Assessment of an osteoblast-like cell line as a model for human primary osteoblasts using Raman spectroscopy

Raman spectroscopy is employed to determine the suitability of the U20S osteoblast-like cell line for use as a model for human primary osteoblasts, with emphasis on the ability of these cell types to replicate their tissue of origin. It was found that both cell types demonstrated early stage mineral deposition that followed significantly different growth patterns. Analysis of the growth pattern and spectral data from primary cells revealed increasing bone quality ratios and a high crystallinity, consistent with previous reports. Conversely the investigation of the U20S osteoblast-like cell line provided evidence of dense multilayered mineralised regions that corresponded more closely to native bone in terms of its crystallinity and bone quality ratios. This finding contradicts previous reports on U20S osteoblast-like cells which have consistently described them as non-osteoinductive when cultured in various conditions on a number of substrates. This work demonstrates the successful application of Raman spectroscopy combined with biological and multivariate analysis for the investigation of osteoblast-like U20S cells and human primary osteoblasts, specifically with focus on the osteoinductive ability of the osteoblast-like cell line and the comparative differences in relation to the primary osteoblasts

A Fuzzy Social Network Analysis Method and a Case Study on Tianya

Social networking service (SNS) has become online service platforms that focus on facilitating the building of social networks among people who share interests, activities, backgrounds, or real-life connections and has had a rapid development in China in the past few years. This paper aims to develop a fuzzy social network service analysis method, which combines graph theory with related fuzzy approach, to analyze the social network structural features and the distribution characteristics of interpersonal nodes in SNS community. A case study on a very famous Chinese tourism BBS-Tianya-is conducted to illustrate and validate the proposed approach. The research findings are as follows: (1) The attraction degrees of various areas in the forum are significantly different; (2) interpersonal nodes in the forum are concentrated relatively; (3) the fuzzy out-degrees and the fuzzy in-degrees of interpersonal nodes in the forum conflict each other; and (4) the distribution of interpersonal nodes is influenced by geographical relations. These findings can directly support social network service management and particularly tourism online service developments. © Springer-Verlag Berlin Heidelberg 2014

Improving the forward kinematics of cable-driven parallel robots through cable angle sensors

This paper presents a sensor fusion method that aims at improving the accuracy of cable-driven planar parallel mechanisms (CDPMs) and simplifying the kinematic resolution. While the end-effector pose of the CDPM is usually obtained with the cable lengths, the proposed method combines the cable length measurement with the cable angle by using a data fusion algorithm. This allows for a resolution based on the loop closure equations and a weighted least squares method. The paper first presents the resolution of the forward kinematics for planar parallel mechanisms using cable angle only. Then, the proposed sensor fusion scheme is detailed. Finally, an experiment comparing the different procedures for obtaining the pose of the CDPM is carried out, in order to demonstrate the efficiency of the proposed fusion method

The acheulean handaxe : More like a bird's song than a beatles' tune?

© 2016 Wiley Periodicals, Inc. KV is supported by the Netherlands Organization for Scientific Research. MC is supported by the Canada Research Chairs Program, the Social Sciences and Humanities Research of Canada, the Canada Foundation for Innovation, the British Columbia Knowledge Development Fund, and Simon Fraser UniversityPeer reviewedPublisher PD

The biological origin of linguistic diversity

In contrast with animal communication systems, diversity is characteristic of almost every aspect of human language. Languages variously employ tones, clicks, or manual signs to signal differences in meaning; some languages lack the noun-verb distinction (e.g., Straits Salish), whereas others have a proliferation of fine-grained syntactic categories (e.g., Tzeltal); and some languages do without morphology (e.g., Mandarin), while others pack a whole sentence into a single word (e.g., Cayuga). A challenge for evolutionary biology is to reconcile the diversity of languages with the high degree of biological uniformity of their speakers. Here, we model processes of language change and geographical dispersion and find a consistent pressure for flexible learning, irrespective of the language being spoken. This pressure arises because flexible learners can best cope with the observed high rates of linguistic change associated with divergent cultural evolution following human migration. Thus, rather than genetic adaptations for specific aspects of language, such as recursion, the coevolution of genes and fast-changing linguistic structure provides the biological basis for linguistic diversity. Only biological adaptations for flexible learning combined with cultural evolution can explain how each child has the potential to learn any human language

Preferences and skills of Indian public sector teachers

With a sample of 700 future public sector primary teachers in India, a Discrete Choice Experiment is used to measure job preferences, particularly regarding location. General skills are also tested. Urban origin teachers and women are more averse to remote locations than rural origin teachers and men respectively. Women would require a 26-73 percent increase in salary for moving to a remote location. The results suggest that existing caste and gender quotas can be detrimental for hiring skilled teachers willing to work in remote locations. The most preferred location is home, which supports decentralised hiring, although this could compromise skills

Modelling for Robust Feedback Control of Fluid Flows

This paper addresses the problem of obtaining low-order models of fluid flows for the purpose of designing robust feedback controllers. This is challenging since whilst many flows are governed by a set of nonlinear, partial differential-algebraic equations (the Navier-Stokes equations), the majority of established control theory assumes models of much greater simplicity, in that they are firstly: linear, secondly: described by ordinary differential equations, and thirdly: finite-dimensional. Linearisation, where appropriate, overcomes the first disparity, but attempts to reconcile the remaining two have proved difficult. This paper addresses these two problems as follows. Firstly, a numerical approach is used to project the governing equations onto a divergence-free basis, thus converting a system of differential-algebraic equations into one of ordinary differential equations. This dispenses with the need for analytical velocity-vorticity transformations, and thus simplifies the modelling of boundary sensing and actuation. Secondly, this paper presents a novel and straightforward approach for obtaining suitable low-order models of fluid flows, from which robust feedback controllers can be synthesised that provide~\emph{a~priori} guarantees of robust performance when connected to the (infinite-dimensional) linearised flow system. This approach overcomes many of the problems inherent in approaches that rely upon model-reduction. To illustrate these methods, a perturbation shear stress controller is designed and applied to plane channel flow, assuming arrays of wall mounted shear-stress sensors and transpiration actuators. DNS results demonstrate robust attenuation of the perturbation shear-stresses across a wide range of Reynolds numbers with a single, linear controller

When is the discretization of a spatially distributed system good enough for control?

Accepted versio

How to increase the potential policy impact of environmental science research

This article highlights eight common issues that limit the policy impact of environmental science research. The article also discusses what environmental scientists can do to resolve these issues, including (1) optimising the directness of their study so that it examines similar processes/populations/environments/ecosystems to that of policy interest; (2) using the most powerful study design possible, to increase confidence in the identified causal mechanisms; (3) selecting a sufficient sample size, to reduce the chance of false positives/negatives and increase policy-makers’ confidence in extrapolation of the findings; (4) minimizing the risk of bias through randomization of study units to treatment and control groups (reducing the risk of selection bias), blinding of study units and investigators (reducing the risk of performance and detection bias), following-up study units from enrolment to study completion (reducing the risk of attrition bias) and prospectively registering the study on a publically-available platform (reducing the risk of reporting and publication bias); (5) proving that statistical analyses meet test assumptions by reporting the results of statistical assumption checks, ideally publishing full datasets online in an open-access format; (6) publishing the research whether statistically significant or not, policy-makers are just as interested in the negative or insignificant results as they are in the positive results; (7) making the study easy to find and use, the title and abstract of an article are of high importance in determining whether articles are examined in detail or not and used to inform policy; (8) contributing towards systematic reviews on environmental topics, to provide policy-makers with comprehensive, reproducible and updateable syntheses of all the evidence on a given topic.</p

A generative inference framework for analysing patterns of cultural change in sparse population data with evidence for fashion trends in LBK culture

Cultural change can be quantified by temporal changes in frequency of different cultural artefacts and it is a central question to identify what underlying cultural transmission processes could have caused the observed frequency changes. Observed changes, however, often describe the dynamics in samples of the population of artefacts, whereas transmission processes act on the whole population. Here we develop a modelling framework aimed at addressing this inference problem. To do so, we firstly generate population structures from which the observed sample could have been drawn randomly and then determine theoretical samples at a later time t2 produced under the assumption that changes in frequencies are caused by a specific transmission process. Thereby we also account for the potential effect of time-averaging processes in the generation of the observed sample. Subsequent statistical comparisons (e.g. using Bayesian inference) of the theoretical and observed samples at t2 can establish which processes could have produced the observed frequency data. In this way, we infer underlying transmission processes directly from available data without any equilibrium assumption. We apply this framework to a dataset describing pottery from settlements of some of the first farmers in Europe (the LBK culture) and conclude that the observed frequency dynamic of different types of decorated pottery is consistent with age-dependent selection, a preference for 'young' pottery types which is potentially indicative of fashion trends