446 research outputs found

    Evolution: Complexity, uncertainty and innovation

    Get PDF
    Complexity science provides a general mathematical basis for evolutionary thinking. It makes us face the inherent, irreducible nature of uncertainty and the limits to knowledge and prediction. Complex, evolutionary systems work on the basis of on-going, continuous internal processes of exploration, experimentation and innovation at their underlying levels. This is acted upon by the level above, leading to a selection process on the lower levels and a probing of the stability of the level above. This could either be an organizational level above, or the potential market place. Models aimed at predicting system behaviour therefore consist of assumptions of constraints on the micro-level – and because of inertia or conformity may be approximately true for some unspecified time. However, systems without strong mechanisms of repression and conformity will evolve, innovate and change, creating new emergent structures, capabilities and characteristics. Systems with no individual freedom at their lower levels will have predictable behaviour in the short term – but will not survive in the long term. Creative, innovative, evolving systems, on the other hand, will more probably survive over longer times, but will not have predictable characteristics or behaviour. These minimal mechanisms are all that are required to explain (though not predict) the co-evolutionary processes occurring in markets, organizations, and indeed in emergent, evolutionary communities of practice. Some examples will be presented briefly

    Long-term outcome prediction by clinicopathological risk classification algorithms in node-negative breast cancer--comparison between Adjuvant!, St Gallen, and a novel risk algorithm used in the prospective randomized Node-Negative-Breast Cancer-3 (NNBC-3) trial.

    Get PDF
    Defining risk categories in breast cancer is of considerable clinical significance. We have developed a novel risk classification algorithm and compared its prognostic utility to the Web-based tool Adjuvant! and to the St Gallen risk classification. After a median follow-up of 10 years, we retrospectively analyzed 410 consecutive node-negative breast cancer patients who had not received adjuvant systemic therapy. High risk was defined by any of the following criteria: (i) age <35 years, (ii) grade 3, (iii) human epithelial growth factor receptor-2 positivity, (iv) vascular invasion, (v) progesterone receptor negativity, (vi) grade 2 tumors >2 cm. All patients were also characterized using Adjuvant! and the St Gallen 2007 risk categories. We analyzed disease-free survival (DFS) and overall survival (OS). The Node-Negative-Breast Cancer-3 (NNBC-3) algorithm enlarged the low-risk group to 37% as compared with Adjuvant! (17%) and St Gallen (18%), respectively. In multivariate analysis, both Adjuvant! [P = 0.027, hazard ratio (HR) 3.81, 96% confidence interval (CI) 1.16-12.47] and the NNBC-3 risk classification (P = 0.049, HR 1.95, 95% CI 1.00-3.81) significantly predicted OS, but only the NNBC-3 algorithm retained its prognostic significance in multivariate analysis for DFS (P < 0.0005). The novel NNBC-3 risk algorithm is the only clinicopathological risk classification algorithm significantly predicting DFS as well as OS

    Long-term outcome prediction by clinicopathological risk classification algorithms in node-negative breast cancer—comparison between Adjuvant!, St Gallen, and a novel risk algorithm used in the prospective randomized Node-Negative-Breast Cancer-3 (NNBC-3) trial

    Get PDF
    Background: Defining risk categories in breast cancer is of considerable clinical significance. We have developed a novel risk classification algorithm and compared its prognostic utility to the Web-based tool Adjuvant! and to the St Gallen risk classification. Patients and methods: After a median follow-up of 10 years, we retrospectively analyzed 410 consecutive node-negative breast cancer patients who had not received adjuvant systemic therapy. High risk was defined by any of the following criteria: (i) age 2 cm. All patients were also characterized using Adjuvant! and the St Gallen 2007 risk categories. We analyzed disease-free survival (DFS) and overall survival (OS). Results: The Node-Negative-Breast Cancer-3 (NNBC-3) algorithm enlarged the low-risk group to 37% as compared with Adjuvant! (17%) and St Gallen (18%), respectively. In multivariate analysis, both Adjuvant! [P = 0.027, hazard ratio (HR) 3.81, 96% confidence interval (CI) 1.16-12.47] and the NNBC-3 risk classification (P = 0.049, HR 1.95, 95% CI 1.00-3.81) significantly predicted OS, but only the NNBC-3 algorithm retained its prognostic significance in multivariate analysis for DFS (P < 0.0005). Conclusion: The novel NNBC-3 risk algorithm is the only clinicopathological risk classification algorithm significantly predicting DFS as well as O

    Effects of low-frequency whole-body vibration on motor-evoked potentials in healthy men.

    Get PDF
    addresses: Sport and Exercise Science Research Centre, Faculty of Engineering, Science and The Built Environment, London South Bank University, 103 Borough Road, London SE1 0AA, UK. [email protected] is the author's post-print version of an article published in Experimental Physiology, 2009, Vol. 94, Issue 1, pp. 103 - 116 Copyright © 2009 Wiley-Blackwell /The Physiological Society. The definitive version is available at www3.interscience.wiley.comThe aim of this study was to determine whether low-frequency whole-body vibration (WBV) modulates the excitability of the corticospinal and intracortical pathways related to tibialis anterior (TA) muscle activity, thus contributing to the observed changes in neuromuscular function during and after WBV exercise. Motor-evoked potentials (MEPs) elicited in response to transcranial magnetic stimulation (TMS) of the leg area of the motor cortex were recorded in TA and soleus (SOL) muscles of seven healthy male subjects whilst performing 330 s continuous static squat exercise. Each subject completed two conditions: control (no WBV) and WBV (30 Hz, 1.5 mm vibration applied from 111 to 220 s). Five single suprathreshold and five paired TMS were delivered during each squat period lasting 110 s (pre-, during and post-WBV). Two interstimulus intervals (ISIs) between the conditioning and the testing stimuli were employed in order to study the effects of WBV on short-interval intracortical inhibition (SICI, ISI = 3 ms) and intracortical facilitation (ICF, ISI = 13 ms). During vibration relative to squat exercise alone, single-pulse TMS provoked significantly higher TA MEP amplitude (56 +/- 14%, P = 0.003) and total area (71 +/- 19%, P = 0.04), and paired TMS with ISI = 13 ms provoked smaller MEP amplitude (-21 +/- 4%, P = 0.01) but not in SOL. Paired-pulse TMS with ISI = 3 ms elicited significantly lower MEP amplitude (TA, -19 +/- 4%, P = 0.009; and SOL, -13 +/- 4%, P = 0.03) and total area (SOL, -17 +/- 6%, P = 0.02) during vibration relative to squat exercise alone in both muscles. Tibialis anterior MEP facilitation in response to single-pulse TMS suggests that WBV increased corticospinal pathway excitability. Increased TA and SOL SICI and decreased TA ICF in response to paired-pulse TMS during WBV indicate vibration-induced alteration of the intracortical processes as well

    The interpretations and uses of fitness landscapes in the social sciences

    Get PDF
    __Abstract__ This working paper precedes our full article entitled “The evolution of Wright’s (1932) adaptive field to contemporary interpretations and uses of fitness landscapes in the social sciences” as published in the journal Biology & Philosophy (http://link.springer.com/article/10.1007/s10539-014-9450-2). The working paper features an extended literature overview of the ways in which fitness landscapes have been interpreted and used in the social sciences, for which there was not enough space in the full article. The article features an in-depth philosophical discussion about the added value of the various ways in which fitness landscapes are used in the social sciences. This discussion is absent in the current working paper. Th

    Technology Nascent Entrepreneur Experiences of Start-up Competition Participation

    Get PDF
    Start-up competitions have been proliferating across university campuses worldwide as one of the mechanisms to support student and graduate entrepreneurship. The chapter takes the start-up competition (SUC) phenomenon from the perspective of the technology nascent entrepreneur participant and within the context of their individual experiences of participation. It contextualises the start-up competition, giving due attention to its origins and the contemporary environment, and conceptualises the phenomenon, unpacking the espoused benefits of the competition participation experience for the participant. This highlights that despite SUC being promoted to technology nascent entrepreneurs as an important activity and valuable opportunity, a problematic dearth in knowledge surrounds how such entrepreneurs understand, describe and reflect upon their experiences of SUC participation. Through the medium of two individual and exploratory case studies, this chapter presents nascent technology entrepreneur accounts of their participation in a UK university-based business plan competition. Propositions are offered which could usefully guide much-needed further exploration of start-up competitions within the context of technology nascent entrepreneurial new venturing
    corecore