Sustainable Complex Coevolutionary Systems Engineering
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The climate conundrum: Financing smallholder productivity and resilience in the age of climate change | RAFLearning

The climate conundrum: Financing smallholder productivity and resilience in the age of climate change | RAFLearning | Sustainable Complex Coevolutionary Systems Engineering | Scoop.it
The thirteenth briefing note in a series from the Initiative for Smallholder Finance, explores the latest practices from the climate finance community and the agricultural finance community to understand how new combined models can boost returns and attract new investors.
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Food for thought and action...
 
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The long road of statistical learning research: past, present and future

The long road of statistical learning research: past, present and future | Sustainable Complex Coevolutionary Systems Engineering | Scoop.it
Almost all types of learning involve, to some degree, the ability to encode regularities across time and space. Although statistical learning (SL) research initially focused on offering a viable alternative to rule-based grammars and specialized mechanisms for word learning (e.g. [[1][1],[2][2]]),
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Symplectic Entropy as a Novel Measure for Complex Systems

Symplectic Entropy as a Novel Measure for Complex Systems | Sustainable Complex Coevolutionary Systems Engineering | Scoop.it
Real systems are often complex, nonlinear, and noisy in various fields, including mathematics, natural science, and social science. We present the symplectic entropy (SymEn) measure as well as an analysis method based on SymEn to estimate the nonlinearity of a complex system by analyzing the given time series. The SymEn estimation is a kind of entropy based on symplectic principal component analysis (SPCA), which represents organized but unpredictable behaviors of systems. The key to SPCA is to preserve the global submanifold geometrical properties of the systems through a symplectic transform in the phase space, which is a kind of measure-preserving transform. The ability to preserve the global geometrical characteristics makes SymEn a test statistic for the detection of the nonlinear characteristics in several typical chaotic time series, and the stochastic characteristic in Gaussian white noise. The results are in agreement with findings in the approximate entropy (ApEn), the sample entropy (SampEn), and the fuzzy entropy (FuzzyEn). Moreover, the SymEn method is also used to analyze the nonlinearities of real signals (including the electroencephalogram (EEG) signals for Autism Spectrum Disorder (ASD) and healthy subjects, and the sound and vibration signals for mechanical systems). The results indicate that the SymEn estimation can be taken as a measure for the description of the nonlinear characteristics in the data collected from natural complex systems.
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Tissue-scale, personalized modeling and simulation of prostate cancer growth

National Academy of Sciences
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The ethics of data and of data science: an economist's perspective

The ethics of data and of data science: an economist's perspective | Sustainable Complex Coevolutionary Systems Engineering | Scoop.it
Data collection and modelling are increasingly important in social science and science-based policy, but threaten to crowd out other ways of thinking. Economists recognize that markets embody and shed light on human sentiments. However, their ethical consequences have been difficult to interpret, let alone manage. Although economic mechanisms are changed by data intensity, they can be redesigned to restore their benefits. We conclude with four cautions: if data are good, more may not be better; scientifically desirable data properties may not help policy; consent is a double-edged tool; and data exist only because someone thought to capture and codify them.

This article is part of the themed issue ‘The ethical impact of data science’.
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Numerical algebraic geometry for model selection and its application to the life sciences

Numerical algebraic geometry for model selection and its application to the life sciences | Sustainable Complex Coevolutionary Systems Engineering | Scoop.it
Researchers working with mathematical models are often confronted by the related problems of parameter estimation, model validation and model selection. These are all optimization problems, well known to be challenging due to nonlinearity, non-convexity and multiple local optima. Furthermore, the challenges are compounded when only partial data are available. Here, we consider polynomial models (e.g. mass-action chemical reaction networks at steady state) and describe a framework for their analysis based on optimization using numerical algebraic geometry. Specifically, we use probability-one polynomial homotopy continuation methods to compute all critical points of the objective function, then filter to recover the global optima. Our approach exploits the geometrical structures relating models and data, and we demonstrate its utility on examples from cell signalling, synthetic biology and epidemiology.
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On the possibility of galactic cosmic ray-induced radiolysis-powered life in subsurface environments in the Universe

On the possibility of galactic cosmic ray-induced radiolysis-powered life in subsurface environments in the Universe | Sustainable Complex Coevolutionary Systems Engineering | Scoop.it
Photosynthesis is a mechanism developed by terrestrial life to utilize the energy from photons of solar origin for biological use. Subsurface regions are isolated from the photosphere, and consequently are incapable of utilizing this energy. This opens up the opportunity for life to evolve alternative mechanisms for harvesting available energy. Bacterium Candidatus Desulforudis audaxviator , found 2.8 km deep in a South African mine, harvests energy from radiolysis, induced by particles emitted from radioactive U, Th and K present in surrounding rock. Another radiation source in the subsurface environments is secondary particles generated by galactic cosmic rays (GCRs). Using Monte Carlo simulations, it is shown that it is a steady source of energy comparable to that produced by radioactive substances, and the possibility of a slow metabolizing life flourishing on it cannot be ruled out. Two mechanisms are proposed through which GCR-induced secondary particles can be utilized for biological use in subsurface environments: (i) GCRs injecting energy in the environment through particle-induced radiolysis and (ii) organic synthesis from GCR secondaries interacting with the medium. Laboratory experiments to test these hypotheses are also proposed. Implications of these mechanisms on finding life in the Solar System and elsewhere in the Universe are discussed.
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Symmetry and reduction in collectives: low-dimensional cyclic pursuit

Symmetry and reduction in collectives: low-dimensional cyclic pursuit | Sustainable Complex Coevolutionary Systems Engineering | Scoop.it
We investigate low-dimensional examples of cyclic pursuit in a collective, wherein each agent employs a constant bearing (CB) steering law relative to exactly one other agent. For the case of three agents in the plane, we characterize relative equilibria and pure shape equilibria of associated closed-loop dynamics. Re-scaling time yields a reduction of phase space to two dimensions and effective tools for stability analysis. Study of bifurcation of a family of collinear equilibria dependent on a single CB control parameter reveals the presence of a rich collection of trajectories that are periodic in shape and undergo precession in physical space. For collectives in three dimensions, with an appropriate notion of CB pursuit strategy and corresponding steering law, the two-agent case proves to be explicitly integrable. These results suggest control schemes for small teams of mobile robotic agents engaged in area coverage tasks such as search and rescue, and raise interesting possibilities for behaviour in biological contexts.
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Molecular and cellular bases of adaptation to a changing environment in microorganisms

Molecular and cellular bases of adaptation to a changing environment in microorganisms | Sustainable Complex Coevolutionary Systems Engineering | Scoop.it
Environmental heterogeneity constitutes an evolutionary challenge for organisms. While evolutionary dynamics under variable conditions has been explored for decades, we still know relatively little about the cellular and molecular mechanisms involved. It is of paramount importance to examine these molecular bases because they may play an important role in shaping the course of evolution. In this review, we examine the diversity of adaptive mechanisms in the face of environmental changes. We exploit the recent literature on microbial systems because those have benefited the most from the recent emergence of genetic engineering and experimental evolution followed by genome sequencing. We identify four emerging trends: (i) an adaptive molecular change in a pathway often results in fitness trade-off in alternative environments but the effects are dependent on a mutation's genetic background; (ii) adaptive changes often modify transcriptional and signalling pathways; (iii) several adaptive changes may occur within the same molecular pathway but be associated with pleiotropy of different signs across environments; (iv) because of their large associated costs, macromolecular changes such as gene amplification and aneuploidy may be a rapid mechanism of adaptation in the short-term only. The course of adaptation in a variable environment, therefore, depends on the complexity of the environment but also on the molecular relationships among the genes involved and between the genes and the phenotypes under selection.
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Waiting time to infectious disease emergence

Waiting time to infectious disease emergence | Sustainable Complex Coevolutionary Systems Engineering | Scoop.it
Emerging diseases must make a transition from stuttering chains of transmission to sustained chains of transmission, but this critical transition need not coincide with the system becoming supercritical. That is, the introduction of infection to a supercritical system results in a significant fraction of the population becoming infected only with a certain probability. Understanding the waiting time to the first major outbreak of an emerging disease is then more complicated than determining when the system becomes supercritical. We treat emergence as a dynamic bifurcation, and use the concept of bifurcation delay to understand the time to emergence after a system becomes supercritical. Specifically, we consider an SIR model with a time-varying transmission term and random infections originating from outside the population. We derive an analytic density function for the delay times and find it to be, in general, in agreement with stochastic simulations. We find the key parameters to be the rate of introduction of infection and the rate of change of the basic reproductive ratio. These findings aid our understanding of real emergence events, and can be incorporated into early-warning systems aimed at forecasting disease risk.
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Protected areas and poverty

Protected areas and poverty | Sustainable Complex Coevolutionary Systems Engineering | Scoop.it
Protected areas are controversial because they are so important for conservation and because they distribute fortune and misfortune unevenly. The nature of that distribution, as well as the terrain of protected areas themselves, have been vigorously contested. In particular, the relationship between protected areas and poverty is a long-running debate in academic and policy circles. We review the origins of this debate and chart its key moments. We then outline the continuing flashpoints and ways in which further evaluation studies could improve the evidence base for policy-making and conservation practice.
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Chasing Ecological Interactions

Chasing Ecological Interactions | Sustainable Complex Coevolutionary Systems Engineering | Scoop.it
Pedro Jordano assesses the challenges of studying the functional aspects of species interactions and how basic research is helping us to address the current fast-paced extinction of species due to human activities.
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Corporate culture has no place in academia

Corporate culture has no place in academia | Sustainable Complex Coevolutionary Systems Engineering | Scoop.it
‘Academic capitalism’ contributed to the mishandling of the Macchiarini case by officials at the Karolinska Institute in Sweden, argues Olof Hallonsten.
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Playing counter-strike versus running: The impact of leisure time activities and cortisol on intermediate-term memory in male students

Playing counter-strike versus running: The impact of leisure time activities and cortisol on intermediate-term memory in male students | Sustainable Complex Coevolutionary Systems Engineering | Scoop.it
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The neurobiology of uncertainty: implications for statistical learning

The neurobiology of uncertainty: implications for statistical learning | Sustainable Complex Coevolutionary Systems Engineering | Scoop.it
The capacity for assessing the degree of uncertainty in the environment relies on estimating statistics of temporally unfolding inputs. This, in turn, allows calibration of predictive and bottom-up processing, and signalling changes in temporally unfolding environmental features. In the last decade, several studies have examined how the brain codes for and responds to input uncertainty. Initial neurobiological experiments implicated frontoparietal and hippocampal systems, based largely on paradigms that manipulated distributional features of visual stimuli. However, later work in the auditory domain pointed to different systems, whose activation profiles have interesting implications for computational and neurobiological models of statistical learning (SL). This review begins by briefly recapping the historical development of ideas pertaining to the sensitivity to uncertainty in temporally unfolding inputs. It then discusses several issues at the interface of studies of uncertainty and SL. Following, it presents several current treatments of the neurobiology of uncertainty and reviews recent findings that point to principles that serve as important constraints on future neurobiological theories of uncertainty, and relatedly, SL. This review suggests it may be useful to establish closer links between neurobiological research on uncertainty and SL, considering particularly mechanisms sensitive to local and global structure in inputs, the degree of input uncertainty, the complexity of the system generating the input, learning mechanisms that operate on different temporal scales and the use of learnt information for online prediction.

This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences’.
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Multiplex social ecological network analysis reveals how social changes affect community robustness more than resource depletion

National Academy of Sciences
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Carbon is not the enemy

Carbon is not the enemy | Sustainable Complex Coevolutionary Systems Engineering | Scoop.it
Design with the natural cycle in mind to ensure that carbon ends up in the right places, urges William McDonough
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Wildlife in decline: Earth's vertebrates fall 58% in past four decades

Wildlife in decline: Earth's vertebrates fall 58% in past four decades | Sustainable Complex Coevolutionary Systems Engineering | Scoop.it
Living Planet Report predicts that by 2020, populations will have declined by two-thirds from 1970.
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Symmetry-breaking phase transitions in highly concentrated semen

Symmetry-breaking phase transitions in highly concentrated semen | Sustainable Complex Coevolutionary Systems Engineering | Scoop.it
New experimental evidence of self-motion of a confined active suspension is presented. Depositing fresh semen sample in an annular shaped microfluidic chip leads to a spontaneous vortex state of the fluid at sufficiently large sperm concentration. The rotation occurs unpredictably clockwise or counterclockwise and is robust and stable. Furthermore, for highly active and concentrated semen, richer dynamics can occur such as self-sustained or damped rotation oscillations. Experimental results obtained with systematic dilution provide a clear evidence of a phase transition towards collective motion associated with local alignment of spermatozoa akin to the Vicsek model. A macroscopic theory based on previously derived self-organized hydrodynamics models is adapted to this context and provides predictions consistent with the observed stationary motion.
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Organized hypocrisy, organizational façades, and sustainability reporting

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On the use of Bayesian decision theory for issuing natural hazard warnings

On the use of Bayesian decision theory for issuing natural hazard warnings | Sustainable Complex Coevolutionary Systems Engineering | Scoop.it
Warnings for natural hazards improve societal resilience and are a good example of decision-making under uncertainty. A warning system is only useful if well defined and thus understood by stakeholders. However, most operational warning systems are heuristic: not formally or transparently defined. Bayesian decision theory provides a framework for issuing warnings under uncertainty but has not been fully exploited. Here, a decision theoretic framework is proposed for hazard warnings. The framework allows any number of warning levels and future states of nature, and a mathematical model for constructing the necessary loss functions for both generic and specific end-users is described. The approach is illustrated using one-day ahead warnings of daily severe precipitation over the UK, and compared to the current decision tool used by the UK Met Office. A probability model is proposed to predict precipitation, given ensemble forecast information, and loss functions are constructed for two generic stakeholders: an end-user and a forecaster. Results show that the Met Office tool issues fewer high-level warnings compared with our system for the generic end-user, suggesting the former may not be suitable for risk averse end-users. In addition, raw ensemble forecasts are shown to be unreliable and result in higher losses from warnings.
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WMO GREENHOUSE GAS
BULLETIN

The State of Greenhouse Gases in the Atmosphere Based on Global Observations through 2015
 
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An investigation of the false discovery rate and the misinterpretation of p-values

An investigation of the false discovery rate and the misinterpretation of p-values | Sustainable Complex Coevolutionary Systems Engineering | Scoop.it
If you use p =0.05 to suggest that you have made a discovery, you will be wrong at least 30% of the time. If, as is often the case, experiments are underpowered, you will be wrong most of the time. This conclusion is demonstrated from several points of view. First, tree diagrams which show the close analogy with the screening test problem. Similar conclusions are drawn by repeated simulations of t -tests. These mimic what is done in real life, which makes the results more persuasive. The simulation method is used also to evaluate the extent to which effect sizes are over-estimated, especially in underpowered experiments. A script is supplied to allow the reader to do simulations themselves, with numbers appropriate for their own work. It is concluded that if you wish to keep your false discovery rate below 5%, you need to use a three-sigma rule, or to insist on p ≤0.001. And never use the word ‘significant’.
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Keeping Signals Straight: How Cells Process Information and Make Decisions

Keeping Signals Straight: How Cells Process Information and Make Decisions | Sustainable Complex Coevolutionary Systems Engineering | Scoop.it
PLOS Biology 's first ever Research Matters explains the importance of understanding the transmission and interpretation of complex biological signals by our own cells and by the bacterial cells that live in or on us.
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Interoception beyond homeostasis: affect, cognition and mental health

Interoception beyond homeostasis: affect, cognition and mental health | Sustainable Complex Coevolutionary Systems Engineering | Scoop.it
Interoception refers to the sensing of the internal state of one's body. Interoception is distinct from the processing of sensory information concerning external (non-self) stimuli (e.g. vision, hearing, touch and smell) and is the afferent axis to internal (autonomic and hormonal) physiological control. However, the impact of interoception extends beyond homeostatic/allostatic reflexes: it is proposed to be fundamental to motivation, emotion (affective feelings and behaviours), social cognition and self-awareness. This view is supported by a growing body of experimental evidence that links peripheral physiological states to mental processes. Within this framework, the representation of self is constructed from early development through continuous integrative representation of biological data from the body, to form the basis for those aspects of conscious awareness grounded on the subjective sense of being a unique individual. This theme issue of the Philosophical Transactions of the Royal Society B draws together state-of-the-art knowledge concerning theoretical, experimental and clinical facets of interoception with the emphasis on cognitive and affective neuroscience. The multidisciplinary and cross-disciplinary perspectives represented in this theme issue disseminate and entrench knowledge about interoception across the scientific community and provide a reference for the conceptualization and further study of interoception across behavioural sciences.
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