Perceived competence moderates the relation between performance-approach and performance-avoidance goals

In the present research, we conducted 4 studies designed to examine the hypothesis that perceived competence moderates the relation between performance-approach and performance-avoidance goals. Each study yielded supportive data, indicating that the correlation between the 2 goals is lower when perceived competence is high. This pattern was observed at the between- and within-subject level of analysis, with correlational and experimental methods and using both standard and novel achievement goal assessments, multiple operationalizations of perceived competence, and several different types of focal tasks. The findings from this research contribute to the achievement goal literature on theoretical, applied, and methodological fronts and highlight the importance of and need for additional empirical work in this area. (PsycINFO Database Record (c) 2012 APA, all rights reserved)(journal abstract)

Palaeobiology of the medieval population of Albano (Rome, Italy): a combined morphological and biomolecular approach

Recent years have seen increased interest in skeletal populations from the Imperial Roman Age in Italy, but much less is known about diet and standards of living in the subsequent medieval period. To fill this gap, we conducted a morphological analysis of human remains from Albano, an Italian town near Rome, as well as a stable isotope analysis of bone collagen to reconstruct diet. The sample was recovered from a Medieval cemetery (1040–1220 cal. yr. BP) located in the gardens of the historical Palazzo Doria Pamphili in Albano. A minimum number of 40 individuals (31 adults and 9 sub-adults) were examined using standard methods. Though the general health status of the population was good, signs of cribra orbitalia and diffuse enthesopathies were noted during the morphological examination. Stable carbon and nitrogen isotope analyses of the bone collagen from 24 adult humans and three faunal bones indicate that the diet of the population may be described as predominantly terrestrial and C3-plant based although the data for some of the individuals suggest a modest consumption of C4-(millet) based or aquatic proteins. No evidence of significant dietary differences between the sexes was found. The comparison of the isotope data from Albano with those from populations recovered in the same region is consistent with a shift from a terrestrial, possibly plant foods-dominated subsistence in the Early Middle Ages to a diet with a higher contribution from animal proteins, both terrestrial and aquatic, in the Later Middle Ages.

A moving mesh approach for modelling avascular tumour growth

A key step in many numerical schemes for time-dependent partial differential equations with moving boundaries is to rescale the problem to a fixed numerical mesh. An alternative approach is to use a moving mesh that can be adapted to focus on specific features of the model. In this paper we present and discuss two different velocity-based moving mesh methods applied to a two-phase model of avascular tumour growth formulated by Breward et al. (2002) J. Math. Biol. 45(2), 125-152. Each method has one moving node which tracks the moving boundary. The first moving mesh method uses a mesh velocity proportional to the boundary velocity. The second moving mesh method uses local conservation of volume fraction of cells (masses). Our results demonstrate that these moving mesh methods produce accurate results, offering higher resolution where desired whilst preserving the balance of fluxes and sources in the governing equations.

Life before ‘The New Biography’: Modernist biographical methods in the Hogarth Press ‘Books on Tolstoi’ 1920-24

In the early 1920s, before Virginia Woolf wrote her now well-known essays “The New Biography” and “The Art of Biography,” the Hogarth Press published four biographies of Tolstoy. Each of these English translations of Russian works takes a different approach to biographical composition, and as a group they offer multiple and contradictory perspectives on Tolstoy’s character and on the genre of biography in the early twentieth century. These works show that Leonard and Virginia Woolf’s Hogarth Press took a multi-perspectival, modernist approach to publishing literary lives.

Performing knowledge requirements analysis for public organisations in a Virtual Learning Environment: a social network analysis approach

This paper describes an application of Social Network Analysis methods for identification of knowledge demands in public organisations. Affiliation networks established in a postgraduate programme were analysed. The course was executed in a distance education mode and its students worked on public agencies. Relations established among course participants were mediated through a virtual learning environment using Moodle. Data available in Moodle may be extracted using knowledge discovery in databases techniques. Potential degrees of closeness existing among different organisations and among researched subjects were assessed. This suggests how organisations could cooperate for knowledge management and also how to identify their common interests. The study points out that closeness among organisations and research topics may be assessed through affiliation networks. This opens up opportunities for applying knowledge management between organisations and creating communities of practice. Concepts of knowledge management and social network analysis provide the theoretical and methodological basis.

Rainfall estimation by rain gauge-radar combination: a concurrent multiplicative-additive approach

A procedure (concurrent multiplicative-additive objective analysis scheme [CMA-OAS]) is proposed for operational rainfall estimation using rain gauges and radar data. On the basis of a concurrent multiplicative-additive (CMA) decomposition of the spatially nonuniform radar bias, within-storm variability of rainfall and fractional coverage of rainfall are taken into account. Thus both spatially nonuniform radar bias, given that rainfall is detected, and bias in radar detection of rainfall are handled. The interpolation procedure of CMA-OAS is built on Barnes' objective analysis scheme (OAS), whose purpose is to estimate a filtered spatial field of the variable of interest through a successive correction of residuals resulting from a Gaussian kernel smoother applied on spatial samples. The CMA-OAS, first, poses an optimization problem at each gauge-radar support point to obtain both a local multiplicative-additive radar bias decomposition and a regionalization parameter. Second, local biases and regionalization parameters are integrated into an OAS to estimate the multisensor rainfall at the ground level. The procedure is suited to relatively sparse rain gauge networks. To show the procedure, six storms are analyzed at hourly steps over 10,663 km2. Results generally indicated an improved quality with respect to other methods evaluated: a standard mean-field bias adjustment, a spatially variable adjustment with multiplicative factors, and ordinary cokriging.

Plane wave discontinuous Galerkin methods: exponential convergence of the hp-version

We consider the two-dimensional Helmholtz equation with constant coefficients on a domain with piecewise analytic boundary, modelling the scattering of acoustic waves at a sound-soft obstacle. Our discretisation relies on the Trefftz-discontinuous Galerkin approach with plane wave basis functions on meshes with very general element shapes, geometrically graded towards domain corners. We prove exponential convergence of the discrete solution in terms of number of unknowns.

On the threshold of adulthood: a new approach for the use of maturation indicators to assess puberty in adolescents from medieval England

Objectives: This study provides the first large scale analysis of the age at which adolescents in medieval England entered and completed the pubertal growth spurt. This new method has implications for expanding our knowledge of adolescent maturation across different time periods and regions. Methods: In total, 994 adolescent skeletons (10-25 years) from four urban sites in medieval England (AD 900-1550) were analysed for evidence of pubertal stage using new osteological techniques developed from the clinical literature (i.e. hamate hook development, CVM, canine mineralisation, iliac crest ossification, radial fusion). Results: Adolescents began puberty at a similar age to modern children at around 10-12 years, but the onset of menarche in girls was delayed by up to 3 years, occurring around 15 for most in the study sample and 17 years for females living in London. Modern European males usually complete their maturation by 16-18 years; medieval males took longer with the deceleration stage of the growth spurt extending as late as 21 years. Conclusions: This research provides the first attempt to directly assess the age of pubertal development in adolescents during the tenth to seventeenth centuries. Poor diet, infections, and physical exertion may have contributed to delayed development in the medieval adolescents, particularly for those living in the city of London. This study sheds new light on the nature of adolescence in the medieval period, highlighting an extended period of physical and social transition.

Disorder prediction methods, their applicability to different protein targets and their usefulness for guiding experimental studies

The role and function of a given protein is dependent on its structure. In recent years, however, numerous studies have highlighted the importance of unstructured, or disordered regions in governing a protein’s function. Disordered proteins have been found to play important roles in pivotal cellular functions, such as DNA binding and signalling cascades. Studying proteins with extended disordered regions is often problematic as they can be challenging to express, purify and crystallise. This means that interpretable experimental data on protein disorder is hard to generate. As a result, predictive computational tools have been developed with the aim of predicting the level and location of disorder within a protein. Currently, over 60 prediction servers exist, utilizing different methods for classifying disorder and different training sets. Here we review several good performing, publicly available prediction methods, comparing their application and discussing how disorder prediction servers can be used to aid the experimental solution of protein structure. The use of disorder prediction methods allows us to adopt a more targeted approach to experimental studies by accurately identifying the boundaries of ordered protein domains so that they may be investigated separately, thereby increasing the likelihood of their successful experimental solution.

Greenhouse gas emissions from waste management—assessment of quantification methods

Of the many sources of urban greenhouse gas (GHG) emissions, solid waste is the only one for which management decisions are undertaken primarily by municipal governments themselves and is hence often the largest component of cities’ corporate inventories. It is essential that decision-makers select an appropriate quantification methodology and have an appreciation of methodological strengths and shortcomings. This work compares four different waste emissions quantification methods, including Intergovernmental Panel on Climate Change (IPCC) 1996 guidelines, IPCC 2006 guidelines, U.S. Environmental Protection Agency (EPA) Waste Reduction Model (WARM), and the Federation of Canadian Municipalities- Partners for Climate Protection (FCM-PCP) quantification tool. Waste disposal data for the greater Toronto area (GTA) in 2005 are used for all methodologies; treatment options (including landfill, incineration, compost, and anaerobic digestion) are examined where available in methodologies. Landfill was shown to be the greatest source of GHG emissions, contributing more than three-quarters of total emissions associated with waste management. Results from the different landfill gas (LFG) quantification approaches ranged from an emissions source of 557 kt carbon dioxide equivalents (CO2e) (FCM-PCP) to a carbon sink of −53 kt CO2e (EPA WARM). Similar values were obtained between IPCC approaches. The IPCC 2006 method was found to be more appropriate for inventorying applications because it uses a waste-in-place (WIP) approach, rather than a methane commitment (MC) approach, despite perceived onerous data requirements for WIP. MC approaches were found to be useful from a planning standpoint; however, uncertainty associated with their projections of future parameter values limits their applicability for GHG inventorying. MC and WIP methods provided similar results in this case study; however, this is case specific because of similarity in assumptions of present and future landfill parameters and quantities of annual waste deposited in recent years being relatively consistent.

Targeting medication non-adherence behavior in selected autoimmune diseases: a systematic approach to digital health program development

Background 29 autoimmune diseases, including Rheumatoid Arthritis, gout, Crohn’s Disease, and Systematic Lupus Erythematosus affect 7.6-9.4% of the population. While effective therapy is available, many patients do not follow treatment or use medications as directed. Digital health and Web 2.0 interventions have demonstrated much promise in increasing medication and treatment adherence, but to date many Internet tools have proven disappointing. In fact, most digital interventions continue to suffer from high attrition in patient populations, are burdensome for healthcare professionals, and have relatively short life spans. Objective Digital health tools have traditionally centered on the transformation of existing interventions (such as diaries, trackers, stage-based or cognitive behavioral therapy programs, coupons, or symptom checklists) to electronic format. Advanced digital interventions have also incorporated attributes of Web 2.0 such as social networking, text messaging, and the use of video. Despite these efforts, there has not been little measurable impact in non-adherence for illnesses that require medical interventions, and research must look to other strategies or development methodologies. As a first step in investigating the feasibility of developing such a tool, the objective of the current study is to systematically rate factors of non-adherence that have been reported in past research studies. Methods Grounded Theory, recognized as a rigorous method that facilitates the emergence of new themes through systematic analysis, data collection and coding, was used to analyze quantitative, qualitative and mixed method studies addressing the following autoimmune diseases: Rheumatoid Arthritis, gout, Crohn’s Disease, Systematic Lupus Erythematosus, and inflammatory bowel disease. Studies were only included if they contained primary data addressing the relationship with non-adherence. Results Out of the 27 studies, four non-modifiable and 11 modifiable risk factors were discovered. Over one third of articles identified the following risk factors as common contributors to medication non-adherence (percent of studies reporting): patients not understanding treatment (44%), side effects (41%), age (37%), dose regimen (33%), and perceived medication ineffectiveness (33%). An unanticipated finding that emerged was the need for risk stratification tools (81%) with patient-centric approaches (67%). Conclusions This study systematically identifies and categorizes medication non-adherence risk factors in select autoimmune diseases. Findings indicate that patients understanding of their disease and the role of medication are paramount. An unexpected finding was that the majority of research articles called for the creation of tailored, patient-centric interventions that dispel personal misconceptions about disease, pharmacotherapy, and how the body responds to treatment. To our knowledge, these interventions do not yet exist in digital format. Rather than adopting a systems level approach, digital health programs should focus on cohorts with heterogeneous needs, and develop tailored interventions based on individual non-adherence patterns.

Exploring methods to evaluate the carbon impact of network investment deferral

Replacement, expansion and upgrading of assets in the electricity network represents financial investment for the distribution utilities. Network Investment Deferral (NID) is a well discussed benefit of wider adoption of Distributed Generation (DG). There have been many attempts to quantify and evaluate the financial benefit for the distribution utilities. While the carbon benefits of NID are commonly mentioned, there is little attempt to quantify these impacts. This paper explores the quantitative methods previously used to evaluate financial benefits in order to discuss the carbon impacts. These carbon impacts are important for companies owning DG equipment for internal reporting and emissions reductions ambitions. Currently, a GB wide approach is taken as a means for discussing more regional and local methods to be used in future work. By investigating these principles, the paper offers a novel approach to quantifying carbon emissions from various DG technologies.

Coaching SME managers: business development or personal therapy? A mixed methods study

While a growing number of small- and medium-sized enterprises (SMEs) are making use of coaching, little is known about the impact such coaching has within this sector. This study sought to identify the factors that influence managers' decision to engage with coaching, their perceptions of the coaching ‘journey’ and the kinds of benefits accruing from coaching: organisational, personal or both. As part of a mixed methods approach, a survey tool was developed based upon a range of relevant management competencies from the UK's Management Occupational Standards and responses analysed using importance-performance analysis, an approach first used in the marketing sector to evaluate customer satisfaction. Results indicate that coaching had a significant impact on personal attributes such as ‘Managing Self-Cognition’ and ‘Managing Self-Emotional’, whereas the impact on business-oriented attributes was weaker. Managers' choice of coaches with psychotherapeutic rather than non-psychotherapeutic backgrounds was also statistically significant. We conclude that even in the competitive business environment of SMEs, coaching was used as a largely personal, therapeutic intervention rather than to build business-oriented competencies.

An approximate dynamic programming approach for improving accuracy of lossy data compression by Bloom filters

Bloom filters are a data structure for storing data in a compressed form. They offer excellent space and time efficiency at the cost of some loss of accuracy (so-called lossy compression). This work presents a yes-no Bloom filter, which as a data structure consisting of two parts: the yes-filter which is a standard Bloom filter and the no-filter which is another Bloom filter whose purpose is to represent those objects that were recognised incorrectly by the yes-filter (that is, to recognise the false positives of the yes-filter). By querying the no-filter after an object has been recognised by the yes-filter, we get a chance of rejecting it, which improves the accuracy of data recognition in comparison with the standard Bloom filter of the same total length. A further increase in accuracy is possible if one chooses objects to include in the no-filter so that the no-filter recognises as many as possible false positives but no true positives, thus producing the most accurate yes-no Bloom filter among all yes-no Bloom filters. This paper studies how optimization techniques can be used to maximize the number of false positives recognised by the no-filter, with the constraint being that it should recognise no true positives. To achieve this aim, an Integer Linear Program (ILP) is proposed for the optimal selection of false positives. In practice the problem size is normally large leading to intractable optimal solution. Considering the similarity of the ILP with the Multidimensional Knapsack Problem, an Approximate Dynamic Programming (ADP) model is developed making use of a reduced ILP for the value function approximation. Numerical results show the ADP model works best comparing with a number of heuristics as well as the CPLEX built-in solver (B&B), and this is what can be recommended for use in yes-no Bloom filters. In a wider context of the study of lossy compression algorithms, our researchis an example showing how the arsenal of optimization methods can be applied to improving the accuracy of compressed data.

Using developmental evaluation methods with communities of practice

Purpose This research explored the use of developmental evaluation methods with community of practice programmes experiencing change or transition to better understand how to target support resources. Design / methodology / approach The practical use of a number of developmental evaluation methods was explored in three organisations over a nine month period using an action research design. The research was a collaborative process involving all the company participants and the academic (the author) with the intention of developing the practices of the participants as well as contributing to scholarship. Findings The developmental evaluation activities achieved the objectives of the knowledge managers concerned: they developed a better understanding of the contribution and performance of their communities of practice, allowing support resources to be better targeted. Three methods (fundamental evaluative thinking, actual-ideal comparative method and focus on strengths and assets) were found to be useful. Cross-case analysis led to the proposition that developmental evaluation methods act as a structural mechanism that develops the discourse of the organisation in ways that enhance the climate for learning, potentially helping develop a learning organization. Practical implications Developmental evaluation methods add to the options available to evaluate community of practice programmes. These supplement the commonly used activity indicators and impact story methods. 2 Originality / value Developmental evaluation methods are often used in social change initiatives, informing public policy and funding decisions. The contribution here is to extend their use to organisational community of practice programmes.