Phytomorphology — if concerned with development — often concentrates on correlative changes of form and neglects the aspects of age, time and clock, although the plant's spatial and temporal organisation are intimately interconnected. Common age as measured in physical time by a physical process is compared to biological age as measured by a biological clock based on a biological process. A typical example for a biological clock on the organ level is, for example, a shoot. Its (...) biological age is measured by the biological time unit of a plastochron, which itself is defined by the cyclic-periodic initiation of the leaves. In a controlled environment biological age may replace physical age. However, biological and physical age are not necessarily linearly convertible into each other. In stationary or steady state conditions the repetitive initiation of any organ, unit or module of an articulate plant or plant modular system may define the biological time unit. A linear — monotonous biological process, e.g. axis elongation, may also define a biological time unit as a certain amount of additional growth, e.g. of length. One may speak of periodical and of continuous plastochron or, perhaps, of plastochron and rheochron. A precise measure of biological age is the generalized plastochron index applying to any modular system and module respectively. However, one should be aware that it is based on two clocks, one of them referring to the periodic process of module initiation for counting the integer plastochrons and the other to the continuous plastochron of module growth for the determination of the fraction of one plastochron. The application of the concepts is restricted to phases of stationary or steady state growth and development. In certain cases of non-stationary or non-steady state conditions a normalized-age concept may apply. (shrink)

According to the so-called Quantum Darwinist approach, the emergence of “classical islands” from a quantum background is assumed to obey a principle of maximal information. We illustrate this idea by considering the coupling of two oscillators. As our approach suggests that the classical limit could have emerged throughout a long and progressive Evolution mechanism, it is likely that primitive living organisms behave in a “more quantum”, “less classical” way than more evolved ones. This brings us to seriously consider the possibility (...) to measure departures from classicality exhibited by biological systems. We describe an experimental proposal the aimed at revealing the presence of entanglement in the biophotonic radiation emitted by biological sources. (shrink)

Habituation, a form of non‐associative learning, isno longer studied exclusively within the fields of psychology and neuroscience. Indeed, the same stimulus–response pattern is observed at the molecular, cellular, and organismal scales and is not dependent upon the presence of neurons. Hence, a more inclusive theory is required to accommodate aneural forms of habituation. Here an abstraction of the habituation process that does not rely upon particular biological pathways or substrates is presented. Instead, five generalizable elements that define the habituation (...) process are operationalized. The formulation can be applied to interrogate systems as they respond to several stimulation paradigms, providing new insights and supporting existing behavioral data. The model can be used to deduce the relative contribution of elements that contribute to the measurable output of the system. The results suggest that habituation serves as a general biological strategy that any system can implement to adaptively respond to harmless, repetitive stimuli. (shrink)

Progress has become a suspect concept in evolutionary biology, not the least because the core concepts of neo-Darwinism do not support the idea that evolution is progressive. There have been a number of attempts to account for directionality in evolution through additions to the core hypotheses of neo-Darwinism, but they do not establish progressiveness, and they are somewhat of an ad hoc collection. The standard account of fitness and adaptation can be rephrased in terms of information theory. From this, an (...) information of adaptation can be defined in terms of a fitness function. The information of adaptation is a measure of the mutual information between biota and their environment. If the actual state of adaptation lags behind the state of optimal adaptation, then it is possible for the information of adaptation to increase indefinitely. Since adaptations are functional, this suggests the possibility of progressive evolution in the sense of increasing adaptation. Keywords: evolution, information, adaptation, fitness, entropy, progress.. (shrink)

Modern integrative systems biology defines itself by the complexity of the problems it takes on through computational modeling and simulation. However in integrative systems biology computers do not solve problems alone. Problem solving depends as ever on human cognitive resources. Current philosophical accounts hint at their importance, but it remains to be understood what roles human cognition plays in computational modeling. In this paper we focus on practices through which modelers in systems biology use computational simulation and (...) other tools to handle the cognitive complexity of their modeling problems so as to be able to make significant contributions to understanding, intervening in, and controlling complex biological systems. We thus show how cognition, especially processes of simulative mental modeling, is implicated centrally in processes of model-building. At the same time we suggest how the representational choices of what to model in systems biology are limited or constrained as a result. Such constraints help us both understand and rationalize the restricted form that problem solving takes in the field and why its results do not always measure up to expectations. (shrink)

Antifragility is a property from which systems are able to resist stress and furthermore benefit from it. Even though antifragile dynamics is found in various real-world complex systems where multiple subsystems interact with each other, the attribute has not been quantitatively explored yet in those complex systems which can be regarded as multilayer networks. Here we study how the multilayer structure affects the antifragility of the whole system. By comparing single-layer and multilayer Boolean networks based on our (...) recently proposed antifragility measure, we found that the multilayer structure facilitated the production of antifragile systems. Our measure and findings will be useful for various applications such as exploring properties of biological systems with multilayer structures and creating more antifragile engineered systems. (shrink)

The properties of the phosphate uptake system of the cyanobacterium Anacystis nidulans have been studied during the transition from a phosphate-deficient non-growing state to a non-deficient growing state. In the phosphate-deficient state the high affinity phosphate transport system in the cell membrane is extremely adaptive. As a result of these adaptive features the phosphate transport system cannot be described by determinate, fixed parameters, because the transport system is influenced by the measurement of the uptake process itself. When the growing state (...) has been initiated by a persisting phosphate pulse, the transport system rapidly loses its adaptive features and can then be characterized by determinate parameters that remain unchanged for a long period of time, even if no uptake occurs in that time. Depending on the amount of phosphate stored during a pulse the cell makes a choice between slow or fast growth. In the latter case the light harvesting and energy converting machinery is completely reorganized before growth commences. Thereby the components of this machinery conform to each other and to the stable properties of the phosphate transport system. It is suggested that the mutual adjustment of these adaptive energy converting subunits is guided by attractors that function as the final cause for the development of the whole system.An application of this model to an analysis of the selforganization of aquatic ecosystems is discussed. (shrink)

A high profile context in which physics and biology meet today is in the new field of systems biology. Systems biology is a fascinating subject for sociological investigation because the demands of interdisciplinary collaboration have brought epistemological issues and debates front and centre in discussions amongst systems biologists in conference settings, in publications, and in laboratory coffee rooms. One could argue that systems biologists are conducting their own philosophy of science. This paper explores the epistemic aspirations (...) of the field by drawing on interviews with scientists working in systems biology, attendance at systems biology conferences and workshops, and visits to systems biology laboratories. It examines the discourses of systems biologists, looking at how they position their work in relation to previous types of biological inquiry, particularly molecular biology. For example, they raise the issue of reductionism to distinguish systems biology from molecular biology. This comparison with molecular biology leads to discussions about the goals and aspirations of systems biology, including epistemic commitments to quantification, rigor and predictability. Some systems biologists aspire to make biology more similar to physics and engineering by making living systems calculable, modelable and ultimately predictable—a research programme that is perhaps taken to its most extreme form in systems biology’s sister discipline: synthetic biology. Other systems biologists, however, do not think that the standards of the physical sciences are the standards by which we should measure the achievements of systems biology, and doubt whether such standards will ever be applicable to ‘dirty, unruly living systems’. This paper explores these epistemic tensions and reflects on their sociological dimensions and their consequences for future work in the life sciences. (shrink)

Bioscientists generate far more data than their minds can handle, and this trend is likely to continue. With the aid of a small set of versatile tools for mathematical modeling and statistical assessment, bioscientists can explore their real-world systems without experiencing data overflow. This article outlines an approach for combining modern high-throughput, low-cost, but non-selective biospectroscopy measurements with soft, multivariate biochemometrics data modeling to overview complex systems, test hypotheses, and making new discoveries. From preliminary, broad hypotheses and goals, (...) many relevant samples are selected and measured with respect to many informative variables. The resulting tables represent a “cacophony” of data. From these, the most relevant and reliable “underlying harmonies and rhythms” are extracted and tested statistically, displayed for interpretation, and used for prediction. Outliers are detected automatically. Interesting subsets of samples can then be chosen for in-depth analyses in subsequent research cycles. This pragmatic, top-down approach takes advantage of developments in both “soft,” data-driven modeling and “hard,” knowledge-driven cultures. Data analytical examples show how information-rich biospectroscopy can be used for characterizing and quantifying known and unknown chemical constituents and physical phenomena in intact biosamples. This is based on a combination of deductive “hard” and inductive “soft” modeling. The examples represent NIR spectra of biochemical mixtures, FTIR spectra of a microbiological fermentation process, and FTIR analysis of fatty acids in milk for functional genomics. (shrink)

The progress of the molecular biosciences has been so enormous that a discipline studying how cellular functioning emerges out of the behaviors of their molecular constituents has become reality. Systems biology studies cells as spatiotemporal networks of interacting molecules using an integrative approach of theory , experimental biology , and quantitative network-wide analytical measurement . Its aim is to understand how molecules jointly bring about life. Systems biology is rapidly discovering principles governing the functioning of molecular networks and (...) methods to model and measure them. The application of the conceptual strength of systems sciences such as physics and engineering are opening up new ways of experimentally studying the design and functioning of molecular networks. Typically, in such studies models are used to highlight principles, design experiments, or to act in a predictive mode to specifically modify cellular behavior. In this trend article, theoretical approaches being applied in systems biology will be discussed. A number of books have recently appeared that deal with theoretical aspects of systems biology. In this article they are highlighted to facilitate the communication of systems biology to a broader audience. (shrink)

In this paper, I discuss how information theory has been used in the study of animal communication, as well as how these uses are justified. Biologists justify their use of Shannon’s information measures by the work they do in allowing for comparisons between different organisms and because they measure a quantity that is purported to be important for natural selection. I argue that there are problems with both sorts of justification. To make these difficulties clear, I focus on the use (...) of Shannon’s information measures to quantify the amount of information transmitted by the fire ant’s odor trail and the honeybee’s waggle dance. Both of these systems are relatively simple and well understood, and the application of Shannon’s information measure to these systems initially seemed very promising and relatively straightforward. They are therefore particularly suitable for revealing the benefits and difficulties of applying Shannon’s information measures to biological systems in general, and animal communication systems in particular. (shrink)

The foundations of systematics lie in ontology, not in subjective epistemology. Systems and their elements should be distinguished from classes; only the latter are constructed from similarities. The term classification should be restricted to ordering into classes; ordering according to systematic relations may be called systematization.The theory of organization levels portrays the real world as a hierarchy of open systems, from energy quanta to ecosystems; followingHartmann these systems as extended in time are considered the primary units of (...) reality. Organization levels should be distinguished from levels of differentiation within each organization level.Certain biological systems, such as species, continue to be misinterpreted as classes, particularly by logicians unfamiliar with modern biological theory. Replacement of Aristotelian definitions of species by “polytypic” definitions achieves nothing, because species are individual systems which can be defined from an ontological viewpoint only as wholes. The dispute whether classes are real per se or only in individuals is of no scientific importance; irrespective of which view is taken, any ordering of physical objects into classes constitutes an hypothesis about the structure of the real world.The distinction between essential and contingent characters is relevant only to classification. There are no universal rules for evaluating characters for purposes of systematization. Character statements do not form separate linear sequences. The search for “unit characters” in an absolute sense is futile. All real characters are reducible to relations and are in principle measurable, although there are limitations on the extent to which this can be presently achieved.The concept of the sexual species is fundamental to theories of biosystematics. Sexual species may be defined as lineages consisting at any given time of series of populations between which genetic exchange can occur and delimited in time by two successive processes of speciation. Linnaean nomenclature needs modification; in its traditional form it is appropriate only to non-truncated hierarchies, whereas real phylogenies form truncated hierarchies. In consequence of the distinction between systematization and classification it is concluded that, while taxa may be classified into age classes or evolutionary grades, their limits as taxa can be no different in either case. Classification into evolutionary grades remains an imprecise endeavour, since no general measure of evolutionary differentiation has been devised.The spatial and temporal extent of ecosystems, the postulated basic units of ecosystematics, remains unclarified. Nevertheless there are grounds for expecting progress in this field as the energetic relations between organisms become better understood. Biotic communities are not “abstract” classes, but systematic units. Physiognomic classification should not be confused with systematization of plant communities; both approaches contribute to an understanding of vegetational structure. (shrink)

A conflict between evidence for causation and the metaphysical requirement of spatiotemporal distinct causal relata arises if the results of experiments commonly described as ‘bottom-up’ and ‘top-down’ are taken to demonstrate ontological determination dependencies between parts and wholes or their respective behaviours. It has been argued that the problem can be circumvented if experimental results are interpreted in terms of relationships between variables measured and manipulated at separating scales. I argue that scale separation fails in the case of biological (...) phenomena due to the small number of molecules and molecular events underlying these phenomena, which makes it impossible to completely disentangle micro and macro-scale behaviours. I defend instead a causal mediation interpretation according to which experiments assess the effects of interventions targeting the composition and exposure of biological systems. Under this interpretation, causal relata are ontologically distinct fractions or parts of biological systems, thus avoiding the oddity of part-whole causation. (shrink)

This paper proposes that an organism's integrated repertoire of operant behavior has the status of a biological system, similar to other biological systems, like the nervous, cardiovascular, or immune systems. Evidence from a number of sources indicates that the distinctions between biological and behavioral events is often misleading, engendering counterproductive explanatory controversy. A good deal of what is viewed as biological (often thought to be inaccessible or hypothetical) can become publicly measurable variables using currently (...) available and developing technologies. Moreover, such endogenous variables can serve as establishing operations, discriminative stimuli, conjoint mediating events, and maintaining consequences within a functional analysis of behavior and need not lead to reductionistic explanation. I suggest that explanatory misunderstandings often arise from conflating different levels of analysis and that behavior analysis can extend its reach by identifying variables operating within a functional analysis that also serve functions in other biological systems. (shrink)

Ioannidis [Why most published research findings are false. PLoS Med 2: e124 ] identifies six factors that contribute to explaining why most of the current published research findings are more likely to be false than true, and argues that for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this article, we argue that three “hot” areas in current biological research, viz., agent-based modeling, evolutionary developmental biology, and systems biology, (...) are especially prone to the flaws. (shrink)

Traction forces developed by most cell types play a significant role in the spatial organisation of biological tissues. However, due to the complexity of cell-extracellular matrix interactions, these forces are quantitatively difficult to estimate without explicitly considering cell properties and extracellular mechanical matrix responses. Recent experimental devices elaborated for measuring cell traction on extracellular matrix use cell deposits on a piece of gel placed between one fixed and one moving holder. We formulate here a mathematical model describing the dynamic (...) behaviour of the cell-gel medium in such devices. This model is based on a mechanical force balance quantification of the gel visco-elastic response to the traction forces exerted by the diffusing cells. Thus, we theoretically analyzed and simulated the displacement of the free moving boundary of the system under various conditions for cells and gel concentrations. This modelis then used as the theoretical basis of an experimental device where endothelial cells are seeded on a rectangular biogel of fibrin cast between two floating holders, one fixed and the other linked to a force sensor. From a comparison of displacement of the gel moving boundary simulated by the model and the experimental data recorded from the moving holder displacement, the magnitude of the traction forces exerted by the endothelial cell on the fibrin gel was estimated for different experimental situations. Different analytical expressions for the cell traction term are proposed and the corresponding force quantifications are compared to the traction force measurements reported for various kind of cells with the use of similar or different experimental devices. (shrink)

This book discusses the basic foundations of theoretical biology. Contrary to the objects of theoretical physics, the biological object contains a kind of ontological duality and refers to a fundamental wholeness of a living system. The rational interpretation of wholeness is considered by the author as a true basis for fundamental principles of development of theoretical biology and for understanding its link to physics, to psychology, and to semiotics. The rational holistic approach in application to theoretical biology can be (...) substantiated through the clarification of internal logic of organization and description of biological systems. This logic will provide an understanding of the place of life in the Universe. The main goal of this book is to introduce the view that in the potentially infinite system of human knowledge, a proper clarification of the place of Man in the Universe is possible only via understanding of the phenomenon of life. (Imprint: Nova Biomedical). (shrink)

Intelligence in current AI research is measured according to designer-assigned tasks that lack any relevance for an agent itself. As such, tasks and their evaluation reveal a lot more about our intelligence than the possible intelligence of agents that we design and evaluate. As a possible first step in remedying this, this article introduces the notion of “self-concern,” a property of a complex system that describes its tendency to bring about states that are compatible with its continued self-maintenance. Self-concern, as (...) argued, is the foundation of the kind of basic intelligence found across all biological systems, because it reflects any such system's existential task of continued viability. This article aims to cautiously progress a few steps closer to a better understanding of some necessary organisational conditions that are central to self-concern in biological systems. By emulating these conditions in embodied AI, perhaps something like genuine self-concern can be implemented in machines, bringing AI one step closer to its original goal of emulating human-like intelligence. (shrink)

Summary Prägnanz was suggested by Max Wertheimer in the 1920s as subsuming all “Laws of Gestalt” as they apply to visual awareness. Thus, it assumes a prominent position in any account of Gestalt phenomena. From a phenomenological perspective, some visual stimuli evidently “have more Prägnanz” than others, so Prägnanz seems to be an intensive quality. Here, we investigate the intricacies that need to be faced on the way to a definition of formal scales. Such measures naturally depend both upon the (...) stimulus and upon the observer. Structural complexity bottlenecks of visual systems play a role, as well as the relevance to biological fitness, that is the affinity to the optical user interface. This positions the notion of Prägnanz squarely within the realm of biology. Indeed, the familiar “releasers” of ethology are singular cases of extremely high Prägnanz. (shrink)

Creativity is commonly thought of as a positive advance for society that transcends the status quo knowledge. Humans display an inordinate capacity for it in a broad range of activities, with art being only one. Most work on creativity’s neural substrates measures general creativity, and that is done with laboratory tasks, whereas specific creativity in art is gleaned from acquired brain damage, largely in observing established visual artists, and some in visual de novo artists (became artists after the damage). The (...) verb “to create” has been erroneously equated with creativity; creativity, in the classic sense, does not appear to be enhanced following brain damage, regardless of etiology. The turning to communication through art in lieu of language deficits reflects a biological survival strategy. Creativity in art, and in other domains, is most likely dependent on intact and healthy knowledge and semantic conceptual systems, which are represented in several pathways in the cortex. It is adversely affected when these systems are dysfunctional, for congenital reasons (savant autism) or because of acquired brain damage (stroke, dementia, Parkinson’s), whereas inherent artistic talent and skill appear less affected. Clues to the neural substrates of general creativity and specific art creativity can be gleaned from considering that art is produced spontaneously mainly by humans, that there are unique neuroanatomical and neurofunctional organizations in the human brain, and that there are biological antecedents of innovation in animals. (shrink)

Behavioral immune system describes psychological mechanisms that detect cues to infectious pathogens in the immediate environment, trigger disease-relevant responses and facilitate behavioral avoidance/escape. BIS activation elicits a perceived vulnerability to disease which can result in conformity with social norms. However, a response to superficial cues can result in aversive responses to people that pose no actual threat, leading to an aversion to unfamiliar others, and likelihood of prejudice. Pathogen-neutralizing behaviors, therefore, have implications for social interaction as well as illness behaviors (...) and responses to health communications. In this study, we investigate how PVD influences conformity, attitudes to other people and to lockdown regulations through the lens of the Reinforcement Sensitivity Theory. RST describes personality in terms of biologically-driven approach and avoidance motivations which support personal goals. Participants from the United Kingdom public completed an RST personality questionnaire and then read either coronavirus morbidity-mortality statistics and current United Kingdom government lifestyle regulations, just the regulations, or no information at all. They all completed the Perceived Vulnerability to Disease scale to assess BIS-relevant Germ Aversion and Perceived Infectability, followed by questions measuring social conformity, warmth toward others and attitudes toward lockdown measures. Significantly lower PVD scores were observed in the no-information condition, with the other conditions showing no difference. In terms of RST, approach behaviors related to goal-drive persistence work alongside fear in explaining conformity to social norms. Reward related approach behaviors partially explained warmth toward others, indicating that social rewards gained through interaction continue to be strong drivers of behavior. We found no role for RST traits in attitudes toward lockdown. Overall, coronavirus-related behavior is not driven purely by fear, but also by social and/or protection goals regulated by approach motivation. This study presents new insights into public perceptions of coronavirus and government regulated lifestyle restrictions, helping to explain social behaviors in terms of biologically driven mechanisms. Such understanding is vital if we are to successfully motivate public behavior to constrain spread of the virus. (shrink)

Before September 11, 2001, a mass-casualty terrorist attack on American soil was generally considered a remote possibility. Similarly, before October 4, 2001—the first confirmed case of anthrax caused by intentional release — widespread bioterrorism seemed implausible. Among the arguments that such a biological artack was unlikely included: the lack of a historical precedent; the technological and organizational challenges to acquiring and weaponizing a biological agent; and the almost universal moral opprobrium that would certainly accompany the use by terrorists (...) of such a weapon. In the wake of September 11th and October 4th, however, many are reconsidering the likelihood of a large-scale bioterrorist attack against civilians.The Centers for Disease Control and Prevention defines bioterrorism as the intentional release of viruses, bacteria, or toxins for the purpose of harming or killing civilian. One measurement of the public health system's level of bioterrorism preparedness is the quality and distribution of laws mandating the reporting of diseases caused by certain biological agents. (shrink)

In addition to its obvious successes within the kinetic theory the ideal gas law and the modeling assumptions associated with it have been used to treat phenomena in domains as diverse as economics and biology. One reason for this is that it is useful to model these systems using aggregates and statistical relationships. The issue I deal with here is the way R. A. Fisher used the model of an ideal gas as a methodological device for examining the causal (...) role of selection in producing variation in Mendelian populations. The model enabled him to create the kind of population where one could measure the effects of selection in a way that could not be done empirically. Consequently we are able to see how the model of an ideal gas was transformed into a biological model that functioned as an instrument for both investigating nature and developing a new theory of genetics. (shrink)

We consider how to discern whether or not evolution is taking place in an observed system. Evolution will be characterized in terms of a particular macroscopic behavior that emerges from microscopic organismic interaction. We de ne evolutionary activity as the rate at which useful genetic innovations are absorbed into the population. After measuring evolutionary activity in a simple model biosphere, we discuss applications to other systems. We argue that evolutionary activity provides an objective, quantitative interpretation of the intuitive idea (...) of biological teleology. We also propose using evolutionary activity in a test for life. (shrink)

A conflict between evidence for causation and the metaphysical requirement of spatiotemporal distinct causal relata arises if the results of experiments commonly described as ‘bottom-up’ and ‘top-down’ are taken to demonstrate ontological determination dependencies between parts and wholes or their respective behaviours. It has been argued that the problem can be circumvented if experimental results are interpreted in terms of relationships between variables measured and manipulated at separating scales. I argue that scale separation fails in the case of biological (...) phenomena due to the small number of molecules and molecular events underlying these phenomena, which makes it impossible to completely disentangle micro and macro-scale behaviours. I defend instead a causal mediation interpretation according to which experiments assess the effects of interventions targeting the composition and exposure of biological systems. Under this interpretation, causal relata are ontologically distinct fractions or parts of biological systems, thus avoiding the oddity of part-whole causation. (shrink)

The emerging concept of systems medicine (or ‘P4 medicine’—predictive, preventive, personalized and participatory) is at the vanguard of the post-genomic movement towards ‘precision medicine’. It is the medical application of systems biology, the biological study of wholes. Of particular interest, P4 systems medicine is currently promised as a revolutionary new biomedical approach that is holistic rather than reductionist. This article analyzes its concept of holism, both with regard to methods and conceptualization of health and disease. Rather (...) than representing a medical holism associated with basic humanistic ideas, we find a technoscientific holism resulting from altered technological and theoretical circumstances in biology. We argue that this holism, which is aimed at disease prevention and health optimization, points towards an expanded form of medicalization, which we call ‘holistic medicalization’: Each person’s whole life process is defined in biomedical, technoscientific terms as quantifiable and controllable and underlain a regime of medical control that is holistic in that it is all-encompassing. It is directed at all levels of functioning, from the molecular to the social, continual throughout life and aimed at managing the whole continuum from cure of disease to optimization of health. We argue that this medicalization is a very concrete materialization of a broader trend in medicine and society, which we call ‘the medicalization of health and life itself’. We explicate this holistic medicalization, discuss potential harms and conclude by calling for preventive measures aimed at avoiding eventual harmful effects of overmedicalization in systems medicine (quaternary prevention). (shrink)

Recent advances in AI raise the possibility that AI systems will one day be able to do anything humans can do, only better. If artificial general intelligence (AGI) is achieved, AI systems may be able to understand, reason, problem solve, create, and evolve at a level and speed that humans will increasingly be unable to match, or even understand. These possibilities raise a natural question as to whether AI will eventually become superior to humans, a successor “digital species”, (...) with a rightful claim to assume leadership of the universe. However, a deeper consideration suggests the overlooked differentiator between human beings and AI is not the brain, but the central nervous system (CNS), providing us with an immersive integration with physical reality. It is our CNS that enables us to experience emotion including pain, joy, suffering, and love, and therefore to fully appreciate the consequences of our actions on the world around us. And that emotional understanding of the consequences of our actions is what is required to be able to develop sustainable ethical systems, and so be fully qualified to be the leaders of the universe. A CNS cannot be manufactured or simulated; it must be grown as a biological construct. And so, even the development of consciousness will not be sufficient to make AI systems superior to humans. AI systems may become more capable than humans on almost every measure and transform our society. However, the best foundation for leadership of our universe will always be DNA, not silicon. (shrink)

The INBIOSA project brings together a group of experts across many disciplines who believe that science requires a revolutionary transformative step in order to address many of the vexing challenges presented by the world. It is INBIOSA’s purpose to enable the focused collaboration of an interdisciplinary community of original thinkers. This paper sets out the case for support for this effort. The focus of the transformative research program proposal is biology-centric. We admit that biology to date has been more fact-oriented (...) and less theoretical than physics. However, the key leverageable idea is that careful extension of the science of living systems can be more effectively applied to some of our most vexing modern problems than the prevailing scheme, derived from abstractions in physics. While these have some universal application and demonstrate computational advantages, they are not theoretically mandated for the living. A new set of mathematical abstractions derived from biology can now be similarly extended. This is made possible by leveraging new formal tools to understand abstraction and enable computability. [The latter has a much expanded meaning in our context from the one known and used in computer science and biology today, that is "by rote algorithmic means", since it is not known if a living system is computable in this sense (Mossio et al., 2009).] Two major challenges constitute the effort. The first challenge is to design an original general system of abstractions within the biological domain. The initial issue is descriptive leading to the explanatory. There has not yet been a serious formal examination of the abstractions of the biological domain. What is used today is an amalgam; much is inherited from physics (via the bridging abstractions of chemistry) and there are many new abstractions from advances in mathematics (incentivized by the need for more capable computational analyses). Interspersed are abstractions, concepts and underlying assumptions “native” to biology and distinct from the mechanical language of physics and computation as we know them. A pressing agenda should be to single out the most concrete and at the same time the most fundamental process-units in biology and to recruit them into the descriptive domain. Therefore, the first challenge is to build a coherent formal system of abstractions and operations that is truly native to living systems. Nothing will be thrown away, but many common methods will be philosophically recast, just as in physics relativity subsumed and reinterpreted Newtonian mechanics. -/- This step is required because we need a comprehensible, formal system to apply in many domains. Emphasis should be placed on the distinction between multi-perspective analysis and synthesis and on what could be the basic terms or tools needed. The second challenge is relatively simple: the actual application of this set of biology-centric ways and means to cross-disciplinary problems. In its early stages, this will seem to be a “new science”. This White Paper sets out the case of continuing support of Information and Communication Technology (ICT) for transformative research in biology and information processing centered on paradigm changes in the epistemological, ontological, mathematical and computational bases of the science of living systems. Today, curiously, living systems cannot be said to be anything more than dissipative structures organized internally by genetic information. There is not anything substantially different from abiotic systems other than the empirical nature of their robustness. We believe that there are other new and unique properties and patterns comprehensible at this bio-logical level. The report lays out a fundamental set of approaches to articulate these properties and patterns, and is composed as follows. -/- Sections 1 through 4 (preamble, introduction, motivation and major biomathematical problems) are incipient. Section 5 describes the issues affecting Integral Biomathics and Section 6 -- the aspects of the Grand Challenge we face with this project. Section 7 contemplates the effort to formalize a General Theory of Living Systems (GTLS) from what we have today. The goal is to have a formal system, equivalent to that which exists in the physics community. Here we define how to perceive the role of time in biology. Section 8 describes the initial efforts to apply this general theory of living systems in many domains, with special emphasis on crossdisciplinary problems and multiple domains spanning both “hard” and “soft” sciences. The expected result is a coherent collection of integrated mathematical techniques. Section 9 discusses the first two test cases, project proposals, of our approach. They are designed to demonstrate the ability of our approach to address “wicked problems” which span across physics, chemistry, biology, societies and societal dynamics. The solutions require integrated measurable results at multiple levels known as “grand challenges” to existing methods. Finally, Section 10 adheres to an appeal for action, advocating the necessity for further long-term support of the INBIOSA program. -/- The report is concluded with preliminary non-exclusive list of challenging research themes to address, as well as required administrative actions. The efforts described in the ten sections of this White Paper will proceed concurrently. Collectively, they describe a program that can be managed and measured as it progresses. (shrink)

Historically, views and measurements of biodiversity have had a narrow focus, for instance, characterizing the attributes of observable patterns but affording less attention to processes. Here, we explore the question: how does a systems thinking view – one where the world is seen as elements and processes that connect and interact in dynamic ways to form a whole – affect the way we understand biodiversity and practice conservation? We answer this question by illustrating the systemic properties of biodiversity at (...) multiple levels, and show that biodiversity is a collection of dynamic systems linking seemingly disparate biological and cultural components and requiring an understanding of the system as a whole. We conclude that systems thinking calls traditional views of species, ecosystem function, and human relationships with the rest of biodiversity into question. Finally, we suggest some of the ways in which this view can impact the science and practice of conservation, particularly through affecting our conservation targets and strategies. (shrink)

A similarity index allowing comparisons of human populations has been defined as the common “Percentage of Isoactive Genes” or PIG, which can be calculated from any gene frequency distribution characterizing two populations. The complement to one of this value has been proved to be a distance, a measure which can be used in most techniques of cluster analysis as well as in usual representations of multivariated data (dendrograms, etc...). Furthermore, the formula can be generalized to a set of populations. From (...) a biological point of vue, PIG values are particularly meaningful, whereas other previously defined indices which tend to measure similarity or difference between populations neither have such an advantage, nor can they be expressed by a single and clear number like a percentage. Moreover,comparisons using PIG indices depend at first on the fluctuations of the most frequent genes of a distribution; on the other hand, different measures principally reflect the variations of low frequency genes, which unfortunately are nearly always poorly estimated, due to weak samples of populations.Interestingly, PIG values can be applied to any frequency distribution of any kind of objects. They can also extend to a whole set of distributions by using a mean value. When applying these measures to a series of polymorphic genetical systems such as ABO, Rhesus, MNSs, Gm and HLA, one can account for the variability or the homogeneity particular to the different human groups, with simple and objective criteria. (shrink)

To study how expertise impacts the understanding of a complex system like the vineyard, three measures were used with 259 participants (190 non-experts, 34 winemakers and/or winegrowers, and 35 biologists): a questionnaire to check for expertise (the Plant Biology Questionnaire), a task about the Structure, Behaviour and Function model, and a measure of the content of the participants? discourse with the ALCESTE software. Results showed that biologists mentioned functions significantly more often than behaviours, whereas it was the opposite for winegrowers. (...) Non-experts mentioned functions and behaviours significantly less frequently than experts did. The content analysis confirmed the differential expression of each kind of expertise: scientific wording for biologists, technical wording for winegrowers, and words focused on perceptible structures for the non-experts. Results from all tasks were highly correlated and allowed for an interpretation of expertise in terms of mental models of the vineyard. (shrink)

In this paper we explore the rise of ‘the breast cancer gene’ as a field of medical, cultural and personal knowledge. We address its significance in the Norwegian public health care system in relation to so-called biological citizenship in this particular national context. One of our main findings is that, despite its claims as a measure for health and disease prevention, gaining access to medical knowledge of BRCA 1/2 breast cancer gene mutations can also produce severe instability in the (...) individuals and families affected. That is, although gene testing provides modern subjects with an opportunity to foresee their biological destiny and thereby become patients in waiting, it undoubtedly also comes with difficult existential dilemmas and choices, with implications that resonate beyond the individual and into different family and love relations. By elaborating on this finding we address the question of whether the empowerment slogan, which continues to be advocated through various health, BRCA and breast cancer discourses, reinforces a naïve or an idealized notion of the actively responsible patient: resourceful enough to seek out medical expertise and gain sufficient knowledge, on which to base informed decisions, thereby reducing the future risk of developing disease. In contrast to this ideal, our Norwegian informants tell a different story, in which there is no apparent heroic mastery of genetic fates, but rather a pragmatic attitude to dealing with a dire situation over which they have little control, despite having complied with medical advice through national guidelines and follow-up procedures for BRCA 1/2 carriers. In conclusion we claim that the sense of safety that gene testing and its associated medical solutions allegedly promise to provide proved illusory. Although BRCA-testing offers the potential for protection from adverse DNA-heritage, administered through possibilities for self-monitoring and self-management of the body, the feeling of ‘being in good health’ has hardly been reinforced by the emergence of gene technology. (shrink)

How much does stimulus input shape perception? The common-sense view is that our perceptions are representations of objects and their features and that the stimulus structures the perceptual object. The problem for this view concerns perceptual biases as responsible for distortions and the subjectivity of perceptual experience. These biases are increasingly studied as constitutive factors of brain processes in recent neuroscience. In neural network models the brain is said to cope with the plethora of sensory information by predicting stimulus regularities (...) on the basis of previous experiences. Drawing on this development, this chapter analyses perceptions as processes. Looking at olfaction as a model system, it argues for the need to abandon a stimulus-centred perspective, where smells are thought of as stable percepts, computationally linked to external objects such as odorous molecules. Perception here is presented as a measure of changing signal ratios in an environment informed by expectancy effects from top-down processes. (shrink)

Many studies have shown that about three biological motions can be maintained in working memory. However, no study has yet analyzed the difficulties of experiment materials used, which partially affect the ecological validity of the experiment results. We use the perspective of system anatomy to decompose BM, and thoroughly explore the influencing factors of difficulties of BMs, including presentation duration, joints to execute motions, limbs to execute motions, type of articulation interference tasks, and number of joints and planes involved (...) in the BM. We apply the change detection paradigm supplemented by the articulation interference task to measure the BM working memory capacity of participants. Findings show the following: the shorter the presentation duration, the less participants remembered; the more their wrist moved, the less accurate their memory was; repeating verbs provided better results than did repeating numerals to suppress verbal encoding; the more complex the BM, the less participants remembered; and whether the action was executed by the handed limbs did not affect the WMC. These results indicate that there are many factors that can be used to adjust BM memory load. These factors can help sports psychology professionals to better evaluate the difficulty of BMs, and can also partially explain the differences in estimations of BM WMC in previous studies. (shrink)

The unprecedented prowess of measurement techniques provides a detailed, multi‐scale look into the depths of living systems. Understanding these avalanches of high‐dimensional data—by distilling underlying principles and mechanisms—necessitates dimensional reduction. We propose that living systems achieve exquisite dimensional reduction, originating from their capacity to learn, through evolution and phenotypic plasticity, the relevant aspects of a non‐random, smooth physical reality. We explain how geometric insights by mathematicians allow one to identify these genuine hallmarks of life and distinguish them from (...) universal properties of generic data sets. We illustrate these principles in a concrete example of protein evolution, suggesting a simple general recipe that can be applied to understand other biological systems. (shrink)

To study the interaction of forces that produce chest wall motion, we propose a model based on the lever system of Hillman and Finucane :951–961, 1987) and introduce some dynamic properties of the respiratory system. The passive elements are considered as elastic compartments linked to the open air via a resistive tube, an image of airways. The respiratory muscles force is applied to both compartments. Parameters of the model are identified in using experimental data of airflow signal measured by pneumotachography (...) and rib cage and abdomen signals measured by respiratory inductive plethysmography on eleven healthy volunteers in five conditions: at rest and with four level of added loads. A breath by breath analysis showed, whatever the individual and the condition are, that there are several breaths on which the airflow simulated by our model is well fitted to the airflow measured by pneumotachography as estimated by a determination coefficient R2 ≥ 0.70. This very simple model may well represent the behaviour of the chest wall and thus may be useful to interpret the relative motion of rib cage and abdomen during quiet breathing. (shrink)

The necessary but not sufficient conditions for biological informational concepts like signs, symbols, memories, instructions, and messages are (1) an object or referent that the information is about, (2) a physical embodiment or vehicle that stands for what the information is about (the object), and (3) an interpreter or agent that separates the referent information from the vehicle’s material structure, and that establishes the stands-for relation. This separation is named the epistemic cut, and explaining clearly how the stands-for relation (...) is realized is named the symbol-matter problem. (4) A necessary physical condition is that all informational vehicles are material boundary conditions or constraints acting on the lawful dynamics of local systems. It is useful to define a dependency hierarchy of information types: (1) syntactic information (i.e., communication theory), (2) heritable information acquired by variation and natural selection, (3) non-heritable learned or creative information, and (4) measured physical information in the context of natural laws. High information storage capacity is most reliably implemented by discrete linear sequences of non-dynamic vehicles, while the execution of information for control and construction is a non-holonomic dynamic process. The first epistemic cut occurs in self-replication. The first interpretation of base sequence information is by protein folding; the last interpretation of base sequence information is by natural selection. Evolution has evolved senses and nervous systems that acquire non-heritable information, and only very recently after billions of years, the competence for human language. Genetic and human languages are the only known complete general purpose languages. They have fundamental properties in common, but are entirely different in their acquisition, storage and interpretation. (shrink)

The INBIOSA project brings together a group of experts across many disciplines who believe that science requires a revolutionary transformative step in order to address many of the vexing challenges presented by the world. It is INBIOSA’s purpose to enable the focused collaboration of an interdisciplinary community of original thinkers. This paper sets out the case for support for this effort. The focus of the transformative research program proposal is biology-centric. We admit that biology to date has been more fact-oriented (...) and less theoretical than physics. However, the key leverageable idea is that careful extension of the science of living systems can be more effectively applied to some of our most vexing modern problems than the prevailing scheme, derived from abstractions in physics. While these have some universal application and demonstrate computational advantages, they are not theoretically mandated for the living. A new set of mathematical abstractions derived from biology can now be similarly extended. This is made possible by leveraging new formal tools to understand abstraction and enable computability. [The latter has a much expanded meaning in our context from the one known and used in computer science and biology today, that is "by rote algorithmic means", since it is not known if a living system is computable in this sense (Mossio et al., 2009).] Two major challenges constitute the effort. The first challenge is to design an original general system of abstractions within the biological domain. The initial issue is descriptive leading to the explanatory. There has not yet been a serious formal examination of the abstractions of the biological domain. What is used today is an amalgam; much is inherited from physics (via the bridging abstractions of chemistry) and there are many new abstractions from advances in mathematics (incentivized by the need for more capable computational analyses). Interspersed are abstractions, concepts and underlying assumptions “native” to biology and distinct from the mechanical language of physics and computation as we know them. A pressing agenda should be to single out the most concrete and at the same time the most fundamental process-units in biology and to recruit them into the descriptive domain. Therefore, the first challenge is to build a coherent formal system of abstractions and operations that is truly native to living systems. Nothing will be thrown away, but many common methods will be philosophically recast, just as in physics relativity subsumed and reinterpreted Newtonian mechanics. -/- This step is required because we need a comprehensible, formal system to apply in many domains. Emphasis should be placed on the distinction between multi-perspective analysis and synthesis and on what could be the basic terms or tools needed. The second challenge is relatively simple: the actual application of this set of biology-centric ways and means to cross-disciplinary problems. In its early stages, this will seem to be a “new science”. This White Paper sets out the case of continuing support of Information and Communication Technology (ICT) for transformative research in biology and information processing centered on paradigm changes in the epistemological, ontological, mathematical and computational bases of the science of living systems. Today, curiously, living systems cannot be said to be anything more than dissipative structures organized internally by genetic information. There is not anything substantially different from abiotic systems other than the empirical nature of their robustness. We believe that there are other new and unique properties and patterns comprehensible at this bio-logical level. The report lays out a fundamental set of approaches to articulate these properties and patterns, and is composed as follows. -/- Sections 1 through 4 (preamble, introduction, motivation and major biomathematical problems) are incipient. Section 5 describes the issues affecting Integral Biomathics and Section 6 -- the aspects of the Grand Challenge we face with this project. Section 7 contemplates the effort to formalize a General Theory of Living Systems (GTLS) from what we have today. The goal is to have a formal system, equivalent to that which exists in the physics community. Here we define how to perceive the role of time in biology. Section 8 describes the initial efforts to apply this general theory of living systems in many domains, with special emphasis on crossdisciplinary problems and multiple domains spanning both “hard” and “soft” sciences. The expected result is a coherent collection of integrated mathematical techniques. Section 9 discusses the first two test cases, project proposals, of our approach. They are designed to demonstrate the ability of our approach to address “wicked problems” which span across physics, chemistry, biology, societies and societal dynamics. The solutions require integrated measurable results at multiple levels known as “grand challenges” to existing methods. Finally, Section 10 adheres to an appeal for action, advocating the necessity for further long-term support of the INBIOSA program. -/- The report is concluded with preliminary non-exclusive list of challenging research themes to address, as well as required administrative actions. The efforts described in the ten sections of this White Paper will proceed concurrently. Collectively, they describe a program that can be managed and measured as it progresses. (shrink)

My paper draws on examples from molecular biology, the details of which I have developed elsewhere (Rheinberger 1992, 1993, 1995, 1997). Here, I can give only a brief outline of my argument. Reduction of complexity is a prerequisite for experimental research. To make sense of the universe of living beings, the modern biologist is bound to divide his world into fragments in which parameters can be defined, quantities measured, qualities identified. Such is the nature of any "experimental system." Ontic complexity (...) has to be reduced in order to make experimental research possible. The complexity of the research object, however, is epistemically retained in the rich context of an experimental landscape, where the eruption of "volcanic systems" can change the scenery dramatically as the result of particular, unprecedented findings. (shrink)

Several authors have used the notion of causal specificity in order to defend non-parity about genetic causes (Waters 2007, Woodward 2010, Weber 2017, forthcoming). Non-parity in this context is the idea that DNA and some other biomolecules that are often described as information-bearers by biologists play a unique role in life processes, an idea that has been challenged by Developmental Systems Theory (e.g., Oyama 2000). Indeed, it has proven to be quite difficult to state clearly what the alleged special (...) role of genetic causes consists in. In this paper, I show that the set of biomolecules that are normally considered to be information-bearers (DNA, mRNA) can be shown to be the most specific causes of protein primary structure, provided that causal specificity is measured over a relevant space of biological possibilities, disregarding physical as well as logically possible states of the causal variables. (shrink)

Hierarchies occur widely in evolving self‐organizing ecological, biological, technological, and social networks, but detecting and comparing hierarchies is difficult. Here we present a metric and technique to quantitatively assess the extent to which self‐organizing directed networks exhibit a flow hierarchy. Flow hierarchy is a commonly observed but theoretically overlooked form of hierarchy in networks. We show that the ecological, neurobiological, economic, and information processing networks are generally more hierarchical than their comparable random networks. We further discovered that hierarchy degree (...) has increased over the course of the evolution of Linux kernels. Taken together, our results suggest that hierarchy is a central organizing feature of real‐world evolving networks, and the measurement of hierarchy opens the way to understand the structural regimes and evolutionary patterns of self‐organizing networks. Our measurement technique makes it possible to objectively compare hierarchies of different networks and of different evolutionary stages of a single network, and compare evolving patterns of different networks. It can be applied to various complex systems, which can be represented as directed networks. (shrink)

Moving beyond the retributive system requires clearing away some of the basic assumptions that form the foundation of that system: most importantly, the assumption of moral responsibility, which is held in place by deep and destructive belief in a just world. Efforts to justify moral responsibility typically appeal to some version of self-making, and that appeal is only plausible through limits on inquiry. Eliminating moral responsibility removes a major impediment to deeper inquiry and understanding of the biological, social, and (...) environmental causes of both vicious and virtuous behavior. The resources for moving beyond the moral responsibility are already being developed in social democratic corporatist cultures as well as in workplace management models that nurture commitment and reject blame and shame. Without moral responsibility we must face the unpleasant fact that although punishment is sometimes unavoidable it is always unjust. That unpleasant fact motivates difficult but beneficial changes that minimize both the extent and the severity of punitive measures. (shrink)

Throughout the biological and biomedical sciences there is a growing need for, prescriptive ‘minimum information’ (MI) checklists specifying the key information to include when reporting experimental results are beginning to find favor with experimentalists, analysts, publishers and funders alike. Such checklists aim to ensure that methods, data, analyses and results are described to a level sufficient to support the unambiguous interpretation, sophisticated search, reanalysis and experimental corroboration and reuse of data sets, facilitating the extraction of maximum value from data (...) sets them. However, such ‘minimum information’ MI checklists are usually developed independently by groups working within representatives of particular biologically- or technologically-delineated domains. Consequently, an overview of the full range of checklists can be difficult to establish without intensive searching, and even tracking thetheir individual evolution of single checklists may be a non-trivial exercise. Checklists are also inevitably partially redundant when measured one against another, and where they overlap is far from straightforward. Furthermore, conflicts in scope and arbitrary decisions on wording and sub-structuring make integration difficult. This presents inhibit their use in combination. Overall, these issues present significant difficulties for the users of checklists, especially those in areas such as systems biology, who routinely combine information from multiple biological domains and technology platforms. To address all of the above, we present MIBBI (Minimum Information for Biological and Biomedical Investigations); a web-based communal resource for such checklists, designed to act as a ‘one-stop shop’ for those exploring the range of extant checklist projects, and to foster collaborative, integrative development and ultimately promote gradual integration of checklists. (shrink)

Information about the environment is captured in human biological systems on a variety of interacting levels – in distributions of genes, linguistic particulars, concepts, methods, theories, preferences, and overt behaviors. I investigate some of the basic principles which govern such a hierarchy by constructing a comparatively simple three-level selection model of bee foraging preferences and behaviors. The information-theoretic notion of ''''mutual information'''' is employed as a measure of efficiency in tracking a changing environment, and its appropriateness in epistemological (...) applications is discussed at some length. In particular, information accumulated in mid-level preference distributions exhibits suggestive properties for the purposes of naturalistic epistemology. It also appears that the novelty of scientific objects and representations and the rapidity of scientific change relative to genetic change need present no obstacle to the use of such models in explanations of scientific progress and the reliability of scientific judgement. (shrink)

In many countries consumers have shown an increasing interest to the way in which food products are being produced. This study investigates Chinese consumers’ attitudes towards different pig production systems by means of a conjoint analysis. While there has been a range of studies on Western consumers’ attitudes to various forms of food production, little is known about the level of Chinese consumers’ attitudes. A cross-sectional survey was carried out with 472 participants in 6 Chinese cities. Results indicate that (...) Chinese consumers prefer industrial pig production systems, where traditional pig breeds are raised, over large-scale and small family farms. Farms with maximum attention to food safety, which furthermore can provide lean meat with consistent quality, are also preferred. Imported pig breeds and tasty but variable meat were rejected. A 3-cluster solution found that consumers from cluster 1 focus almost exclusively on the food safety aspect. Consumers from cluster 2 show weak overall attitudes to pig production systems in general. Cluster 3 stands out by being very positive about industrial, large-size farms and consistent quality. From a Chinese consumer’s perspective, the industrial approach seems to represent values such as achievement and evolution, as well as quality and safety, since pig production is moving away from low-cost, low-quality, and low-safety family-scale systems. A complex set of rural and environmental development, quality aspects, and food safety measures are challenges that must be met by the stakeholders of pig production systems in China. (shrink)

This paper contrasts and compares strategies of model-building in condensed matter physics and biology, with respect to their alleged unequal susceptibility to trade-offs between different theoretical desiderata. It challenges the view, often expressed in the philosophical literature on trade-offs in population biology, that the existence of systematic trade-offs is a feature that is specific to biological models, since unlike physics, biology studies evolved systems that exhibit considerable natural variability. By contrast, I argue that the development of ever more (...) sophisticated experimental, theoretical, and computational methods in physics is beginning to erode this contrast, since condensed matter physics is now in a position to measure, describe, model, and manipulate sample-specific features of individual systems – for example at the mesoscopic level – in a way that accounts for their contingency and heterogeneity. Model-building in certain areas of physics thus turns out to be more akin to modeling in biology than has been supposed and, indeed, has traditionally been the case. (shrink)

We advance an account that grounds cognition, specifically decision-making, in an activity all organisms as autonomous systems must perform to keep themselves viable—controlling their production mechanisms. Production mechanisms, as we characterize them, perform activities such as procuring resources from their environment, putting these resources to use to construct and repair the organism's body and moving through the environment. Given the variable nature of the environment and the continual degradation of the organism, these production mechanisms must be regulated by control (...) mechanisms that select when a production is required and how it should be carried out. To operate on production mechanisms, control mechanisms need to procure information through measurement processes and evaluate possible actions. They are making decisions. In all organisms, these decisions are made by multiple different control mechanisms that are organized not hierarchically but heterarchically. In many cases, they employ internal models of features of the environment with which the organism must deal. Cognition, in the form of decision-making, is thus fundamental to living systems which must control their production mechanisms. (shrink)

Background on probability and evolution -- Laying the foundation. Population-environment systems ; Causal probability and empirical practice ; Irrelevance of fitness as a causal property of token organisms ; Roles of environmental variation in selection -- Reconstructing evolution and chance. Populations in biological practice: Pragmatic yet real ; Real causation in pragmatic population-environment systems ; Fitness concepts in measurement and modeling ; Chance in population-environment systems ; The input measure problem for MM-CCS chance -- Conclusion.

The experience of the use of applied containerized biomedical software tools in cloud environment is summarized. The reproducibility of scientific computing in relation with modern technologies of scientific calculations is discussed. The main approaches to biomedical data preprocessing and integration in the framework of the intelligent analytical system are described. At the conditions of pandemic, the success of health care system depends significantly on the regular implementation of effective research tools and population monitoring. The earlier the risks of disease can (...) be identified, the more effective process of preventive measures or treatments can be. This publication is about the creation of a prototype for such a tool within the project «Development of methods, algorithms and intelligent analytical system for processing and analysis of heterogeneous clinical and biomedical data to improve the diagnosis of complex diseases», implementted by the V.M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, together with the United Institute of Informatics Problems, National Academy of Sciences of Belarus. The insurers, entering the market, can insure mostly low risks by facilitating more frequent changes of insurers by consumers and mixing the overall health insurance market. Socio-demographic variables can be risk adjusters. Since age and gender have a relatively small explanatory power, other socio-demographic variables were studied – marital status, retirement status, disability status, educational level, income level. Because insurers have an interest in beneficial diagnoses for their policyholders, they are also interested in the ability to interpret relevant information – upcoding: insurers can encourage their policyholders to consult with doctors more often to select as many diagnoses as possible. Many countries and health care systems use diagnostic information to determine the reimbursement to a service provider, revealing the necessary data. For processing and analysis of these data, software implementations of construction for classifiers, allocation of informative features, processing of heterogeneous medical and biological variables for carrying out scientific research in the field of clinical medicine are developed. The experience of the use of applied containerized biomedical software tools in cloud environment is summarized. The reproducibility of scientific computing in relation with modern technologies of scientific calculations is discussed. Particularly, attention is paid to containerization of biomedical applications, this permits to get reproducibility of the conditions in which the calculations took place, technologies of software pipelining of calculations, that allows to organize flow calculations, and technologies for parameterization of software environment, that allows to reproduce, if necessary, an identical computing environment. The main approaches to biomedical data preprocessing and integration in the framework of the intelligent analytical system are described. The experience of using the developed linear classifier, gained during its testing on artificial and real data, allows us to conclude about several advantages provided by the containerized form of the created application: it permits to provide access to real data located in cloud environment; it is possible to perform calculations to solve research problems on cloud resources both with the help of developed tools and with the help of cloud services; such a form of research organization makes numerical experiments reproducible, i.e. any other researcher can compare the results of their developments on specific data that have already been studied by others, in order to verify the conclusions and technical feasibility of new results; there exists a universal opportunity to use the developed tools on technical devices of various classes from a personal computer to powerful cluster. (shrink)