by providing a more quantitative picture of the complex and highly dynamic organization of living systems. Amongst these techniques, single particle tracking (SPT) has emerged as a powerful approach to study a variety of dynamic processes in life sciences. SPT provides access to single molecule behavior in the natural context of living cells, thereby allowing a complete statistical characterization of the system under study. In this review we describe the foundations of SPT together with novel optical implementations that nowadays allow the investigation of single molecule dynamic events with increasingly high spatiotemporal resolution using molecular densities closer to physiological expression levels. We outline some of the algorithms for the faithful reconstruction of SPT trajectories as well as data analysis, and highlight biological examples where the technique has provided novel insights into the role of diffusion regulating cellular function. The last part of the review concentrates on different theoretical models that describe anomalous transport behavior and ergodicity breaking observed from SPT studies in living cells. [ABSTRACT FROM AUTHOR]

This index covers all technical items - papers, correspondence, reviews, etc. - that appeared in this periodical during the year, and items from previous years that were commented upon or corrected in this year. Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name. The primary entry includes the co-authors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages. Note that the item title is found only under the primary entry in the Author Index. [ABSTRACT FROM AUTHOR]

A subject and author index for the January 2012 issue of "IEEE Journal on Selected Areas in Communications" is presented.