Bertalanffy’s so-called “general system theory” (GST) and cybernetics were and are often confused: this calls for clarification. In this article, Bertalanffy’s conceptions and ideas are compared with those developed in cybernetics in order to investigate the differences and convergences. Bertalanffy was concerned with first order cybernetics. Nonetheless, his perspectivist epistemology is also relevant with regard to developments in second order cybernetics, and the latter is therefore also considered to some extent. W. Ross Ashby’s important role as mediator between GST and cybernetics is analysed. The respective basic epistemological approaches, scientific approaches and inherent world views are discussed. We underline the complementarity of cybernetic and “organismic” trends in systems research within the unitary hermeneutical framework of “general systemology”. This paper follows two earlier publications  was formally established in 1956, the ASC was officially established in 1964. During the 1970s, both societies became closely associated, also having common conferences Hammond . W. RossBoth fields comprise various dimensions, namely epistemology, scientific, application, ideology and world view. In order to compare Bertalanffy’s approach with cybernetics, it is useful to provide a short introduction into the latter field. This is given in the next section. We then compare the epistemological approaches in general systemology and cybernetics. In the next step, we investigate their basic scientific concepts. Then, characteristics of the two fields are compared with regard to world view and ideology. Finally, we examine the connections between the two fields on other levels such as the institutional level.2. Broadly speaking, the modern “systems” movement has three roots. One was the demand for a “general theory of systems,” posed by myself shortly after the Second War; the second, cybernetics finding a powerful expression in Wiener’s book (1948); the third, the demands of engineering in complex production processes, man-machine systems, armament research and the like.  “that the chief mechanism of the central nervous system is one of negative feed-back”; and (2) “that the negative feed-back mechanism explains ‘purpose’ and ‘adaptive’ behavior” Wisdom , 5. Neveintegrated whole” .The universality of the negative feedback mechanism is illustrated by the examples of picking up a pencil or steering a boat. The act of picking up a pencil involves a feedback for the correction of the position of the fingers towards the pencil, making the distance ever smaller. A circular process from the nervous system to the muscles over “re-entering” the nervous system via the sense organs is proposed to be at work Wiener . And WieThe term purposeful is meant to denote that the act of behavior may be interpreted as directed to the attainment of a goal – i.e. to a final condition in which the behaving object reaches a definite correlation in time or in space with respect to another object or event.  and such without feedback .Note that the term “active” here means that the output energy for a certain behavioural phenomenon stems from within the object; “in passive behavior […] all the energy in the output can be traced to the immediate input”Ashby  sought tParts can, in general, be coupled in different ways to form a whole. The defining of the component parts does not determine the way of coupling. From this follows an important corollary. That a whole machine should be built of parts of given behavior is not sufficient to determine its behavior as a whole: only when the details of coupling are added does the whole’s behavior become determinate. Ashby , 53Ashby  derived Such complex systems cannot be treated as an interlaced set of more or less independent feedback circuits, but only as a whole. For understanding the general principles of dynamic systems, therefore, the concept of feedback is inadequate in itself. What is important is that complex systems, richly cross-connected internally, have complex behaviors, and that these behaviors can be goal-seeking in complex patterns. Ashby , 54Very similar to Bertalanffy, Ashby was interested in problems in which each part of a system affects the other.The concept of homeostasis as developed by Cannon cf.  influencIn cybernetics, the concept of a “black box” is often used, meaning something of which the internal organization is not known, and which can only be investigated by applying an input and analysing the behaviour via the output. Such a behaviouristic study procedure deals with the input and output of an object while making an abstraction of its inner organization  biases of some of its architects, or of some works usually related to its development. Those biases seriously impeded the chances of cybernetics to become a genuine transdisciplinary science, while implying ideological biases which were as pernicious as implicit  may reasonably make an infinity of different selections, there must first be given an observer (or experimenter); a ”. Ashby , 16Therefore, second order cyberneticists reject the attitude that observations are independent of the characteristics of the observer Umpleby .16 TheThe point of view taken here is that science (as represented by the observer’s discoveries) is not immediately concerned with discovering what the system “really” is, but with co-ordinating the various observers’ discoveries, each of which is only a portion, or an aspect, of the whole truth. Ashby , 107Furthermore, distinguishing between organism and environment is partly conceptual and hence arbitrary Ashby , 40. As Second order cybernetics deals with the observer and the observed as two systems interacting with each other. What this field looks at is the observer who is constructing a model of another system. In other words: “[S]econd-order cybernetics studies how observers construct models of other cybernetic systems” According to this view, reality is an interactive conception because observer and observed are a mutually dependent couple. Objectivity in the traditional sense, as Heinz von Foerster has remarked, is the cognitive version of the physiological blind spot: we do not see what we do not see. Objectivity is a subject’s delusion that observing can be done without him. Invoking objectivity is abrogating responsibility – hence its popularity.  correspondence or match, radical constructivism sees it as an adaptation in the functional sense. , and knowledge not a simple approximation to “truth” or “reality.” It is an interaction between knower and known, this dependent on a multiplicity of factors of a biological, psychological, cultural, linguistic, etc., nature. […] This leads to a “perspective” philosophy […].  left is certain invariants expressed in highly abstract conservation laws […] In its de-anthropomorphized form, science is a conceptual construct representing certain formal or structural relationships in an unknown X. , can already be found in Bertalanffy’s considerations on the categories of experience. Bertalanffy was clearly influenced by Konrad Lorenz in this respectIt follows that there is no fundamental contradiction between Bertalanffy’s (and Cassirer’s) perspectivism and the constructivism defended by second order cyberneticists. Both can be seen as research attitudes aiming at grasping invariants in the phenomenal world via a multiplicity of conceptual constructs (“models”). Both epistemological approaches are rooted in the history of philosophy with some common ancestors, such as Vico, Kant and Piaget. There is a thematic  continuity from general systemology to second order cybernetics. Emphasizing the observer is therefore not so much an essential extension  cybernetics also finds its parallel in general systemology. Klir’s comments on such a character of “systems science”, which can be understood here as the subfield of general systemology termed “basic theoretical systemology”, are crucial in this respect:In the framework of “basic theoretical systemology”, the systemologist is concerned with the structure of already elaborated or conceivable theoretical models of entities displaying complex behaviour; the equivalence classes are induced by the logical homologies between these models. As such, Klir’s work is clearly concerned with the model character of “systems”. But it is also concerned with self-reference insofar as he, as a systemologist, reflects upon scientific constructions in a meta-theoretical perspective.It suffices here to show that general systemology and (second order) cybernetics do not contradict each other with respect to general epistemological issues. In some details, differences can be shown, such as the emphasis on different issues or different methods to construct knowledge: recursive loops in cybernetics and multiple perspective views in general systemology. Investigating such differences would be a useful endeavour in order to avoid talking past each other and to possibly arrive at a commonly agreed epistemological framework.3.2. No substantial part of the universe is so simple that it can be grasped and controlled without abstraction. Abstraction consists in replacing the part of the universe under consideration by a model of similar but simpler structure. Models, formal or intellectual on the one hand, or material on the other, are thus a central necessity of scientific procedure.  it is but one of these models and, as recent developments show, neither exhaustive nor unique.  and dynamical system theory (interactions in a multivariable system) can be shown. We note that no scientific model is monopolistic; each may reproduce, more or less successfully, certain aspects of reality.  research.science of complex systems:allowed this method; for this method is often fundamentally impossible in the complex systems […] Until recently, science tended to evade the study of such systems, focusing its attention on those that were simple and, especially, reducible […] Science today is also taking the first steps towards studying “complexity” as a subject in its own right [… And] cybernetics offers the hope of providing effective methods for the study, and control, of systems that are intrinsically extremely complex.  aim at the same goal: finding laws of organic “wholeness” and teleology  The “inter-scientific character”, that is, the fact that cybernetics “embraces” different established academic disciplines. One should also note its transdisciplinarity, since Bertalanffy simultaneously pointed to the cyberneticians’ contention that “certain model conceptions are applicable in quite different fields”.(2) The “opposition, as against the analytical, cause-effect, stimulus-response, and two-variable scheme, of the concept of mutual interaction”.(3) The “statement that there seems to correspond to the principle of complementarity in physics […] a fundamental limitation in biology, namely, a complementarity between investigation of isolated processes and that of the organism-as-a-whole”.(4) The “emphasis laid upon the dynamic, instead of static, character of organic equilibria and the insight that the apparently solid organism is, in fact, a continuous flux” (cf. Wiener (5) The “overcoming of the ancient antithesis of structure and function”.  The “re-orientation in the concepts of time and energy”.  The “realization that, as against the timid belief that the inductive method leads to fundamental theories and laws, the progress in physics was and in biology may be, achieved by the way of bold theoretical constructions”.Bertalanffy was well aware of Wiener’s writings. Already in the early days of both developments, he enumerated seven major “parallelisms” between GST and cybernetics , and so forth, are but a rather restricted subclass of “general systems.”  of his second “organismic principle” (progressive hierarchization) to his first “organismic principle” (openness), was transposed by Bertalanffy at a meta-theoretical level in order to subordinate the cybernetic approach to his own (“organismic”) one. This transposition was based on the following argument:primary regulations are such as result from dynamic interaction within a unitary system and according to general system laws. Superimposed are those regulations which may be called secondary, and which are governed by fixed “machine-like” structures. They comprise all phenomena of feedback, homeostasis, and related regulative mechanisms. There is a simple reason for the primacy, in the organism, of dynamical as against structural order. In contrast to a machine which consists of lasting parts, all organic structures are maintained in a continuous process, in perpetual breaking down and regeneration. The only thing which is really permanent in the organism is the order of processes. Therefore, the ultimate reason of the pattern and order in the living system can be sought only in the laws of the process itself, not in pre-established and enduring structures. Ontogenetically as well as phylogenetically, we find a principle of progressive mechanization, creating those mechanisms and making the organism more efficient while at the same time limiting its regulability. Dynamic regulation appears to be the primordial and more general law. . This criticism is, as far as we know, the first publication focused on cybernetics that mentioned Bertalanffy’s conceptions, and it is interesting that it did so by stressing both the generality and specificity of the latter’s “open system theory”, most certainly without agreeing with the idea of a reduction of cybernetics to a specific field within the framework of “general systemology” – although Wisdom knew this project:Although nothing suggests that these commentaries of Wisdom, published in the UK, have significantly influenced American cyberneticists, it is very probable that at least one of their English colleagues did not remain impervious to them: it is Ashby, who very early showed interest in Bertalanffy’s conceptions.4.4. The nature and origin of adaptive behaviour was at the heart of Ashby’s reflections as early as 1940 Wisdom , 6. AccoI hope to show that a system can be both mechanistic in nature and yet produce behavior that is adaptive. I hope to show that the essential difference between the brain and any machine yet made is that the brain makes extensive use of a method hitherto little used in machines. I hope to show that by the use of this method a machine’s behavior may be made as adaptive as we please, and that the method may be capable of explaining even the adaptiveness of Man. Ashby , 1Ashby’s initial main concern as a psychiatrist remained brain functioning, and more particularly learning. His aim was thus to prove that it is possible to construct a machine having this ability, and to establish in that way a “machine” explanation of this ability even in humans:Ashby was led by his perspective to elaborate a theory of adaptive behaviour and to construct, based on this theory, a machine meeting those aims. But in doing so, it is more generally his own conception of cybernetics that he elaborated; a conception which, while being in significant aspects different from Bertalanffy’s general systemological project, enabled an essential mediation between this project and the cybernetic science of systems.S of internal states and of a set I of inputs to the set S (in the form S × I → S). He judged this mapping “able to include both the continuous, the discontinuous and even the discrete without the slightest loss of rigor”  of the one machine into those of the other can convert the one representation to the other. Ashby , 97–98Ashby also referred to the importance of “isomorphism” Ashby , 85, e.gpartial formal correspondences. In contrast, Ashby made a clarifying distinction between “isomorphic machines” and “homomorphic machines”, the latter ones expressing a “lesser degree of resemblance”:Two machines may also be related by a “homomorphism”. This occurs when a many-to-one transformation, applied to the more complex, can reduce it to a form that is isomorphic with the simpler […] Two machines are homomorphic when they become alike if one is merely simplified, i.e. observed with less than full discrimination. Formally, if two machines are so related that a many-one transformation can be found that, applied to one of the machines, gives a machine that is isomorphic with the other, then the other (the simpler of the two) is a homomorphism of the first. Ashby , 97–103Bertalanffy’s texts suffered from a lack of clarity in his use of the word “isomorphism” in reference to whole system. His aim must be to achieve a partial knowledge that, though partial over the whole, is none the less complete within itself, and is sufficient for his ultimate practical purpose […] Science is not immediately concerned with discovering what the system “really” is, but with co-ordinating the various observer’s discoveries, each of which is only apportion, an aspect, of the whole truth […] The method of studying very large systems by studying only carefully selected aspects of them is simply what is always done in practice. Here we intend to follow the process more rigorously and consciously.  another system S, that is, lessen its “variety” while maintaining its stability, if, and only if R’s variety is higher than S’s variety: “only variety can destroy variety”. Another form of this law, which is related to one of Shannon’s theorems,R’s capacity as a regulator cannot exceed its capacity as a channel of communication” .R to S, the less is R’s control ability . This is valid until a situation in which S’s “variety” becomes higher than R’s, S thus becoming likely to control R . Ashby pointed out the importance of his law in biology:A species continues to exist primarily because its members can block the flow of variety (thought of as disturbance) to the gene-pattern, and this blockage is the species’ most fundamental need […] By the law of Requisite Variety, the amount of disturbance that reaches the gene-pattern can be diminished only by the amount of information so transmitted. That is the importance of the law in biology. Ashby , 212Ashby defined the “variety” of a set as the base 2 logarithm of the number of its different elements; in particular, the variety of a dynamic system was defined as the base 2 logarithm of its different states Ashby , 124–126n” Ashby , 273–277More generally, the scope of this law would concern all scientists working on the issue of control, especially those dealing with systems having a high “variety”.only statement deserving the true status of general system “law” (in the deductive-nomologic sense of the term).even if it is used preciselyprovided that the machine has been designed to make the necessary selection”  to the rank of “the” n” Ashby , 53.Notwithstanding all those significant lines of convergence, Ashby , 2 distiIf cybernetics, as understood by Ashby, started with the most general systems in order to deduce all possible instances, then cybernetics would be the larger field and include GST. Bertalanffy, however, criticized Ashby’s approach because even though it was deductive, it left out an important issue: systems that show progressive differentiation and evolve in that way to states of higher complexity. This can be found in biological ontogenesis and phylogenesis, as well as in social organizations  feedback system. But dynamic order  can freeze into a (secondary) order with increasingly segregated elements without interaction and fixed feedback loops. A system tending towards such a secondary order appeared as increasingly mechanistic to Bertalanffy. As far as an order is “organismic” in his sense, the dynamics is however always primary, whatever its level of mechanization. For example, when one biological process is altered in an organism, this dynamical system develops compensation strategies. Bertalanffy held that “primary regulations” are a result of dynamic interactions and can be superimposed by secondary regulation where the structures are fixed and “machine-like”. Accordingly, a dynamical order exists before any structural order in the organism. This enables a development towards mechanization, potentially leading to one-way causality, physically speaking to a reduction in the degrees of freedom. And this may be applied ontogenetically as well as phylogenetically , regulation of metabolism in the cell (e.g. in respiration or photosynthesis) is based upon a network of reactions in an open system; with progressive evolution, ever more elaborate homeostatic mechanisms, such as nervous and hormonal feedbacks, arise.  to dynamic regulations, that is, regulations not based upon fixed mechanisms but taking place within a system functioning as a whole , (2) to spontaneous activities, (3) to processes whose goal is not reduction but building up of tensions, and (4) to processes of growth, development, creation, and the like.Bertalanffy constantly emphasized the distinction between regulation in dynamic systems and in feedback systems. The original negative feedback mechanism – not the extended version of Ashby discussed above – is used to minimize the value of a variable (e.g. the distance of one object to another). The arrangement that performs such an operation is fixed and pre-established. If the system is disturbed, the feedback mechanism drives the value to a minimum again. Regulation against disturbance in a dynamical system is different from such a fixed or frozen .As Ungerer , 125–126Even though the result of regulations based on a flux equilibrium in an open system and those which are based on homeostasis [in Wiener’s sense] are similar, and even though both types of regulation overlap in many physiological phenomena, one should clearly distinguish them. The maintenance of flux equilibrium in an open system is based on kinetic and dynamic principles. Whereas homeostasis is based on mechanisms that are typified by feedback; i.e. part of the output of a machine is – as information – guided back to the input and regulates the input and stabilizes the performance of the machine.  or attaining a goal outside the system is due to pre-established structural arrangements. The model scheme in feedback is essentially a machine theory. . These explanations persistently relied on “pre-established structural arrangements”, to which Bertalanffy opposed the principles of his “open system in flux equilibrium”:Feedback mechanisms are essentially one-way causal chains. This is not altered even in the case of what may be called compound feedback, i.e. when not only one, but some regulating mechanisms are active, as in the case, for instance, in ship-steering systems. Feedbacks are what has been called by H. Jordan “amboceptors”. In many biological regulations, however, we have pantoceptor reactions, i.e. interactions of many or all elements integrated in the system. That dynamical order is not taken into consideration by cybernetics, is made clear in an earlier publication . von B, 354linear causality (cause A being followed by effect B), the cybernetic model introduces circular causality by way of the feedback loop and this makes for the self-regulation, goal-directedness, homeostasis, etc., of the system. In contrast, the more general system model is that of dynamic interaction between many variables.  cybernetics provides a “refined machine theory”, but the essential element for him was that it could “hardly be conciliated with definite facts indicating an authentic dynamic order” . He was, however, mistaken to state the reproach that cybernetics is “restricted to closed systems”. The root of this mistake is the evocation by McCulloch of the possibility to explain the Here the two basic features of the theory are obvious, namely, first the machine model of biological phenomena, secondly, the restriction to closed systems. In this sense, our theory seems to be more revolutionary, since, first, it overthrows, as far as basic phenomena are concerned, the Cartesian machine-theory of the organism, and, secondly, is based upon the conception of the organism as an open system. , namely the machine concept versus the organismic concept and the closed versus the open system concept:For the same reason [system closed with respect to exchange of matter], a cybernetic system cannot be “self-organizing”, that is, evolving from a less to a more differentiated state. To be sure, cybernetic systems provided with memory devices can learn, that is, change and increase their organization owing to information input. They cannot undergo processes of differentiation which require input of energy (and matter). In other terms, cybernetic systems can only increase in their entropy content and decrease in information content, information being partly converted into noise but not vice versa (Shannon’s Tenth Theorem). Anti-entropic processes presuppose the system’s being “open”, that is, transfer of matter and energy taking place. . The distinction between open and closed depends where the borders are drawn. For Ashby, the system plus the environment is information tight. He insisted on the fact that the closed system is “organism plus environment” Ashby , 16, 40.nth-order differential equation, and the terms of the latter considered as – formal – “state variables”; while their physical meaning remains indefinite, formal “translation” from one language into the other is thus possible.  be developed as a linear Similarly, predator-prey systems, usually described dynamically by Volterra equations, can also be expressed in terms by cybernetic feedback circuits.  does not change the fact that these models are epistemologically different. They differ with respect to the relevant and important dichotomies internal/external and continuous/discrete, as well as with respect to the formalisms, except perhaps in Ashby’s view of feedback. Moreover, they may be relevant for different aspects of a single phenomenon under study. In line with general systemology (and its perspectivism), these different aspects and their models may have a common underlying basis, whose layout can be revealed by a single general model. Different applications, however, can emphasize different aspects. This does not mean that the aspects and their models are identical and should be confused. Thus, Bertalanffy’s dichotomies remain relevant, although Rosen was right in moderating them.4.7. Coming from philosophy and biology, Bertalanffy crossed the problem of teleology very early (ii), although a difference was seen between the man-made machine and the organism. The machine works in “a way to yield certain products and performances”, whereas in the organism the order of processes “is such as to maintain the system itself”. In the latter, homeostasis comes into play as “an important part of these processes”. Type (2)(iii), equifinality, i.e. the final state can be “reached from different initial conditions and in different ways”, is found in open systems and is responsible for “primary regulability”. Static teleology and dynamic teleology of type (2)(ii) are found in man-made machines and are due to the “planning intelligence”, which in turn is of type (2)(iv) (iii). In a first step, he strived to demonstrate the impossibility to subsume the whole set of organic regulation phenomena under the “homeostasis” concept. He did this by denouncing the trend to conceptualize in that way processes which either have nothing to do with feedback mechanisms (such as metabolic regulation and organic growth) or cannot be completely reduced to such mechanisms (such as the regulations of oxygenation and blood acidity). According to Bertalanffy, the frequent “loose” use of the term “homeostasis” implies a loss of its “proper meaning”, as well as significant epistemological dangers bound to inappropriate methodological procedure:This applies to the classical “proofs of vitalism” as advanced by Driesch and others, such as equifinal regulation in embryonic development, self-regulation in metabolism, “remaining a whole” in spite of division in biological elementary units such as genes and chromosomes, as well as to regeneration, wound-healing, regulations within the nervous system after injuries in its peripheral and central parts, re-establishment of gestalt-perception, etc. Feedback gives no more an explanation of these phenomena than any other machine-theory, whilst these features are, at least in their general aspects, consequences of the open-system character of the organism.  was mistaken with “serving a purpose” or “carrying out a purpose” (einen Zweck ausführen), and the first meaning was reduced to the second one; this is a mistake that Bertalanffy did not make The Macy conferences as well as contemporary papers on cybernetics bathed freely in this reductionism, including representatives of social sciences such as Gregory Bateson and Karl W. Deutsch: life was understood as an entropy reduction device; the organisms and their associations, particularly humans and their societies, as servomechanisms; and the brain, as a computer Heims , 27–28.coup de grace to the mind, and bears out the behaviorist and physiological approach. Now it is true that cybernetics leaves out the mental aspects of action. But the proper inference from this is that cybernetics is in the tradition of physiology and neurology. It does not solve the problem of the relation of mind and body, because it omits one of the parties concerned and suffers from the one-sidedness of its ancestors. . WiIt would be as much dangerous to believe blindly in the models provided by cybernetics as to disdain them […] Psychologically, the integral faith of the cyberneticists in their models looks like the faith of the researchers in the perpetual movement or to the quadrators of the circle. It may be temporarily useful because of the enthusiasm that it raises, but it can quickly become harmful […] All the internal difficulties of cybernetics originate in the same mistake in principle and in the unfortunate postulate according to which the information machines are always supervised by a conscious and meaningful activity […] Every genuine anti-chance is the basis of connections and every connection is based on consciousness. Applying to the machine in order to clear up the mystery of anti-chance and the origin of information is therefore a contradiction. Organic and psychological information, the ordered and meaningful epigenesis of structures in memory and invention cannot be explained mechanistically.  of the present and future; hence, it should be either replaced by computers and other hardware or else made “reliable” – that is, as machinelike, automated, uniform, conformist, and controlled as possible. “Systems” thus appears to be the epitome of the automated wasteland of Bertalanffy tried to safeguard “systems thinking” from being linked to gloomy predictions of the future. This caused him to contrast the intentions or implications of general systemology with those of cybernetics and others. The title and content of one of his papers, “General Systems Theory and a new view of the nature of man”  approach is obviously imperative to deal with the complex problems in modern society; it carries the danger of making the human individual ever more into a small wheel of the social “megamachine.”  as belonging, respectively, to the “mechanistic” and the “organismic” trends of systems science  an awareness of the necessity to develop new strategies in order to grasp the problems resisting the “meristic” epistemologies and their classical “mechanistic” declensions; (2) the subsequent development of systemic concepts and principles; (3) a will to inscribe this development in the mathematical sphere as far as possible and, overall, to overcome the confinement of holistic categories to metaphysics or to the realm of intuition; (4) the general character – that is, abstract and transcending established disciplinary subdivisions – of the concepts and principles in question; (5) an effort to overcome the old dualism between “natural science” and “humanities”Nonetheless, these common traits are in themselves not sufficient to account for the confluence of those lines of research that differ significantly from the point of view of their respective problems and of the “system” concepts that each of them developed Pouvreau , 670–808The systemologists, particularly Bertalanffy from the 1930s onwards, were specifically setting up a project which, from the onset, made extensive use of those three meanings of the concept of “theory”. At the same time, they strived to lay the philosophical foundation that would enable their consistent coexistence and overcoming the aforementioned apparent contradictions: at least since the early 1950s, all the concerned issues had been discussed with more or less depth in their initial contributions to “philosophical systemology” related to perspectivism, philosophy of systems science, ontology, logic, methodology, axiology and praxeology. The further deepening of these discussions has in fact been a major characteristic of the whole development of the systemological project, especially in Rapoport’s work Pouvreau , 197–210The “cybersciences” framework lacked any clarification of the function of theory and of the concept of scientific law. This was a problem in that these new sciences introduced a radical novelty which was theorized some years later by Herbert A. SimonWithout trying to remedy it before the 1950s, some “cyberscientists” were aware of this set of uncertainties regarding epistemology as well as the general philosophy of science and of its social function.7. Overcoming specialization and integrating various scientific fields was a common aim of Bertalanffy and cyberneticists, even though they started from different standpoints. First order cybernetics was largely concerned with engineering. Here, very useful theoretical models and methods were developed that turned out to be applicable in different fields in a relatively straight forward way. In contrast, Bertalanffy’s “systemological” project was from the onset very significantly concerned with philosophy in general  as well as with ideological issues. And it was chiefly elaborated with regard to the fields of biology and psychology. The criticism towards an alleged “realism” of general systemology cannot be upheld: it must be strictly rejected with regard to the trained philosopher Bertalanffy and almost all other systemologists. Constructivism stemming from second order cybernetics and Bertalanffy’s perspectivism are not equal, but they are also not mutually exclusive. This provides an opportunity for common future efforts. On scientific grounds, cybernetics starts with a machine view of different kinds of systems , whereas systemology starts with an organismic view of various systems . Bertalanffy emphasized the  difference between regulation in an open system and in a homeostatic feedback system. He pointed out the problem of trying to apply the feedback mechanism to research issues where it is not applicable; arguing that other types of explanation had to be sought. He also emphasized the connections of these different approaches to different world views, and the fact  and call the cyberneticists’ contribution “cybernetic systemology”. Both would therefore be different but complementary aspects of the development of “general systemology” as a general science of the systemic interpretation of the “real” . We suggest the term “general systemology” for the common endeavour. Suggestions such as “systems science” as an umbrella term  as an umbrella term is more neutral. Remaining fully faithful to Bertalanffy’s inspiration, the concept to which it refers may in particular help avoiding reductionism in “systems research”.Bertalanffy had a very general view of systemology as a program and hermeneutics for the systemic interpretation of the “real” Pouvreau ; 2014a. Manfred Drack is Austrian. He was trained as a mechanical engineer and studied biology. After conducting research at the Center for Biomimetics at the University of Reading, he received a doctorate from the University of Vienna with a thesis on biomimetics and eco-design. He worked in several projects at the Center for Appropriate Technology of the Vienna University of Technology. Rupert Riedl brought him back to the University of Vienna. After one year in Olaf Wolkenhauer’s group at the University of Rostock, he was working at the Department of Theoretical Biology, University of Vienna. Now he is at the University of Tübingen.David Pouvreau is French. He is a postgraduate in mathematics (agrégation) and holds a doctorate in the history and philosophy of science . He is a fellow at the Bertalanffy Center for the Study of Systems Science in Vienna and is associate researcher at the Department of Philosophy of the University of Toulouse II. He is continuing his research in the history and philosophy of “general system theory”, which was the subject of his doctoral studies. He has published several papers on the subject, as well as a biography of Ludwig von Bertalanffy.


In the past decades, various frameworks, methods, indicators, and tools have been developed to assess the needs as well as to monitor and evaluate  health research capacity development (HRCD) activities. This systematic review gives an overview on NaME activities at the individual and organizational level in the past 10 years with a specific focus on methods, tools and instruments. Insight from this review might support researchers and stakeholders in systemizing future efforts in the HRCD field.A systematic literature search was conducted in PubMed and Google Scholar. Additionally, the personal bibliographies of the authors were scanned. Two researchers independently reviewed the identified abstracts for inclusion according to previously defined eligibility criteria. The included articles were analysed with a focus on both different HRCD activities as well as NaME efforts.Initially, the search revealed 700 records in PubMed, two additional records in Google Scholar, and 10 abstracts from the personal bibliographies of the authors. Finally, 42 studies were included and analysed in depth. Findings show that the NaME efforts in the field of HRCD are as complex and manifold as the concept of HRCD itself. NaME is predominately focused on outcome evaluation and mainly refers to the individual and team levels.A substantial need for a coherent and transparent taxonomy of HRCD activities to maximize the benefits of future studies in the field was identified. A coherent overview of the tools used to monitor and evaluate HRCD activities is provided to inform further research in the field. The capacity to cope with new and ill-structured situations is a crucial ability in today’s world. Developing this ability, by shaping empowered citizens, challenges individuals as well as organisations and societies. This process of empowerment is usually referred to as capacity development (CD) . While tWe followed the PRISMA checklist for reporting systematic reviews and meta-analyses . Inclusi”, “capacity development” AND “research”, and “capacity strengthening” AND “research”. We checked the first 200 hits in Google Scholar for each search term. “Health” and “evaluation” were not included in the search terms as a pre-test search had revealed this would exclude relevant literature. Articles from personal bibliographies of the authors were also included.We conducted the systematic literature search in July 2013. The search was done in both the literature database PubMed and the search engine Google Scholar. We applied the three search terms “capacity building” AND “researchThe inclusion process was structured along the five inclusion categories ‘capacity development’, ‘research’, ‘health profession fields’, ‘monitoring and evaluation’, and ‘level of NaME’. Table The category ‘capacity development’  represenFor the categories ‘research’, ‘health profession fields’ and ‘monitoring and evaluation’, at least one of the operationalisations of each category had to be addressed by the study. The category ‘level of NaME’ was operationalized referring to the ESSENCE framework ‘Planning, monitoring and evaluation framework for capacity strengthening in health research’ which describes three CD levels: individual and/or team, organizational, and system levels . Only puAdditionally, the following eligibility criteria were set: English or German language, publication period from January 1, 2003, to June 30, 2013, intervention, non-intervention and multiple design studies  . Six stuThe evaluation focus of the studies was predominately on outcome evaluation (n = 23). Besides that, six studies surveyed the current state, three studies assessed requirements, and two studies investigated needs of HRCD activities. The remaining eight studies combined two evaluation aspects: definition of needs and outcome evaluation (n = 4), analysis of current state and outcome evaluation (n = 1), outcome evaluation and impact evaluation (n = 1), and analysis of current state and definition of needs (n = 1). Jamerson et al.  did not Nearly half of the studies investigated HRCD on the individual/team level (n = 20); 16 studies were conducted at both the individual/team and organizational levels. The authors of six studies focused on organizational aspects of HRCD.Almost all studies (n = 38) described and evaluated HRCD activities; 19 of these HRCD activities were training programmes of predefined duration, lasting between some hours or days up to 2 years. Another nine HRCD activities were perpetual or their duration not specified and 10 studies defined and pre-assessed the setting in preparation of an HRCD activity. The authors of four studies did not specify an HRCD activity, focussing on the development or validation of tools, instruments, and frameworks.The participants of HRCD activities represent a wide range of health professions ; 10 studies investigated staff with management tasks in health, e.g. hospital managers, clinical research managers. Nurses participated in eight studies with another eight studies looking into ‘research staff’ and ‘scientists’ with no further description. Medical practitioners were studied in five papers. Besides all these, the background of participants was often not specified beyond general terms like ‘health professionals’, ‘ethic committee members’, ‘scholars’, ‘university faculty members’, or ‘allied health professionals’. In a different approach, Suter et al.  analysedA wide variety of study designs was employed by the studies included in the review. We identified 35 single-study and six multi-study approaches. Of the 35 single-study approaches, 10 were designed as intervention (three with control groups) and 25 as non-intervention studies. Four multi-study approaches combined an intervention study with a non-intervention study. Two multi-study approaches combined different non-intervention studies. Jamerson et al.  did not Many different tools and instruments for NaME were identified and applied in quantitative, qualitative and mixed mode of analysis. No preferred approach was observed. One third of the studies (n = 16) used a combination of tools for quantitative as well as qualitative analysis. In 13 studies, tools like questionnaires and assessment sheets were applied to evaluate and monitor HRCD activities quantitatively. Evaluation tools, such as interviews, focus group discussions, document analyses, or mapping of cases against evaluation frameworks, were identified in 12 studies and commonly analysed in a qualitative approach. In one study, tools for evaluation were not described at all.The aim of our systematic review was to give an overview on tools and instruments for NaME of HRCD activities on the individual and organizational level; 42 included articles demonstrated a large variety of tools and instruments in specific settings. Questionnaires, assessment sheets and interviews  were most commonly applied and in part disseminated for further use, development and validation.Overall, 36 studies were either conducted on the individual/team or on both individual/team and organizational level. Within these studies, a well-balanced mixture of quantitative, qualitative and mixed tools and modes of analysis were applied. Judging from the depth of these studies, it seems as if NaME of HRCD on the individual level is quite well developed. Only six studies focused exclusively on organizational aspects, almost all with qualitative approaches, indicating that HRCD studies at this level are still mainly exploratory. The organizational level is possibly a more complex construct to measure. The fact that 13 out of 19 studies that broach organizational aspects were conducted in high-income countries might reflect the wider possibilities of these research institutions and indicates a need for more attention to NaME on the organizational level in lower-income settings. Results from these exploratory studies on the organizational level should feed into the development of standardized quantitative indicators more regularly. Qualitative approaches could be pursued for complex and specific constructs not easily covered quantitatively.By not limiting the primary selection of articles for this review to a specific health profession, it was revealed that staff with management tasks in health research, as well as nurses, were the cohorts most frequently targeted by NaME studies. Further research should concentrate on other health professionals to determine communalities and differences of health-research related skill acquisition and development between health professions. These studies could determine whether and which parts of HRCD and NaME can be considered generic across health professions. Further, we will at some point have to ask, who is being left out and who is not getting access to HRCD programs, and why.The focus of NaME throughout the studies included in this review was on outcome measurement, regardless of whether these were conducted in high-income, upper-middle, lower-middle, or low-income countries. However, there were only few reports of needs assessment from middle- and low-income economies, while high-income countries regularly give account of current states. While this should not be over-interpreted, it still raises the question of whether the needs assessment in the middle- and low-income countries is being done as thoroughly as warranted, but not reported in the articles, or if these countries’ needs might not always be at the very centre of the HRCD’s attention. While the evaluation of HRCD outcomes is, of course, of importance, more attention should be paid to the sustainability of programs and impact evaluation, e.g. parameters of patient care or societal aspects. Only one study, that of Hyder et al. , made usWhen undertaking the review, three main methodological weaknesses of this research area became apparent. First, there is a need for common definitions and terminologies to better communicate and compare the HRCD efforts. The analysis of the studies showed that there is an inconsistent use of terms, for example, for CD activities . Similar problems were already identified in the context of educational capacity building by Steinert et al. , who sugThe second weakness of the research area is the varying adherence to reporting standards. While there are standards available for reporting qualitative or quantitative research (e.g. Rossi et al. , DowningThe last point concerns the study designs implemented. The majority of articles are mainly descriptive, non-intervention studies that only allow for low evidence according to Cochrane standards . While mThis systematic review displays some methodological limitations itself. The issue of deviating terminologies has been raised earlier. In most cases, we adopted the terms used in the studies themselves, e.g. when reporting the authors’ denoted study designs. In very few cases, we changed or completed terms to make the studies more comparable to others. One example is changing the wording from Green et al.’s  “case stA systematic review on studies from the field of HRCD activities was conducted, with 42 studies being fully analysed. The analysis revealed that a variety of terms and definitions used to describe NaME efforts impedes the comparability and transferability of results. Nevertheless, insight from this review can help to inform researchers and other stakeholders in the HRCD community. A coherent overview on tools and instruments for NaME of HRCD was developed and is provided Table .Furthermore, it is time to set standards for NaME in the HRCD community. Researchers and stakeholders should develop a common research agenda to push, systematise and improve the research efforts in the field of NaME of HRCD activities. To do so, a common language and terminology is required. The conceptualizations used for the purpose of these review can inform this development. On the other hand, we have to critically analyse research gaps in terms of generalizable versus context-specific theories, methods, tools, and instruments. To maximize the benefits and to incorporate different research traditions, these undertakings should be done internationally and multi-professionally within the HRCD community.


Quantum information provides fundamentally different computational resources than classical information. We prove that there is no unitary protocol able to add unknown quantum states belonging to different Hilbert spaces. This is an inherent restriction of quantum physics that is related to the impossibility of copying an arbitrary quantum state, i.e., the no-cloning theorem. Moreover, we demonstrate that a quantum adder, in absence of an ancillary system, is also forbidden for a known orthonormal basis. This allows us to propose an approximate quantum adder that could be implemented in the lab. Finally, we discuss the distinct character of the forbidden quantum adder for quantum states and the allowed quantum adder for density matrices. Addition plays a central role in mathematics and physics, while adders are ubiquitous devices in the fields of computation4678ϕ = ϕ1 + ϕ2, yielding an observable relative phase. When the ancillary state U to two equal state vectors Let U is a unitary matrix, it imposes some orthogonality conditions on the final vectors, d, but these constraints require the existence of at least 2d − 1 orthonormal vectors, which is impossible.We consider now a different question, whether a quantum adder may exist for a given orthonormal basis. In this case, as we will see, the global phase does not produce any ambiguity in the equations. Let us consider the action of the unitary operator Ua, computes the exact sum of the basis elements in qubit systems. Moreover, Ua is extended by linearity to the whole Hilbert space, and implements an approximate sum when the input states are superpositions of the basis elements. The adder is given by the following expression in which We propose now the use of an ancillary system Although this approximate quantum adder shows high fidelities, it is not optimal as the one recently found in Ref. i, j ≤ d. These operators straightforwardly perform the sum, i.e., Beyond the sum of quantum states in Let us compare the adders for state vectors and density operators. By writing the input states in By comparing the adders in How to cite this article: Alvarez-Rodriguez, U. et al. The Forbidden Quantum Adder. Sci. Rep.5, 11983; doi: 10.1038/srep11983 (2015).


Viruses are generally considered to be amongst the smallest bioactive particles; dating back to the original observations, including those of luminaries such as Ivanosky and Beijerinck, size has always been at issue within the definition, a tradition that continued for many years . It was Mimiviridae that infect amoebas, as well as the “extended” phylogenetic group that infect algae [Nucleocytoplasmic large DNA viruses (NCLDVs) group that also includes the Phycodnaviridae, Iridoviridae, Poxviridae, Marseilleviridae, Asfarviridae, and Ascoviridae. These viruses have been shown (to date) to infect organisms including algae and protists . And while their size is constantly surprising, it is the latter trait  that is of interest to many researchers. A research opportunity is to question why these particles need to carry so many different genetic blueprints , and how these extra costs provide benefits with respect to viral fitness and selection in a complicated and complex microbial and viral world.In general, the term “giant virus” is now commonly used to refer to viruses that have a large genome  and/or particle size (>0.2 μm). While a variety of arguments can be made for altering these metrics, what is clear is that these viruses bring with them a potential (in terms of genes that are transcribed and translated) that is historically associated with cellular life forms: this includes members of the ct algae . These vChlorella-infecting virus group [Oedogonium spp. “L” [Uronema gigas [Gymnodinium uberrimum [As noted above, the study of giant viruses emerged with the confluence of observation  and opportunity (the emergence of modern techniques in molecular biology that have rapidly advanced the ability to study these viruses). In retrospect, there have historically been many other large viruses observed by scientists. Several algal viruses such as Ectocaprus siliculosus virus (EsV-1)  and Micrus group , have bespp. “L”  and Uronma gigas , respectberrimum . Indeed,Acanthamoeba spp. to enrich for virus populations. This technique has led to the discovery of novel giant viruses in marine and freshwater samples and, unexpectedly, ancient amoeba-infecting viruses that have persisted in ~30,000-year-old Siberian permafrost [While the discovery of Mimivirus has spurred extensive research into the origins and capabilities of giant viruses, little is currently known about their global distribution and diversity. Giant viruses have been isolated largely from aquatic samples, often using rmafrost . Giant vrmafrost . That thrmafrost ). IndeedGiant viruses exhibit diverse morphologies, lifestyles, and even genomic structure, but there are some shared features that set them apart from other systems. Most obvious is the “nucleocytoplasmic” distinction of replicative strategies: for example, in some of these giant viruses, a cytoplasmic, organelle-like virion factory quickly forms in the infected host as the site for virion morphogenesis—a feature previously witnessed only in RNA viruses . This orOne thing that has become clear since the discovery of the Mimivirus  is that the “rules” are changing. In recent months, we have seen a series of researchers working to redefine “What is a virus?”  and even