Clusters, human capital and economic development in Oxfordshire and Cambridgeshire

Oxfordshire and Cambridgeshire are two of the most high tech economies in the UK (see for example DTI, 2002 and Garnsey and Lawton Smith, 1998). They are home to world class research universities and public and private research laboratories as well as a full range of business and professional services which support the development of their clusters. Building on previous work (Lawton Smith and Waters, 2011) this paper draws on national datasets to review the continued development of these economies. The paper considers issues such as new firm formation, sectoral composition and gross value added and relates them to social inclusion and worklessness. The paper draws on literature which emphasises the endogeneity of processes within regions, but also on studies which show that there are different kinds of high tech regions with varying industrial structures. Conclusions are drawn on the extent to which the presence of successful clusters (Spencer et al, 2010) influences outcomes for the local economy more generally, and how Oxfordshire and Cambridgeshire have performed over the last ten years

Entrepreneurship, innovation and the triple helix model: evidence from Oxfordshire and Cambridgeshire

This paper focuses on how regions become entrepreneurial and the extent to which the actors in the triple helix model are dominant at particular stages in development. It uses the case studies of Oxfordshire and Cambridgeshire in the UK to explore this theme. Both can now be described as ‘regional triple helix spaces’ (Etzkowitz 2008), and form two points of the Golden Triangle of Oxford, Cambridge and London universities. As entrepreneurial regions, however, they differ in a number of respects. This is not surprising given their differing geo-historical contexts. However, by comparing the two similar counties but which have their own distinctive features we are able to explore different dynamics which lead to the inception, implementation, consolidation and renewal (Etzkowitz and Klofsten 2005) of regions characterised by very high levels of technology-based entrepreneurship

A High Speed Particle Phase Discriminator (PPD-HS) for the classification of airborne particles, as tested in a continuous flow diffusion chamber

© Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License.A new instrument, the High-speed Particle Phase Discriminator (PPD-HS), developed at the University of Hertfordshire, for sizing individual cloud hydrometeors and determining their phase is described herein. PPD-HS performs an in situ analysis of the spatial intensity distribution of near-forward scattered light for individual hydrometeors yielding shape properties. Discrimination of spherical and aspherical particles is based on an analysis of the symmetry of the recorded scattering patterns. Scattering patterns are collected onto two linear detector arrays, reducing the complete 2-D scattering pattern to scattered light intensities captured onto two linear, one-dimensional strips of light sensitive pixels. Using this reduced scattering information, we calculate symmetry indicators that are used for particle shape and ultimately phase analysis. This reduction of information allows for detection rates of a few hundred particles per second. Here, we present a comprehensive analysis of instrument performance using both spherical and aspherical particles generated in a well-controlled laboratory setting using a vibrating orifice aerosol generator (VOAG) and covering a size range of approximately 3-32 μm. We use supervised machine learning to train a random forest model on the VOAG data sets that can be used to classify any particles detected by PPD-HS. Classification results show that the PPD-HS can successfully discriminate between spherical and aspherical particles, with misclassification below 5% for diameters >3μm. This phase discrimination method is subsequently applied to classify simulated cloud particles produced in a continuous flow diffusion chamber setup. We report observations of small, near-spherical ice crystals at early stages of the ice nucleation experiments, where shape analysis fails to correctly determine the particle phase. Nevertheless, in the case of simultaneous presence of cloud droplets and ice crystals, the introduced particle shape indicators allow for a clear distinction between these two classes, independent of optical particle size. From our laboratory experiments we conclude that PPD-HS constitutes a powerful new instrument to size and discriminate the phase of cloud hydrometeors. The working principle of PPD-HS forms a basis for future instruments to study microphysical properties of atmospheric mixed-phase clouds that represent a major source of uncertainty in aerosol-indirect effect for future climate projections..Peer reviewe

Personality Trait Differences Between Traditional and Social Entrepreneurs

Purpose This research seeks to identify personality trait differences between social and traditional entrepreneurs. Design/Methodology The Durham Business School’s General Enterprise Tendencies (GET) test was chosen to measure an individual’s entrepreneurial personality. The choice was based on the test’s established use within industry and its ability to measure traits most commonly considered ‘entrepreneurial’ by the extant literature. The test was adapted for this study and distributed to both social and traditional entrepreneurs. The results were then statistically analysed to test for significant differences between the two groups. Findings It was found that social entrepreneurs exhibited statistically significantly higher levels of creativity, risk taking, and need for autonomy than traditional entrepreneurs. The results were then discussed critically in light of the literature. Limitations The modest sample size was the main limitation of the research. In addition, the sample set was fairly culturally homogeneous. It has been recommended that an additional test be carried out with a larger sample size, consisting of a more culturally diverse range of participants, in order to improve the generalisation of the findings. Originality/Value This research provides new insights into personality trait differences between social and traditional entrepreneurs and is particularly useful to those with an interest in entrepreneurial orientation and those interested in the identification and development of social entrepreneurs

The Leishmania major BBSome subunit BBS1 is essential for parasite virulence in the mammalian host

Bardet–Biedl syndrome (BBS) is a human genetic disorder with a spectrum of symptoms caused by primary cilium dysfunction. The disease is caused by mutations in one of at least 17 identified genes, of which seven encode subunits of the BBSome, a protein complex required for specific trafficking events to and from the primary cilium. The molecular mechanisms associated with BBSome function remain to be fully elucidated. Here, we generated null and complemented mutants of the BBSome subunit BBS1 in the protozoan parasite, Leishmania. In the absence of BBS1, extracellular parasites have no apparent defects in growth, flagellum assembly, motility or differentiation in vitro but there is accumulation of vacuole-like structures close to the flagellar pocket. Infectivity of these parasites for macrophages in vitro is reduced compared with wild-type controls but the null parasites retain the ability to differentiate to the intracellular amastigote stage. However, infectivity of BBS1 null parasites is severely compromised in a BALB/c mouse footpad model. We hypothesize that the absence of BBS1 in Leishmania leads to defects in specific trafficking events that affect parasite persistence in the host. This is the first report of an association between the BBSome complex and pathogen infectivity

Interactome comparison of human embryonic stem cell lines with the inner cell mass and trophectoderm

Networks of interacting co-regulated genes distinguish the inner cell mass (ICM) from the differentiated trophectoderm (TE) in the preimplantation blastocyst, in a species specific manner. In mouse the ground state pluripotency of the ICM appears to be maintained in murine embryonic stem cells (ESCs) derived from the ICM. This is not the case for human ESCs. In order to gain insight into this phenomenon, we have used quantitative network analysis to identify how similar human (h)ESCs are to the human ICM. Using the hESC lines MAN1, HUES3 and HUES7 we have shown that all have only a limited overlap with ICM specific gene expression, but that this overlap is enriched for network properties that correspond to key aspects of function including transcription factor activity and the hierarchy of network modules. These analyses provide an important framework which highlights the developmental origins of hESCs

Exploring patterns of error in acute care using framework analysis

Background: Junior doctors are often the first responders to deteriorating patients in hospital. In the high-stakes and time-pressured context of acute care, the propensity for error is high. This study aimed to identify the main subject areas in which junior doctors' acute care errors occur, and cross-reference the errors with Reason's Generic Error Modelling System (GEMS). GEMS categorises errors according to the underlying cognitive processes, and thus provides insight into the causative factors. The overall aim of this study was to identify patterns in junior doctors' acute care errors in order to enhance understanding and guide the development of educational strategies. Methods: This observational study utilised simulated acute care scenarios involving junior doctors dealing with a range of emergencies. Scenarios and the subsequent debriefs were video-recorded. Framework analysis was used to categorise the errors according to eight inductively-developed key subject areas. Subsequently, a multi-dimensional analysis was performed which cross-referenced the key subject areas with an earlier categorisation of the same errors using GEMS. The numbers of errors in each category were used to identify patterns of error. Results: Eight key subject areas were identified; hospital systems, prioritisation, treatment, ethical principles, procedural skills, communication, situation awareness and infection control. There was a predominance of rule-based mistakes in relation to the key subject areas of hospital systems, prioritisation, treatment and ethical principles. In contrast, procedural skills, communication and situation awareness were more closely associated with skill-based slips and lapses. Knowledge-based mistakes were less frequent but occurred in relation to hospital systems and procedural skills. Conclusions: In order to improve the management of acutely unwell patients by junior doctors, medical educators must understand the causes of common errors. Adequate knowledge alone does not ensure prompt and appropriate management and referral. The teaching of acute care skills may be enhanced by encouraging medical educators to consider the range of potential error types, and their relationships to particular tasks and subjects. Rule-based mistakes may be amenable to simulation-based training, whereas skill-based slips and lapses may be reduced using strategies designed to raise awareness of the interplay between emotion, cognition and behaviour.</p

Exploring patterns of error in acute care using framework analysis

Background: Junior doctors are often the first responders to deteriorating patients in hospital. In the high-stakes and time-pressured context of acute care, the propensity for error is high. This study aimed to identify the main subject areas in which junior doctors' acute care errors occur, and cross-reference the errors with Reason's Generic Error Modelling System (GEMS). GEMS categorises errors according to the underlying cognitive processes, and thus provides insight into the causative factors. The overall aim of this study was to identify patterns in junior doctors' acute care errors in order to enhance understanding and guide the development of educational strategies. Methods: This observational study utilised simulated acute care scenarios involving junior doctors dealing with a range of emergencies. Scenarios and the subsequent debriefs were video-recorded. Framework analysis was used to categorise the errors according to eight inductively-developed key subject areas. Subsequently, a multi-dimensional analysis was performed which cross-referenced the key subject areas with an earlier categorisation of the same errors using GEMS. The numbers of errors in each category were used to identify patterns of error. Results: Eight key subject areas were identified; hospital systems, prioritisation, treatment, ethical principles, procedural skills, communication, situation awareness and infection control. There was a predominance of rule-based mistakes in relation to the key subject areas of hospital systems, prioritisation, treatment and ethical principles. In contrast, procedural skills, communication and situation awareness were more closely associated with skill-based slips and lapses. Knowledge-based mistakes were less frequent but occurred in relation to hospital systems and procedural skills. Conclusions: In order to improve the management of acutely unwell patients by junior doctors, medical educators must understand the causes of common errors. Adequate knowledge alone does not ensure prompt and appropriate management and referral. The teaching of acute care skills may be enhanced by encouraging medical educators to consider the range of potential error types, and their relationships to particular tasks and subjects. Rule-based mistakes may be amenable to simulation-based training, whereas skill-based slips and lapses may be reduced using strategies designed to raise awareness of the interplay between emotion, cognition and behaviour.</p

Exploring patterns of error in acute care using framework analysis

Background: Junior doctors are often the first responders to deteriorating patients in hospital. In the high-stakes and time-pressured context of acute care, the propensity for error is high. This study aimed to identify the main subject areas in which junior doctors' acute care errors occur, and cross-reference the errors with Reason's Generic Error Modelling System (GEMS). GEMS categorises errors according to the underlying cognitive processes, and thus provides insight into the causative factors. The overall aim of this study was to identify patterns in junior doctors' acute care errors in order to enhance understanding and guide the development of educational strategies. Methods: This observational study utilised simulated acute care scenarios involving junior doctors dealing with a range of emergencies. Scenarios and the subsequent debriefs were video-recorded. Framework analysis was used to categorise the errors according to eight inductively-developed key subject areas. Subsequently, a multi-dimensional analysis was performed which cross-referenced the key subject areas with an earlier categorisation of the same errors using GEMS. The numbers of errors in each category were used to identify patterns of error. Results: Eight key subject areas were identified; hospital systems, prioritisation, treatment, ethical principles, procedural skills, communication, situation awareness and infection control. There was a predominance of rule-based mistakes in relation to the key subject areas of hospital systems, prioritisation, treatment and ethical principles. In contrast, procedural skills, communication and situation awareness were more closely associated with skill-based slips and lapses. Knowledge-based mistakes were less frequent but occurred in relation to hospital systems and procedural skills. Conclusions: In order to improve the management of acutely unwell patients by junior doctors, medical educators must understand the causes of common errors. Adequate knowledge alone does not ensure prompt and appropriate management and referral. The teaching of acute care skills may be enhanced by encouraging medical educators to consider the range of potential error types, and their relationships to particular tasks and subjects. Rule-based mistakes may be amenable to simulation-based training, whereas skill-based slips and lapses may be reduced using strategies designed to raise awareness of the interplay between emotion, cognition and behaviour.</p