Desk study on homeopathy in organic livestock farming: Principles, obstacles and recommendations for practice and research

Organic livestock farming has its own concept of health and welfare. The approach to health can be characterised by the key words human, preventive, self-regulating and holistic (Chapter 1). This has consequences for the way we deal with diseases and problems, the nature of the solutions and the use of medication, among other things. In terms of therapeutic and regulatory measures this health concept is based primarily on natural food supplements and homeopathic remedies, which in view of their origin fit in well with the natural character of organic agriculture (Verhoog et al., 2002). Apart from various forms of potentised remedies (classic, clinical, anthroposophic, isopathic; Chapter 2) and all manner of applications within phytotherapy (Bach flower, aromatherapy), there is interest in organic livestock farming in complementary health treatments other than acupuncture. We also need more detailed research into the practical implications of possible self-medication by animals (Engel, 2001). Complementary medicine demands a new type of knowledge in relation to its working mechanism, testing for authenticity and the way it is used (Chapter 3). The thinking behind the use of homeopathic remedies often based on a preventive approach to health. With the aid of these remedies the doctor seeks to create a more balanced environment in and around the animal and to improve the animal’s resistance to infections (Baars en Ellinger, 1997). Striezel (2001) calls homeopathy a regulatory therapy, which heals the body by stimulating the individual immune system and regulating the metabolism. The use of homeopathic remedies is still limited in practice, partly due to a lack of suitably trained veterinary practitioners (Chapter 4). In the elaboration of the research questions the authors discovered that the use of homeopathic remedies meets with particular resistance which can be traced back to philosophical assumptions (sections 4.1-4.3). As the research is fleshed out it is therefore important that it is not simply carried out in conformity with currently valid scientific standards. The research design must also be in line with the philosophy of homeopathy in terms of both quantity and quality (Chapter 5). This is particularly important for homeopathy because its therapeutic methods are based on principles which do not fit in with conventional notions about life. The similia principle (law of similars) is an important feature of homeopathy and homeopathy shares the second key concept of potentisation with anthroposophy (Chapter 2). There is limited acceptance of homeopathic remedies in particular, despite the fact that there is some empirical evidence for the efficacy of homeopathic treatments. Both outcome research into homeopathic treatments of humans and animals and fundamental empirical research into the validity of the similia law and the efficacy of high dilutions produce results which tend to bear this out. However, it is rejected out of hand on ontological grounds and because of the assumed working mechanism. Follow-up research into homeopathic remedies is desirable, but must be in line with the underlying complementary health and welfare concept of organic agriculture, which includes treatment with veterinary medicines. Randomised Clinical Trials are thus only of limited use, since they disregard the individually tailored nature of the treatment. In practice however, sufficient alternative therapies have been developed which can be used in outcome research. The researchers propose a graduated structure for the outcome research (Chapter 6). The first step is to join in with the monitoring of experience in practice, and follow this with casuistic outcome research

Behavior change interventions: the potential of ontologies for advancing science and practice

A central goal of behavioral medicine is the creation of evidence-based interventions for promoting behavior change. Scientific knowledge about behavior change could be more effectively accumulated using "ontologies." In information science, an ontology is a systematic method for articulating a "controlled vocabulary" of agreed-upon terms and their inter-relationships. It involves three core elements: (1) a controlled vocabulary specifying and defining existing classes; (2) specification of the inter-relationships between classes; and (3) codification in a computer-readable format to enable knowledge generation, organization, reuse, integration, and analysis. This paper introduces ontologies, provides a review of current efforts to create ontologies related to behavior change interventions and suggests future work. This paper was written by behavioral medicine and information science experts and was developed in partnership between the Society of Behavioral Medicine's Technology Special Interest Group (SIG) and the Theories and Techniques of Behavior Change Interventions SIG. In recent years significant progress has been made in the foundational work needed to develop ontologies of behavior change. Ontologies of behavior change could facilitate a transformation of behavioral science from a field in which data from different experiments are siloed into one in which data across experiments could be compared and/or integrated. This could facilitate new approaches to hypothesis generation and knowledge discovery in behavioral science

Evidence based or person centered? An ontological debate

Evidence based medicine (EBM) is under critical debate, and person centered healthcare (PCH) has been proposed as an improvement. But is PCH offered as a supplement or as a replacement of EBM? Prima facie PCH only concerns the practice of medicine, while the contended features of EBM also include methods and medical model. I here argue that there are good philosophical reasons to see PCH as a radical alternative to the existing medical paradigm of EBM, since the two seem committed to conflicting ontologies. This paper aims to make explicit some of the most fundamental assumptions that motivate EBM and PCH, respectively, in order to show that the choice between them ultimately comes down to ontological preference. While EBM has a solid foundation in positivism, or what I here call Humeanism, PCH is more consistent with causal dispositionalism. I conclude that if there is a paradigmatic revolution on the way in medicine, it is first of all one of ontology

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N

What Normative Facts Should Political Theory Be About? Philosophy of Science meets Political Liberalism

Just as different sciences deal with different facts—say, physics versus biology—so we may ask a similar question about normative theories. Is normative political theory concerned with the same normative facts as moral theory or different ones? By developing an analogy with the sciences, we argue that the normative facts of political theory belong to a higher— more coarse-grained—level than those of moral theory. The latter are multiply realizable by the former: competing facts at the moral level can underpin the same facts at the political one. Consequently, some questions that moral theories answer are indeterminate at the political level. This proposal offers a novel interpretation of John Rawls’s idea that, in public reasoning, we should abstract away from comprehensive moral doctrines. We contrast our distinction between facts at different levels with the distinction between admissible and inadmissible evidence and discuss some implications for the practice of political theory

Categorical Ontology of Complex Systems, Meta-Systems and Theory of Levels: The Emergence of Life, Human Consciousness and Society

Single cell interactomics in simpler organisms, as well as somatic cell interactomics in multicellular organisms, involve biomolecular interactions in complex signalling pathways that were recently represented in modular terms by quantum automata with ‘reversible behavior’ representing normal cell cycling and division. Other implications of such quantum automata, modular modeling of signaling pathways and cell differentiation during development are in the fields of neural plasticity and brain development leading to quantum-weave dynamic patterns and specific molecular processes underlying extensive memory, learning, anticipation mechanisms and the emergence of human consciousness during the early brain development in children. Cell interactomics is here represented for the first time as a mixture of ‘classical’ states that determine molecular dynamics subject to Boltzmann statistics and ‘steady-state’, metabolic (multi-stable) manifolds, together with ‘configuration’ spaces of metastable quantum states emerging from complex quantum dynamics of interacting networks of biomolecules, such as proteins and nucleic acids that are now collectively defined as quantum interactomics. On the other hand, the time dependent evolution over several generations of cancer cells --that are generally known to undergo frequent and extensive genetic mutations and, indeed, suffer genomic transformations at the chromosome level (such as extensive chromosomal aberrations found in many colon cancers)-- cannot be correctly represented in the ‘standard’ terms of quantum automaton modules, as the normal somatic cells can. This significant difference at the cancer cell genomic level is therefore reflected in major changes in cancer cell interactomics often from one cancer cell ‘cycle’ to the next, and thus it requires substantial changes in the modeling strategies, mathematical tools and experimental designs aimed at understanding cancer mechanisms. Novel solutions to this important problem in carcinogenesis are proposed and experimental validation procedures are suggested. From a medical research and clinical standpoint, this approach has important consequences for addressing and preventing the development of cancer resistance to medical therapy in ongoing clinical trials involving stage III cancer patients, as well as improving the designs of future clinical trials for cancer treatments.\ud \ud \ud KEYWORDS: Emergence of Life and Human Consciousness;\ud Proteomics; Artificial Intelligence; Complex Systems Dynamics; Quantum Automata models and Quantum Interactomics; quantum-weave dynamic patterns underlying human consciousness; specific molecular processes underlying extensive memory, learning, anticipation mechanisms and human consciousness; emergence of human consciousness during the early brain development in children; Cancer cell ‘cycling’; interacting networks of proteins and nucleic acids; genetic mutations and chromosomal aberrations in cancers, such as colon cancer; development of cancer resistance to therapy; ongoing clinical trials involving stage III cancer patients’ possible improvements of the designs for future clinical trials and cancer treatments. \ud \u

Ontology-driven conceptual modeling: A'systematic literature mapping and review

All rights reserved. Ontology-driven conceptual modeling (ODCM) is still a relatively new research domain in the field of information systems and there is still much discussion on how the research in ODCM should be performed and what the focus of this research should be. Therefore, this article aims to critically survey the existing literature in order to assess the kind of research that has been performed over the years, analyze the nature of the research contributions and establish its current state of the art by positioning, evaluating and interpreting relevant research to date that is related to ODCM. To understand and identify any gaps and research opportunities, our literature study is composed of both a systematic mapping study and a systematic review study. The mapping study aims at structuring and classifying the area that is being investigated in order to give a general overview of the research that has been performed in the field. A review study on the other hand is a more thorough and rigorous inquiry and provides recommendations based on the strength of the found evidence. Our results indicate that there are several research gaps that should be addressed and we further composed several research opportunities that are possible areas for future research

A model-driven method for the systematic literature review of qualitative empirical research

This paper explores a model-driven method for systematic literature reviews (SLRs), for use where the empirical studies found in the literature search are based on qualitative research. SLRs are an important component of the evidence-based practice (EBP) paradigm, which is receiving increasing attention in information systems (IS) but has not yet been widely-adopted. We illustrate the model-driven approach to SLRs via an example focused on the use of BPMN (Business Process Modelling Notation) in organizations. We discuss in detail the process followed in using the model-driven SLR method, and show how it is based on a hermeneutic cycle of reading and interpreting, in order to develop and refine a model which synthesizes the research findings of previous qualitative studies. This study can serve as an exemplar for other researchers wishing to carry out model-driven SLRs. We conclude with our reflections on the method and some suggestions for further researc