Habitability: a process versus a state variable framework with observational tests and theoretical implications

International Journal of Astrobiology ◽

10.1017/s1473550420000415 ◽

2021 ◽

pp. 1-8

Author(s):

A. Lenardic ◽

J. Seales

Keyword(s):

Process Variable ◽

State Variable ◽

Modelling Framework ◽

Meta Level ◽

Planetary Habitability

The term habitable is used to describe planets that can harbour life. Debate exists as to specific conditions that allow for habitability but the use of the term as a planetary variable has become ubiquitous. This paper poses a meta-level question: What type of variable is habitability? Is it akin to temperature, in that it is something that characterizes a planet, or is something that flows through a planet, akin to heat? That is, is habitability a state or a process variable? Forth coming observations can be used to discriminate between these end-member hypotheses. Each has different implications for the factors that lead to differences between planets (e.g. the differences between Earth and Venus). Observational tests can proceed independent of any new modelling of planetary habitability. However, the viability of habitability as a process can influence future modelling. We discuss a specific modelling framework based on anticipating observations that can discriminate between different views of habitability.

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A Variable Weight Function Model in Geological Variables Function Research

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.785-786.1423 ◽

2013 ◽

Vol 785-786 ◽

pp. 1423-1429

Author(s):

Wen Bo Liu ◽

Lai Jun Liu

Keyword(s):

Weight Function ◽

Mineral Resources ◽

Process Variable ◽

Mathematics Model ◽

Constant Weight ◽

Connection Degree ◽

State Variable ◽

Variable Weight ◽

The Status ◽

Constant Coefficients

In mineral resources prediction and other research of geological variables, stability exactness of quantitative models concern modeling conditions, geological variables from model and the status of the variable. In traditional geological modeling process, variable support is measured under some contrains weight and this kind of weight is characterized by constant coefficients. Constant weight[1] has some limitations due to structuredness and dependency of variable. For overcoming the inflexibility of constant weight, this paper proposes geological variable mathematics model basedd state variable vector. We revise existing form of state variable weight and provide logarithm state variable vector as measurement level of geological variable weight coefficients. According to 1:200000 scale geochemistry measured data from Baishan area, we calculate the samples unit connection degree based on exponent and logarithm state variable vector and compare the connection degree based on constant weight. The connection degree sorting has the similarity as a whole among them, but there is the obvious difference locally. We can conclude that geological variable weight function based on state variable vector is more flexible and fine.

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Stochastic dynamics of snow avalanche occurrence by superposition of Poisson processes

Proceedings of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rspa.2012.0396 ◽

2012 ◽

Vol 468 (2148) ◽

pp. 4193-4208 ◽

Cited By ~ 7

Author(s):

Paolo Perona ◽

Edoardo Daly ◽

Benoît Crouzy ◽

Amilcare Porporato

Keyword(s):

Snow Depth ◽

Stochastic Dynamics ◽

Probability Distributions ◽

Poisson Processes ◽

Entropy Function ◽

Constant Frequency ◽

State Variable ◽

Modelling Framework ◽

State Dependent ◽

Deterministic Trajectories

We study the dynamics of systems with deterministic trajectories randomly forced by instantaneous discontinuous jumps occurring according to two different compound Poisson processes. One process, with constant frequency, causes instantaneous positive random increments, whereas the second process has a state-dependent frequency and describes negative jumps that force the system to restart from zero (renewal jumps). We obtain the probability distributions of the state variable and the magnitude and intertimes of the jumps to zero. This modelling framework is used to describe snow-depth dynamics on mountain hillsides, where the positive jumps represent snowfall events, whereas the jumps to zero describe avalanches. The probability distributions of snow depth, together with the statistics of avalanche magnitude and occurrence, are used to explain the correlation between avalanche occurrence and snowfall as a function of hydrologic, terrain slope and aspect parameters. This information is synthesized into a ‘prediction entropy’ function that gives the level of confidence of avalanche occurrence prediction in relation to terrain properties.

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A Measurement Modelling Framework for Complex Working Memory Models

PsycEXTRA Dataset ◽

10.1037/e520602012-292 ◽

2011 ◽

Author(s):

Klaus Oberauer ◽

Jarrold Chris ◽

Farrell Simon ◽

Lewandowsky Stephan

Keyword(s):

Working Memory ◽

Memory Models ◽

Modelling Framework ◽

Working Memory Models

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Adaptive identification methods of nonlinear random electrical signal

International Journal of Applied Electromagnetics and Mechanics ◽

10.3233/jae-209349 ◽

2020 ◽

Vol 64 (1-4) ◽

pp. 431-438

Author(s):

Jian Liu ◽

Lihui Wang ◽

Zhengqi Tian

Keyword(s):

Wavelet Transform ◽

Electric Vehicle ◽

Signal To Noise Ratio ◽

Sudden Change ◽

Electrical Signal ◽

Signal Recognition ◽

State Variable ◽

Signal Characteristics ◽

The Matrix ◽

Kalman Filter Algorithm

The nonlinearity of the electric vehicle DC charging equipment and the complexity of the charging environment lead to the complex and changeable DC charging signal of the electric vehicle. It is urgent to study the distortion signal recognition method suitable for the electric vehicle DC charging. Focusing on the characteristics of fundamental and ripple in DC charging signal, the Kalman filter algorithm is used to establish the matrix model, and the state variable method is introduced into the filter algorithm to track the parameter state, and the amplitude and phase of the fundamental waves and each secondary ripple are identified; In view of the time-varying characteristics of the unsteady and abrupt signal in the DC charging signal, the stratification and threshold parameters of the wavelet transform are corrected, and a multi-resolution method is established to identify and separate the unsteady and abrupt signals. Identification method of DC charging distortion signal of electric vehicle based on Kalman/modified wavelet transform is used to decompose and identify the signal characteristics of the whole charging process. Experiment results demonstrate that the algorithm can accurately identify ripple, sudden change and unsteady wave during charging. It has higher signal to noise ratio and lower mean root mean square error.

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Importance of the Intersection of Library and Information Sciences with Systems Theory

Journal of Critical Library and Information Studies ◽

10.24242/jclis.v1i1.23 ◽

2017 ◽

Vol 1 (1) ◽

Author(s):

Hannah Lee

Keyword(s):

System Theory ◽

General System ◽

General System Theory ◽

Von Bertalanffy ◽

Meta Level ◽

Professional Field ◽

The Subject ◽

Critical Insight ◽

Insight Into ◽

Information Sciences

This paper is the attempt to show how system theory could provide critical insight into the transdisciplinary field of library and information sciences (LIS). It begins with a discussion on the categorization of library and information sciences as an academic and professional field (or rather, the lack of evidence on the subject) and what is exactly meant by system theory, drawing upon the general system theory established by Ludwig von Bertalanffy. The main conversation of this paper focuses on the inadequacies of current meta-level discussions of LIS and the benefits of general system theory (particularly when considering the exponential rapidity in which information travels) with LIS.

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