Stochastic growth

2005 ◽  
Vol 62 (8) ◽  
pp. 1746-1755 ◽  
Author(s):  
Gudmundur Gudmundsson
Keyword(s):  
Growth Models ◽  
Individual Growth ◽  
Stochastic Growth ◽  
Actual Length ◽  
Size Dependent ◽  
Growth Functions ◽  
Random Term ◽  
Large Fluctuations ◽  
Environmental Variations ◽  
Living Organisms

Environmental variations in food and temperature induce substantial irregular variations in the growth of many living organisms. In fisheries research, stochastic growth has been modelled by adding a random term to deterministic growth functions. This entails large fluctuations in individual growth paths, including spells of negative growth. A different approach to modelling stochastic growth is presented where the anomalous short-term behaviour is avoided. The third moment of length distributions contains valuable information for the formulation of growth models. The size distribution of actual stocks is modified by size-dependent mortality. New methods for estimation of growth functions, taking this effect into account, are presented, requiring less specific assumptions about the properties of growth and stochastic variations than previous methods. Actual length distributions are also affected by genetic variability. The effects of this upon the development of second and third moments of length distributions with age differ depending on whether they are associated with maximum length or growth.

scholarly journals Architecture of RNA influences plant biology

2021 ◽  
Author(s):  
Jiaying Zhu ◽  
Changhao Li ◽  
Xu Peng ◽  
Xiuren Zhang
Keyword(s):  
Rna Binding ◽  
Rna Binding Proteins ◽  
Mirna Biogenesis ◽  
Plant Responses ◽  
Tertiary Structures ◽  
Rna Transcripts ◽  
Environmental Variations ◽  
Living Organisms ◽  
Processing Stability

Abstract The majority of the genome is transcribed to RNA in living organisms. RNA transcripts can form astonishing arrays of secondary and tertiary structures via Watson-Crick, Hoogsteen or wobble base pairing. In vivo, RNA folding is not a simple thermodynamics event of minimizing free energy. Instead, the process is constrained by transcription, RNA binding proteins (RBPs), steric factors and micro-environment. RNA secondary structure (RSS) plays myriad roles in numerous biological processes, such as RNA processing, stability, transportation and translation in prokaryotes and eukaryotes. Emerging evidence has also implicated RSS in RNA trafficking, liquid-liquid phase separation and plant responses to environmental variations such as temperature and salinity. At the molecular level, RSS is correlated with regulating splicing, polyadenylation, protein systhsis, and miRNA biogenesis and functions. In this review, we summarized newly reported methods for probing RSS in vivo and functions and mechanisms of RSS in plant physiology.

scholarly journals Comparison of growth models to describe growth from birth to 6 years in a Beninese cohort of children with repeated measurements

BMJ Open ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. e035785
Author(s):  
Shukrullah Ahmadi ◽  
Florence Bodeau-Livinec ◽  
Roméo Zoumenou ◽  
André Garcia ◽  
David Courtin ◽  
...  
Keyword(s):  
Growth Model ◽  
Goodness Of Fit ◽  
Growth Models ◽  
Information Criterion ◽  
Height Growth ◽  
Sub Saharan Africa ◽  
Individual Growth ◽  
Secondary Outcome ◽  
Growth Trajectories ◽  
Best Fitting

ObjectiveTo select a growth model that best describes individual growth trajectories of children and to present some growth characteristics of this population.SettingsParticipants were selected from a prospective cohort conducted in three health centres (Allada, Sekou and Attogon) in a semirural region of Benin, sub-Saharan Africa.ParticipantsChildren aged 0 to 6 years were recruited in a cohort study with at least two valid height and weight measurements included (n=961).Primary and secondary outcome measuresThis study compared the goodness-of-fit of three structural growth models (Jenss-Bayley, Reed and a newly adapted version of the Gompertz growth model) on longitudinal weight and height growth data of boys and girls. The goodness-of-fit of the models was assessed using residual distribution over age and compared with the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The best-fitting model allowed estimating mean weight and height growth trajectories, individual growth and growth velocities. Underweight, stunting and wasting were also estimated at age 6 years.ResultsThe three models were able to fit well both weight and height data. The Jenss-Bayley model presented the best fit for weight and height, both in boys and girls. Mean height growth trajectories were identical in shape and direction for boys and girls while the mean weight growth curve of girls fell slightly below the curve of boys after neonatal life. Finally, 35%, 27.7% and 8% of boys; and 34%, 38.4% and 4% of girls were estimated to be underweight, wasted and stunted at age 6 years, respectively.ConclusionThe growth parameters of the best-fitting Jenss-Bayley model can be used to describe growth trajectories and study their determinants.

Discrete Stochastic Growth Models for Two-Dimensional Shapes

1994 ◽  
pp. 301-318 ◽  
Author(s):  
Scott Thompson ◽  
Azriel Rosenfeld
Keyword(s):  
Growth Models ◽  
Two Dimensional ◽  
Stochastic Growth ◽  
Stochastic Growth Models

Maturity in Outsourcing Relationships

2010 ◽  
pp. 98-117
Author(s):  
Hans Solli-Sæther ◽  
Petter Gottschalk
Keyword(s):  
Life Cycle ◽  
Information Systems ◽  
Product Life Cycle ◽  
Growth Models ◽  
It Outsourcing ◽  
Growth Stages ◽  
Stage Model ◽  
Stages Of Growth ◽  
Systems Planning ◽  
Living Organisms

Stages of growth models have been used widely in both organizational research and information technology management research. According to King and Teo (1997), these models describe a wide variety of phenomena – the organizational life cycle, product life cycle, biological growth, stages of growth in information systems, growth model for integration between business planning and information systems planning, electronic commerce evolution, stages of knowledge management technology, and a number of other interesting developments in time perspectives. These models assume that predictable patterns (conceptualized in terms of stages or levels) exist in the growth of organizations and organizational parts, the sales levels of products, and the growth of living organisms. These stages are (1) sequential in nature, (2) occur as a hierarchical progression that is not easily reversed, and (3) evolve a broad range of organizational activities and structures. This chapter starts with an introduction to stages of growth models. In the following sections we present the three-stage model for the evolution of IT outsourcing relationships (Gottschalk & Solli-Sæther, 2006). The three stages are labelled cost stage, resource stage, and partnership stage respectively. Theory-based benchmark variables for measuring maturity in IT outsourcing relationships are presented, followed by the stage hypothesis and a description of how benchmark variables are used to indicate characteristics at each stage of growth. Finally in this chapter, we present results from an exploratory study testing the stage model. The purpose of this chapter is to develop a framework for improved understanding of the current situation in an IT outsourcing relationship in terms of a specific stage, to develop strategies for moving to a higher stage in the future, and to learn from earlier stage experience.

The association of socioeconomic status with quality of life in cancer patients over a 6-month period using individual growth models

2019 ◽  
Vol 27 (9) ◽  
pp. 3347-3355 ◽  
Author(s):  
Julia Roick ◽  
Helge Danker ◽  
Anette Kersting ◽  
Arne Dietrich ◽  
Andreas Dietz ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Socioeconomic Status ◽  
Cancer Patients ◽  
Growth Models ◽  
Individual Growth

Population structure of sigmodontine rodents through age estimation by individual growth models

2021 ◽  
Vol 66 (4) ◽  
pp. 649-656
Author(s):  
Irene Laura Gorosito ◽  
Maria Busch
Keyword(s):  
Population Structure ◽  
Age Estimation ◽  
Growth Models ◽  
Individual Growth

Limit theorems for stochastic growth models. I

1972 ◽  
Vol 4 (02) ◽  
pp. 193-232 ◽  
Author(s):  
Harry Kesten
Keyword(s):  
Fixed Point ◽  
Limit Theorem ◽  
Limit Theorems ◽  
Growth Models ◽  
Branching Processes ◽  
Random Variable ◽  
Present Situation ◽  
Stochastic Growth ◽  
Stochastic Growth Models ◽  
Zygotic Selection

We consider d-dimensional stochastic processes which take values in (R+) d . These processes generalize Galton-Watson branching processes, but the main assumption of branching processes, independence between particles, is dropped. Instead, we assume for some Here τ: (R+) d → R+, |x| = Σ1 d |x(i)| A = {x ∈ (R+) d : |x| = 1} and T: A → A. Under various assumptions on the maps τ and T it is shown that with probability one there exists a ρ > 1, a fixed point p ∈ A of T and a random variable w such that lim n→∞ Z n ρ−n = wp. This result is a generalization of the main limit theorem for super-critical branching processes; note, however, that in the present situation both p and ρ are random as well. The results are applied to a population genetical model for zygotic selection without mutation at one locus.

Limit theorems for stochastic growth models. II

1972 ◽  
Vol 4 (3) ◽  
pp. 393-428 ◽  
Author(s):  
Harry Kesten
Keyword(s):  
Limit Theorems ◽  
Growth Models ◽  
Branching Processes ◽  
Random Variable ◽  
Present Situation ◽  
Stochastic Growth ◽  
Stochastic Growth Models ◽  
Zygotic Selection ◽  
Image Position ◽  
Supercritical Branching Processes

We consider d-dimensional stochastic processes which take values in (R+)d These processes generalize Galton-Watson branching processes, but the main assumption of branching processes, independence between particles, is dropped. Instead, we assume for some Here τ:(R+)d→R +, |x| = σ1d |x(i)|, A {x ∈(R+)d: |x| 1} and T: A→A. Under various assumptions on the maps τ and T it is shown that with probability one there exists a ρ > 1, a fixed point p ∈ A of T and a random variable w such that limn→∞Zn|ρnwp. This result is a generalization of the main limit theorem for supercritical branching processes; note, however, that in the present situation both ρ and ρ are random as well. The results are applied to a population genetical model for zygotic selection without mutation at one locus.

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