The joint influence of personal achievement goals and classroom goal structures on achievement-relevant outcomes

The authors provide an analytic framework for studying the joint influence of personal achievement goals and classroom goal structures on achievement-relevant outcomes. This framework encompasses 3 models (the direct effect model, indirect effect model, and interaction effect model), each of which addresses a different aspect of the joint influence of the 2 goal levels. These 3 models were examined together with a sample of 1,578 Japanese junior high and high school students from 47 classrooms. Results provided support for each of the 3 models: Classroom goal structures were not only direct, but also indirect predictors of intrinsic motivation and academic self-concept, and some cross-level interactions between personal achievement goals and classroom goal structures were observed (indicating both goal match and goal mismatch effects). A call is made for more research that takes into consideration achievement goals at both personal and structural levels of representation. (PsycINFO Database Record (c) 2012 APA, all rights reserved)(journal abstract)

Evaluation of reach and grasp robot-assisted therapy suggests similar functional recovery patterns on proximal and distal arm segments in sub-acute hemiplegia

This paper provides some additional evidence in support of the hypothesis that robot therapies are clinically beneficial in neurorehabilitation. Although only 4 subjects were included in the study, the design of the intervention and the measures were done so as to minimise bias. The results are presented as single case studies, and can only be interpreted as such due to the study size. The intensity of intervention was 16 hours and the therapy philosophy (based on Carr and Shepherd) was that coordinated movements are preferable to joint based therapies, and that coordinating distal movements (in this case grasps) helps not only to recover function in these areas, but has greater value since the results are immediately transferable to daily skills such as reach and grasp movements.

Fire history and the Global Charcoal Database: a new tool for hypothesis testing and data exploration

Version 1 of the Global Charcoal Database is now available for regional fire history reconstructions, data exploration, hypothesis testing, and evaluation of coupled climate–vegetation–fire model simulations. The charcoal database contains over 400 radiocarbon-dated records that document changes in charcoal abundance during the Late Quaternary. The aim of this public database is to stimulate cross-disciplinary research in fire sciences targeted at an increased understanding of the controls and impacts of natural and anthropogenic fire regimes on centennial-to-orbital timescales. We describe here the data standardization techniques for comparing multiple types of sedimentary charcoal records. Version 1 of the Global Charcoal Database has been used to characterize global and regional patterns in fire activity since the last glacial maximum. Recent studies using the charcoal database have explored the relation between climate and fire during periods of rapid climate change, including evidence of fire activity during the Younger Dryas Chronozone, and during the past two millennia.

An integrated multi-stage model of knowledge management in international joint ventures: identifying a trigger for knowledge exploration and knowledge harvest

This paper examines the evolution of knowledge management from the initial knowledge migration stage, through adaptation and creation, to the reverse knowledge migration stage in international joint ventures (IJVs). While many studies have analyzed these stages (mostly focusing on knowledge transfer), we investigated the path-dependent nature of knowledge flow in IJVs. The results from the empirical analysis based on a survey of 136 Korean parent companies of IJVs reveal that knowledge management in IJVs follows a sequential, multi-stage process, and that the knowledge transferred from parents to IJVs must first be adapted within its new environment before it reaches the creation stage. We also found that only created knowledge is transferred back to parents.

Gaussian anamorphosis in the analysis step of the EnKF: a joint state-variable/observation approach

The analysis step of the (ensemble) Kalman filter is optimal when (1) the distribution of the background is Gaussian, (2) state variables and observations are related via a linear operator, and (3) the observational error is of additive nature and has Gaussian distribution. When these conditions are largely violated, a pre-processing step known as Gaussian anamorphosis (GA) can be applied. The objective of this procedure is to obtain state variables and observations that better fulfil the Gaussianity conditions in some sense. In this work we analyse GA from a joint perspective, paying attention to the effects of transformations in the joint state variable/observation space. First, we study transformations for state variables and observations that are independent from each other. Then, we introduce a targeted joint transformation with the objective to obtain joint Gaussianity in the transformed space. We focus primarily in the univariate case, and briefly comment on the multivariate one. A key point of this paper is that, when (1)-(3) are violated, using the analysis step of the EnKF will not recover the exact posterior density in spite of any transformations one may perform. These transformations, however, provide approximations of different quality to the Bayesian solution of the problem. Using an example in which the Bayesian posterior can be analytically computed, we assess the quality of the analysis distributions generated after applying the EnKF analysis step in conjunction with different GA options. The value of the targeted joint transformation is particularly clear for the case when the prior is Gaussian, the marginal density for the observations is close to Gaussian, and the likelihood is a Gaussian mixture.

Joint multiple dictionary learning for tensor sparse coding

Traditional dictionary learning algorithms are used for finding a sparse representation on high dimensional data by transforming samples into a one-dimensional (1D) vector. This 1D model loses the inherent spatial structure property of data. An alternative solution is to employ Tensor Decomposition for dictionary learning on their original structural form —a tensor— by learning multiple dictionaries along each mode and the corresponding sparse representation in respect to the Kronecker product of these dictionaries. To learn tensor dictionaries along each mode, all the existing methods update each dictionary iteratively in an alternating manner. Because atoms from each mode dictionary jointly make contributions to the sparsity of tensor, existing works ignore atoms correlations between different mode dictionaries by treating each mode dictionary independently. In this paper, we propose a joint multiple dictionary learning method for tensor sparse coding, which explores atom correlations for sparse representation and updates multiple atoms from each mode dictionary simultaneously. In this algorithm, the Frequent-Pattern Tree (FP-tree) mining algorithm is employed to exploit frequent atom patterns in the sparse representation. Inspired by the idea of K-SVD, we develop a new dictionary update method that jointly updates elements in each pattern. Experimental results demonstrate our method outperforms other tensor based dictionary learning algorithms.

JULES-crop: a parametrisation of crops in the Joint UK Land Environment Simulator

Studies of climate change impacts on the terrestrial biosphere have been completed without recognition of the integrated nature of the biosphere. Improved assessment of the impacts of climate change on food and water security requires the development and use of models not only representing each component but also their interactions. To meet this requirement the Joint UK Land Environment Simulator (JULES) land surface model has been modified to include a generic parametrisation of annual crops. The new model, JULES-crop, is described and evaluation at global and site levels for the four globally important crops; wheat, soybean, maize and rice. JULES-crop demonstrates skill in simulating the inter-annual variations of yield for maize and soybean at the global and country levels, and for wheat for major spring wheat producing countries. The impact of the new parametrisation, compared to the standard configuration, on the simulation of surface heat fluxes is largely an alteration of the partitioning between latent and sensible heat fluxes during the later part of the growing season. Further evaluation at the site level shows the model captures the seasonality of leaf area index, gross primary production and canopy height better than in the standard JULES. However, this does not lead to an improvement in the simulation of sensible and latent heat fluxes. The performance of JULES-crop from both an Earth system and crop yield model perspective is encouraging. However, more effort is needed to develop the parametrisation of the model for specific applications. Key future model developments identified include the introduction of processes such as irrigation and nitrogen limitation which will enable better representation of the spatial variability in yield.

Exploration of relational factors: Sino-foreign joint-venture partnering

Purpose – Despite recent threats of economic contraction, China still offers attractive opportunities for foreign companies seeking to expand their business activities through joint venturing (JV) partnering entry strategies. Recent research has indicated a growing recognition of the importance of relational factors in JV partnering. The purpose of this paper is to build on recent research findings that identify critical relation success factors in JVs and explores these in the context of a Hong Kong-based civil aviation services company seeking to expand business activities in Greater China. Design/methodology/approach – While the extant management literature focuses primarily on factors relevant to the inter-partner relationship between partners in the formation stage of a joint venture, this research takes a dynamic stakeholder perspective in respect of the relevant relational factors over the evolution of a partnership. The research described in this paper is based on a case-based study that identifies and examines the relevance and importance of uniquely Chinese factors such as guanxi, renqing and mianzi in the specific context of a strategic partnering relationship. Findings – This phenomenological study provides empirical evidence of critical linkages of these to intrinsically Chinese notions of guanxi, mianzi and renqing – it links these to key strategic partnering success factors identified to be trust, conflict resolution, commitment and cooperation. This study thereby reinforces the importance of the uniquely Chinese relational context in cross-border JVs. Moreover, the research findings suggest that these factors underpin the dynamic bi-directional stakeholder relationship in a Sino-foreign strategic partnership. Originality/value – This study conceptually links the uniquely Chinese relational factors (guanxi, mianzi and renqing) to key success factors supporting the establishment of a strategic partnership in a Sino-foreign context; moreover, it contributes empirical evidence substantiating the proposed conceptual linkage.

Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer clouds using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances under conditions when precipitation does not reach the surface. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievals using synthetic measurements from large-eddy simulation snapshots of cumulus under stratocumulus, where cloud water path is retrieved with an error of 31 g m−2 . The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the Northeast Pacific. Here, retrieved cloud water path agrees well with independent three-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m−2.

Joint data assimilation of satellite reflectance and net ecosystem exchange data constrains ecosystem carbon fluxes at a high-elevation subalpine forest

We utilized an ecosystem process model (SIPNET, simplified photosynthesis and evapotranspiration model) to estimate carbon fluxes of gross primary productivity and total ecosystem respiration of a high-elevation coniferous forest. The data assimilation routine incorporated aggregated twice-daily measurements of the net ecosystem exchange of CO2 (NEE) and satellite-based reflectance measurements of the fraction of absorbed photosynthetically active radiation (fAPAR) on an eight-day timescale. From these data we conducted a data assimilation experiment with fifteen different combinations of available data using twice-daily NEE, aggregated annual NEE, eight-day f AP AR, and average annual fAPAR. Model parameters were conditioned on three years of NEE and fAPAR data and results were evaluated to determine the information content from the different combinations of data streams. Across the data assimilation experiments conducted, model selection metrics such as the Bayesian Information Criterion and Deviance Information Criterion obtained minimum values when assimilating average annual fAPAR and twice-daily NEE data. Application of wavelet coherence analyses showed higher correlations between measured and modeled fAPAR on longer timescales ranging from 9 to 12 months. There were strong correlations between measured and modeled NEE (R2, coefficient of determination, 0.86), but correlations between measured and modeled eight-day fAPAR were quite poor (R2 = −0.94). We conclude that this inability to determine fAPAR on eight-day timescale would improve with the considerations of the radiative transfer through the plant canopy. Modeled fluxes when assimilating average annual fAPAR and annual NEE were comparable to corresponding results when assimilating twice-daily NEE, albeit at a greater uncertainty. Our results support the conclusion that for this coniferous forest twice-daily NEE data are a critical measurement stream for the data assimilation. The results from this modeling exercise indicate that for this coniferous forest, average annuals for satellite-based fAPAR measurements paired with annual NEE estimates may provide spatial detail to components of ecosystem carbon fluxes in proximity of eddy covariance towers. Inclusion of other independent data streams in the assimilation will also reduce uncertainty on modeled values.

Mens rea in joint enterprise: a role for endorsement?

This paper argues that the problems commonly associated with the joint enterprise doctrine might be alleviated by supplementing the cognitive mens rea standard of foresight with a volitional element that looks to how the defendant related to the foreseen risk. A re-examination of the case law suggests that a mens rea conception of foresight plus endorsement might be within interpretative reach. The paper considers possible objections to such a development but ultimately rejects them. It concludes that it is not necessary to wait for Parliament to put in place reforms: joint enterprise is a creature of the common law, and the common law is able to tame it unaided.

On the evolutionary origins of obesity: a new hypothesis

Obesity is an escalating threat of pandemic proportions, currently affecting billions of people worldwide and exerting a devastating socioeconomic influence in industrialized countries. Despite intensive efforts to curtail obesity, results have proved disappointing. Although it is well recognized that obesity is a result of gene-environment interactions and that predisposition to obesity lies predominantly in our evolutionary past, there is much debate as to the precise nature of how our evolutionary past contributed to obesity. The “thrifty genotype” hypothesis suggests that obesity in industrialized countries is a throwback to our ancestors having undergone positive selection for genes that favored energy storage as a consequence of the cyclical episodes of famine and surplus after the advent of farming 10 000 years ago. Conversely, the “drifty genotype” hypothesis contends that the prevalence of thrifty genes is not a result of positive selection for energy-storage genes but attributable to genetic drift resulting from the removal of predative selection pressures. Both theories, however, assume that selection pressures the ancestors of modern humans living in western societies faced were the same. Moreover, neither theory adequately explains the impact of globalization and changing population demographics on the genetic basis for obesity in developed countries, despite clear evidence for ethnic variation in obesity susceptibility and related metabolic disorders. In this article, we propose that the modern obesity pandemic in industrialized countries is a result of the differential exposure of the ancestors of modern humans to environmental factors that began when modern humans left Africa around 70 000 years ago and migrated through the globe, reaching the Americas around 20 000 years ago. This article serves to elucidate how an understanding of ethnic differences in genetic susceptibility to obesity and the metabolic syndrome, in the context of historic human population redistribution, could be used in the treatment of obesity in industrialized countries