Watch and Learn: Seeing Is Better than Doing when Acquiring Consecutive Motor Tasks

During motor adaptation learning, consecutive physical practice of two different tasks compromises the retention of the first. However, there is evidence that observational practice, while still effectively aiding acquisition, will not lead to interference and hence prove to be a better practice method. Observers and Actors practised in a clockwise (Task A) followed by a counterclockwise (Task B) visually rotated environment, and retention was immediately assessed. An Observe-all and Act-all group were compared to two groups who both physically practised Task A, but then only observed (ObsB) or did not see or practice Task B (NoB). The two observer groups and the NoB control group better retained Task A than Actors, although importantly only the observer groups learnt Task B. RT data and explicit awareness of the rotation suggested that the observers had acquired their respective tasks in a more strategic manner than Actor and Control groups. We conclude that observational practice benefits learning of multiple tasks more than physical practice due to the lack of updating of implicit, internal models for aiming in the former

Testing a model of UK growth: A role for R&D subsidies

Debate continues on the economic growth effects of direct support for business R&D. We set out aDSGE model of the UK in which direct R&D subsidies drive total factor productivity (TFP) throughtheir incentive effects on agents' optimal decisions. We estimate and test the model by IndirectInference, finding that this model can account for the joint behaviour of UK output and TFP. The model allows us to analyse the short-run impact of R&D subsidies on TFP and to quantify the longer-term impacts of R&D subsidy shocks on output. We also determine uncertainty bounds for key growth parameters using Monte Carlo analysis. Our results show that even temporary policy cuts to R&D funding have long-lasting impacts on UK economic growth. The findings are of great policy relevance given ongoing debate around the future UK innovation environment and the novel application of indirect inference to this question

A log-normal spectral analysis of inorganic grain-size distributions from a Canadian boreal lake core: Towards refining depositional process proxy data from high latitude lakes

Better methods for interpreting grain size spectra will enhance current understanding of past transport–depositional processes. A high-resolution inorganic grain-size dataset has been measured from a freeze core extracted from ‘Alberta Lake E’ a boreal fresh water lake 40 km east of the Athabasca Oil Sands in north-eastern Alberta, Canada. The grain-size spectra are remarkably consistent throughout the core, exhibiting a structure comprising six persistent grain-size distributions below ca 250 μm, plus a rare medium-sand distribution. Automated deconvolution of the grain-size spectra produced poor results. Constraining the modes of two of the distributions produced deconvolution solutions that were statistically excellent and consistent with the structure of each spectrum. Statistical analysis of the ‘constrained’ solutions indicates that deconvolution successfully extracted independent grain-size populations. Conversely, the multimodal spectra generate traditional measures (for example, mean grain size) that are inconsistent combinations of different individual populations, and thus are poor proxies of transport–depositional processes. Alberta Lake E is situated in a boreal wetland landscape where sediment delivery is dominated by overland flow transport during spring melt. This context means that the Alberta Lake E grain-size spectra can be interpreted to reflect: (i) a bedload component transported during short-duration high discharge events that reflect the intensity of the melt; and (ii) a finer suspended load component representing material whose magnitude is controlled by the volume of the spring melt. Stratigraphically, bedload and suspended load populations demonstrate different short-wavelength and long-wavelength cyclicity, suggesting that spring melt is likely to be driven by cyclic external forcing factors. The links between the grain-size spectra and spring melt have potential for generating proxy records that better capture the external controls over spring melt in boreal systems, and the risks associated with these energetic hydrodynamics. This is exemplified by the coarsest Alberta Lake E distributions, which indicate that more intense spring melt dynamics occurred in pre-historical times

‘Cytology-on-a-chip’ based sensors for monitoring of potentially malignant oral lesions

Despite significant advances in surgical procedures and treatment, long-term prognosis for patients with oral cancer remains poor, with survival rates among the lowest of major cancers. Better methods are desperately needed to identify potential malignancies early when treatments are more effective. Objective To develop robust classification models from cytology-on-a-chip measurements that mirror diagnostic performance of gold standard approach involving tissue biopsy. Materials and methods Measurements were recorded from 714 prospectively recruited patients with suspicious lesions across 6 diagnostic categories (each confirmed by tissue biopsy -histopathology) using a powerful new ‘cytology-on-a-chip’ approach capable of executing high content analysis at a single cell level. Over 200 cellular features related to biomarker expression, nuclear parameters and cellular morphology were recorded per cell. By cataloging an average of 2000 cells per patient, these efforts resulted in nearly 13 million indexed objects. Results Binary “low-risk”/“high-risk” models yielded AUC values of 0.88 and 0.84 for training and validation models, respectively, with an accompanying difference in sensitivity + specificity of 6.2%. In terms of accuracy, this model accurately predicted the correct diagnosis approximately 70% of the time, compared to the 69% initial agreement rate of the pool of expert pathologists. Key parameters identified in these models included cell circularity, Ki67 and EGFR expression, nuclear-cytoplasmic ratio, nuclear area, and cell area. Conclusions This chip-based approach yields objective data that can be leveraged for diagnosis and management of patients with PMOL as well as uncovering new molecular-level insights behind cytological differences across the OED spectrum

The social biography of antibiotic use in smallholder dairy farms in India

Background Antimicrobial resistance (AMR) has been identified as one of the major threats to global health, food security and development today. While there has been considerable attention about the use and misuse of antibiotics amongst human populations in both research and policy environments, there is no definitive estimate of the extent of misuse of antibiotics in the veterinary sector and its contribution to AMR in humans. In this study, we explored the drivers ofirrational usage of verterinary antibiotics in the dairy farming sector in peri-urban India. Methods and materials The study was conducted in the peri-urban belts of Ludhiana, Guwahati and Bangalore. A total of 54 interviews (formal and non-formal) were carried out across these three sites. Theme guides were developed to explore different drivers of veterinary antimicrobial use. Data was audio recorded and transcribed. Analysis of the coded data set was carried out using AtlasTi. Version 7. Themes emerged inductively from the set of codes. Results Findings were presented based on concept of ‘levels of analyses’. Emergent themes were categorised as individual, health systems, and policy level drivers. Low level of knowledge related to antibiotics among farmers, active informal service providers, direct marketing of drugs to the farmers and easily available antibiotics, dispensed without appropriate prescriptions contributed to easy access to antibiotics, and were identified to be the possible drivers contributing to the non-prescribed and self-administered use of antibiotics in the dairy farms. Conclusions Smallholding dairy farmers operated within very small margins of profits. The paucity of formal veterinary services at the community level, coupled with easy availability of antibiotics and the need to ensure profits and minimise losses, promoted non-prescribed antibiotic consumption. It is essential that these local drivers of irrational antibiotic use are understood in order to develop interventions and policies that seek to reduce antibiotic misuse

Mapping the Relationship Among Political Ideology, CSR Mindset, and CSR Strategy: A Contingency Perspective Applied to Chinese Managers

The literature on antecedents of corporate social responsibility (CSR) strategies of firms has been predominately content driven. Informed by the managerial sense-making process perspective, we develop a contingency theoretical framework explaining how political ideology of managers affects the choice of CSR strategy for their firms through their CSR mindset. We also explain to what extent the outcome of this process is shaped by the firm’s internal institutional arrangements and external factors impacting on the firm. We develop and test several hypotheses using data collected from 129 Chinese managers. The results show that managers with a stronger socialist ideology are likely to develop a mindset favouring CSR, which induces the adoption of a proactive CSR strategy. The CSR mindset mediates the link between socialist ideology and CSR strategy. The strength of the relationship between the CSR mindset and the choice of CSR strategy is moderated by customer response to CSR, industry competition, the role of government, and CSR-related managerial incentives

What role for human capital in the growth process: new evidence from endogenous latent factor panel quantile regressions

The estimates for the human capital effect in cross-country growth regressions have been subject of considerable controversy. We argue that human capital is intrinsically a multidimensional construct. We construct human capital measure by combining available alternative proxies via confirmatory factor analysis. Using panel data endogenous quantile regression methods we analyse the whole conditional growth distribution by simultaneously accounting for the potential endogeneity of human capital and country specific effects. Our results conform to theoretical expectations and we are able to demonstrate the beneficial effect of both the measurement approach and the endogeneity correction on the derivation of theoretically consistent estimates