How do banks assess entrepreneurial competence? The role of voluntary information disclosure

This research adds to the literature on relationship lending in the small business context by discussing the roles of entrepreneurial competence and voluntarily disclosed information as determinants of credit access. More specifically, we propose that the loan manager’s evaluation of the information voluntarily disclosed by the entrepreneur is an important complement to publicly available financial data and soft information collected through observation and third parties in framing the loan manager’s perception of the entrepreneur’s competence. Further, we argue that banks charge lower interest rates if the loan manager perceives the entrepreneur to be competent. Econometric analysis based on 433 bank-firm relationships supports these hypothesised relationships. The results imply that entrepreneurs need to communicate their competence effectively to loan managers, and that banks should utilise their loan managers’ personal evaluations as inputs to lending decisions

The aggregation of cytochrome C may be linked to its flexibility during refolding

Large-scale expression of biopharmaceutical proteins in cellular hosts results in production of large insoluble mass aggregates. In order to generate functional product, these aggregates require further processing through refolding with denaturant, a process in itself that can result in aggregation. Using a model folding protein, cytochrome C, we show how an increase in final denaturant concentration decreases the propensity of the protein to aggregate during refolding. Using polarised fluorescence anisotropy, we show how reduced levels of aggregation can be achieved by increasing the period of time the protein remains flexible during refolding, mediated through dilution ratios. This highlights the relationship between the flexibility of a protein and its propensity to aggregate. We attribute this behaviour to the preferential urea-residue interaction, over self-association between molecules

An upper limit on the contribution of accreting white dwarfs to the type Ia supernova rate

There is wide agreement that Type Ia supernovae (used as standard candles for cosmology) are associated with the thermonuclear explosions of white dwarf stars. The nuclear runaway that leads to the explosion could start in a white dwarf gradually accumulating matter from a companion star until it reaches the Chandrasekhar limit, or could be triggered by the merger of two white dwarfs in a compact binary system. The X-ray signatures of these two possible paths are very different. Whereas no strong electromagnetic emission is expected in the merger scenario until shortly before the supernova, the white dwarf accreting material from the normal star becomes a source of copious X-rays for ~1e7 yr before the explosion. This offers a means of determining which path dominates. Here we report that the observed X-ray flux from six nearby elliptical galaxies and galaxy bulges is a factor of ~30-50 less than predicted in the accretion scenario, based upon an estimate of the supernova rate from their K-band luminosities. We conclude that no more than ~5 per cent of Type Ia supernovae in early type galaxies can be produced by white dwarfs in accreting binary systems, unless their progenitors are much younger than the bulk of the stellar population in these galaxies, or explosions of sub-Chandrasekhar white dwarfs make a significant contribution to the supernova rate.Comment: 10 pages, 1 tabl

Prime movers : mechanochemistry of mitotic kinesins

Mitotic spindles are self-organizing protein machines that harness teams of multiple force generators to drive chromosome segregation. Kinesins are key members of these force-generating teams. Different kinesins walk directionally along dynamic microtubules, anchor, crosslink, align and sort microtubules into polarized bundles, and influence microtubule dynamics by interacting with microtubule tips. The mechanochemical mechanisms of these kinesins are specialized to enable each type to make a specific contribution to spindle self-organization and chromosome segregation

Chronic non-specific low back pain - sub-groups or a single mechanism?

Copyright 2008 Wand and O'Connell; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background: Low back pain is a substantial health problem and has subsequently attracted a considerable amount of research. Clinical trials evaluating the efficacy of a variety of interventions for chronic non-specific low back pain indicate limited effectiveness for most commonly applied interventions and approaches. Discussion: Many clinicians challenge the results of clinical trials as they feel that this lack of effectiveness is at odds with their clinical experience of managing patients with back pain. A common explanation for this discrepancy is the perceived heterogeneity of patients with chronic non-specific low back pain. It is felt that the effects of treatment may be diluted by the application of a single intervention to a complex, heterogeneous group with diverse treatment needs. This argument presupposes that current treatment is effective when applied to the correct patient. An alternative perspective is that the clinical trials are correct and current treatments have limited efficacy. Preoccupation with sub-grouping may stifle engagement with this view and it is important that the sub-grouping paradigm is closely examined. This paper argues that there are numerous problems with the sub-grouping approach and that it may not be an important reason for the disappointing results of clinical trials. We propose instead that current treatment may be ineffective because it has been misdirected. Recent evidence that demonstrates changes within the brain in chronic low back pain sufferers raises the possibility that persistent back pain may be a problem of cortical reorganisation and degeneration. This perspective offers interesting insights into the chronic low back pain experience and suggests alternative models of intervention. Summary: The disappointing results of clinical research are commonly explained by the failure of researchers to adequately attend to sub-grouping of the chronic non-specific low back pain population. Alternatively, current approaches may be ineffective and clinicians and researchers may need to radically rethink the nature of the problem and how it should best be managed

Cognitive loading affects motor awareness and movement kinematics but not locomotor trajectories during goal-directed walking in a virtual reality environment.

The primary purpose of this study was to investigate the effects of cognitive loading on movement kinematics and trajectory formation during goal-directed walking in a virtual reality (VR) environment. The secondary objective was to measure how participants corrected their trajectories for perturbed feedback and how participants' awareness of such perturbations changed under cognitive loading. We asked 14 healthy young adults to walk towards four different target locations in a VR environment while their movements were tracked and played back in real-time on a large projection screen. In 75% of all trials we introduced angular deviations of ±5° to ±30° between the veridical walking trajectory and the visual feedback. Participants performed a second experimental block under cognitive load (serial-7 subtraction, counter-balanced across participants). We measured walking kinematics (joint-angles, velocity profiles) and motor performance (end-point-compensation, trajectory-deviations). Motor awareness was determined by asking participants to rate the veracity of the feedback after every trial. In-line with previous findings in natural settings, participants displayed stereotypical walking trajectories in a VR environment. Our results extend these findings as they demonstrate that taxing cognitive resources did not affect trajectory formation and deviations although it interfered with the participants' movement kinematics, in particular walking velocity. Additionally, we report that motor awareness was selectively impaired by the secondary task in trials with high perceptual uncertainty. Compared with data on eye and arm movements our findings lend support to the hypothesis that the central nervous system (CNS) uses common mechanisms to govern goal-directed movements, including locomotion. We discuss our results with respect to the use of VR methods in gait control and rehabilitation

Converting simulated total dry matter to fresh marketable yield for field vegetables at a range of nitrogen supply levels

Simultaneous analysis of economic and environmental performance of horticultural crop production requires qualified assumptions on the effect of management options, and particularly of nitrogen (N) fertilisation, on the net returns of the farm. Dynamic soil-plant-environment simulation models for agro-ecosystems are frequently applied to predict crop yield, generally as dry matter per area, and the environmental impact of production. Economic analysis requires conversion of yields to fresh marketable weight, which is not easy to calculate for vegetables, since different species have different properties and special market requirements. Furthermore, the marketable part of many vegetables is dependent on N availability during growth, which may lead to complete crop failure under sub-optimal N supply in tightly calculated N fertiliser regimes or low-input systems. In this paper we present two methods for converting simulated total dry matter to marketable fresh matter yield for various vegetables and European growth conditions, taking into consideration the effect of N supply: (i) a regression based function for vegetables sold as bulk or bunching ware and (ii) a population approach for piecewise sold row crops. For both methods, to be used in the context of a dynamic simulation model, parameter values were compiled from a literature survey. Implemented in such a model, both algorithms were tested against experimental field data, yielding an Index of Agreement of 0.80 for the regression strategy and 0.90 for the population strategy. Furthermore, the population strategy was capable of reflecting rather well the effect of crop spacing on yield and the effect of N supply on product grading

The temporal pattern and lifestyle associations of respiratory virus infection in a cohort study spanning the first two years of life

Background: Respiratory virus infection is common in early childhood, and children may be symptomatic or symptom-free. Little is known regarding the association between symptomatic/asymptomatic infection and particular clinical factors such as breastfeeding as well as the consequences of such infection. Method: We followed an unselected cohort of term neonates to two years of age (220 infants at recruitment, 159 who remained in the study to 24 months), taking oral swabs at birth and oropharyngeal swabs at intervals subsequently (at 1.5, 6, 9, 12, 18 and 24 months and in a subset at 3 and 4.5 months) while recording extensive metadata including the presence of respiratory symptoms and breastfeeding status. After 2 years medical notes from the general practitioner were inspected to ascertain whether doctor-diagnosed wheeze had occurred by this timepoint. Multiplex PCR was used to detect a range of respiratory viruses: influenza (A&B), parainfluenza (1–4), bocavirus, human metapneumovirus, rhinovirus, coronavirus (OC43, 229E, NL63, HKU1), adenovirus, respiratory syncytial virus (RSV), and polyomavirus (KI, WU). Logistic regression and generalised estimating equations were used to identify associations between clinical factors and virus detection. Results: Overall respiratory viral incidence increased with age. Rhinovirus was the virus most frequently detected. The detection of a respiratory virus was positively associated with respiratory symptoms, male sex, season, childcare and living with another child. We did not observe breastfeeding (whether assessed as the number of completed months of breastfeeding or current feed status) to be associated with the detection of a respiratory virus. There was no association between early viral infection and doctor-diagnosed wheeze by age 2 years. Conclusion: Asymptomatic and symptomatic viral infection is common in the first 2 years of life with rhinovirus infection being the most common. Whilst there was no association between early respiratory viral infection and doctor-diagnosed wheeze, we have not ruled out an association of early viral infections with later asthma, and long-term follow-up of the cohort continues

Severe stress switches CRF action in the nucleus accumbens from appetitive to aversive.

Stressors motivate an array of adaptive responses ranging from \u27fight or flight\u27 to an internal urgency signal facilitating long-term goals. However, traumatic or chronic uncontrollable stress promotes the onset of major depressive disorder, in which acute stressors lose their motivational properties and are perceived as insurmountable impediments. Consequently, stress-induced depression is a debilitating human condition characterized by an affective shift from engagement of the environment to withdrawal. An emerging neurobiological substrate of depression and associated pathology is the nucleus accumbens, a region with the capacity to mediate a diverse range of stress responses by interfacing limbic, cognitive and motor circuitry. Here we report that corticotropin-releasing factor (CRF), a neuropeptide released in response to acute stressors and other arousing environmental stimuli, acts in the nucleus accumbens of naive mice to increase dopamine release through coactivation of the receptors CRFR1 and CRFR2. Remarkably, severe-stress exposure completely abolished this effect without recovery for at least 90 days. This loss of CRF\u27s capacity to regulate dopamine release in the nucleus accumbens is accompanied by a switch in the reaction to CRF from appetitive to aversive, indicating a diametric change in the emotional response to acute stressors. Thus, the current findings offer a biological substrate for the switch in affect which is central to stress-induced depressive disorders

Why Robots Should Be Social: Enhancing Machine Learning through Social Human-Robot Interaction.

Social learning is a powerful method for cultural propagation of knowledge and skills relying on a complex interplay of learning strategies, social ecology and the human propensity for both learning and tutoring. Social learning has the potential to be an equally potent learning strategy for artificial systems and robots in specific. However, given the complexity and unstructured nature of social learning, implementing social machine learning proves to be a challenging problem. We study one particular aspect of social machine learning: that of offering social cues during the learning interaction. Specifically, we study whether people are sensitive to social cues offered by a learning robot, in a similar way to children's social bids for tutoring. We use a child-like social robot and a task in which the robot has to learn the meaning of words. For this a simple turn-based interaction is used, based on language games. Two conditions are tested: one in which the robot uses social means to invite a human teacher to provide information based on what the robot requires to fill gaps in its knowledge (i.e. expression of a learning preference); the other in which the robot does not provide social cues to communicate a learning preference. We observe that conveying a learning preference through the use of social cues results in better and faster learning by the robot. People also seem to form a "mental model" of the robot, tailoring the tutoring to the robot's performance as opposed to using simply random teaching. In addition, the social learning shows a clear gender effect with female participants being responsive to the robot's bids, while male teachers appear to be less receptive. This work shows how additional social cues in social machine learning can result in people offering better quality learning input to artificial systems, resulting in improved learning performance