The effect of a life development intervention on sports career transition adjustment

Lavallee, D. (2005). The effect of a life development intervention on sports career transition adjustment. The Sport Psychologist. 19(2), pp.193-202 RAE2008

Osmotic stress tolerance mechanisms in Lactococcus lactis

The response of Lactococcus lactis subsp. cremoris NCDO 712 to low water activity (aw) was investigated, both in relation to growth following moderate reductions in the aw and in terms of survival following substantial reduction of the aw with NaCI. Lc.lactis NCDO 712 was capable of growth in the presence of ≤ 4% w/v NaCI and concentrations in excess of 4% w/v were lethal to the cells. The presence of magnesium ions significantly increased the resistance of NCDO 712 to challenge with NaCI and also to challenge with high temperature or low pH. Survival of Lc.lactis NCDO 712 exposed to high NaCI concentrations was growth phase dependent and cells were most sensitive in the early exponential phase of growth. Pre-exposure to 3% w/v NaCI induced limited protection against subsequent challenge with higher NaCI concentrations. The induction was inhibited by chloramphenicol and even when induced, the response did not protect against NaCI concentrations> 10% w/v. When growing at low aw, potassium was accumulated by Lc. lactis NCDO 712 growing at low aw, if the aw was reduced by glucose or fructose, but not by NaCI. Reducing the potassium concentration of chemically defined medium from 20 to 0.5 mM) produced a substantial reduction in the growth rate, if the aw was reduced with NaCI, but not with glucose or fructose. The reduction of the growth rate correlated strongly with a reduction in the cytoplasmic potassium concentration and in cell volume. Addition of the compatible solute glycine betaine, partially reversed the inhibition of growth rate and partially restored the cell volume. The potassium transport system was characterised in cells grown in medium at both high and low aw. It appeared that a single system was present, which was induced approximately two-fold by growth at low aw. Potassium transport was assayed in vitro using cells depleted of potassium; the assay was competitively inhibited by Na+ and by the other monovalent cations NH4+, Li+, and Cs+. There was a strong correlation between the ability of strains of Lc. lactis subsp. lactis and subsp. cremoris to grow at low aw and their ability to accumulate the compatible solute glycine betaine. The Lc. lactis subsp. cremoris strains incapable of growth at NaCI concentrations> 2% w/v did not accumulate glycine betaine when growing at low aw, whereas strains capable of growth at NaCI concentrations up to 4% w/v did. A mutant, extremely sensitive to low aw was isolated from the parent strain Lc. lactis subsp. cremoris MG 1363, a plasmid free derivative of NCDO 712. The parent strain tolerated up to 4% w/v NaCI and actively accumulated glycine betaine when challenged at low aw. The mutant had lost the ability to accumulate glycine betaine and was incapable of growth at NaCI concentrations >2% w/v or the equivalent concentration of glucose. As no other compatible solute seemed capable of substitution for glycine betaine, the data suggest that the traditional; phenotypic speciation of strains on the basis of tolerance to 4% w/v NaCI can be explained as possession or lack of a glycine betaine transport system.

College adjustment, depressive symptoms and peer support among undergraduate university students

Background: College adjustment is a developmental milestone that can be stressful and may lead to mental health problems such as depression. Support during this adjustment period is seen as essential, however it is unknown if informal peer support from fellow students has any impact on either college adjustment or depressive symptoms. Aim: To identify levels of social and personal college adjustment, depressive symptoms and peer support among students, and to examine the relationship between the variables. Design: A quantitative correlational design was used Instruments: Data were collected using two subscales of the Student Adaptation to College Questionnaire; the Centre for Epidemiology Depressive Symptoms Scale and a subscale of the Peer Support Evaluation Inventory. Sample: The sample consisted of 417, first (n=188), second (n=134) and fourth (n=94) year nursing and midwifery students from one University in Ireland. Findings: The findings indicated that 20% of participants were poorly personally adjusted and 9% poorly socially adjusted. Furthermore, 34% of participants experienced significant depressive symptoms. Most students had good levels of peer support. Statistically significant relationships were found between all key variables, the strongest of which were between personal adjustment and depressive symptoms and social adjustment and depressive symptoms. Differences in adjustment and depressive symptom scores were found based on year of study, with second year students experiencing more depressive symptoms and having poorer personal adjustment scores. Participants who had poor relationships with their father’s experienced greater depressive symptoms and had more difficulties personally and socially adjusting to college. The alcohol consumption of participants had a statistically significant correlation with college adjustment, depressive symptoms and peer support, with higher consumption having a positive impact on the variables.

The effects of osmotic stress on the structure and function of the cell nucleus.

Osmotic stress is a potent regulator of the normal function of cells that are exposed to osmotically active environments under physiologic or pathologic conditions. The ability of cells to alter gene expression and metabolic activity in response to changes in the osmotic environment provides an additional regulatory mechanism for a diverse array of tissues and organs in the human body. In addition to the activation of various osmotically- or volume-activated ion channels, osmotic stress may also act on the genome via a direct biophysical pathway. Changes in extracellular osmolality alter cell volume, and therefore, the concentration of intracellular macromolecules. In turn, intracellular macromolecule concentration is a key physical parameter affecting the spatial organization and pressurization of the nucleus. Hyper-osmotic stress shrinks the nucleus and causes it to assume a convoluted shape, whereas hypo-osmotic stress swells the nucleus to a size that is limited by stretch of the nuclear lamina and induces a smooth, round shape of the nucleus. These behaviors are consistent with a model of the nucleus as a charged core/shell structure pressurized by uneven partition of macromolecules between the nucleoplasm and the cytoplasm. These osmotically-induced alterations in the internal structure and arrangement of chromatin, as well as potential changes in the nuclear membrane and pores are hypothesized to influence gene transcription and/or nucleocytoplasmic transport. A further understanding of the biophysical and biochemical mechanisms involved in these processes would have important ramifications for a range of fields including differentiation, migration, mechanotransduction, DNA repair, and tumorigenesis.

Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem

This paper studies the multiplicity-correction effect of standard Bayesian variable-selection priors in linear regression. Our first goal is to clarify when, and how, multiplicity correction happens automatically in Bayesian analysis, and to distinguish this correction from the Bayesian Ockham's-razor effect. Our second goal is to contrast empirical-Bayes and fully Bayesian approaches to variable selection through examples, theoretical results and simulations. Considerable differences between the two approaches are found. In particular, we prove a theorem that characterizes a surprising aymptotic discrepancy between fully Bayes and empirical Bayes. This discrepancy arises from a different source than the failure to account for hyperparameter uncertainty in the empirical-Bayes estimate. Indeed, even at the extreme, when the empirical-Bayes estimate converges asymptotically to the true variable-inclusion probability, the potential for a serious difference remains. © Institute of Mathematical Statistics, 2010.

Flexible self-adjustment of task deployment in dynamic environments

This paper presents an investigation into dynamic self-adjustment of task deployment and other aspects of self-management, through the embedding of multiple policies. Non-dedicated loosely-coupled computing environments, such as clusters and grids are increasingly popular platforms for parallel processing. These abundant systems are highly dynamic environments in which many sources of variability affect the run-time efficiency of tasks. The dynamism is exacerbated by the incorporation of mobile devices and wireless communication. This paper proposes an adaptive strategy for the flexible run-time deployment of tasks; to continuously maintain efficiency despite the environmental variability. The strategy centres on policy-based scheduling which is informed by contextual and environmental inputs such as variance in the round-trip communication time between a client and its workers and the effective processing performance of each worker. A self-management framework has been implemented for evaluation purposes. The framework integrates several policy-controlled, adaptive services with the application code, enabling the run-time behaviour to be adapted to contextual and environmental conditions. Using this framework, an exemplar self-managing parallel application is implemented and used to investigate the extent of the benefits of the strategy

Artificial neural networks in modelling osmotic dehydration of foods

Artificial neural network (ANN) models for water loss (WL) and solid gain (SG) were evaluated as potential alternative to multiple linear regression (MLR) for osmotic dehydration of apple, banana and potato. The radial basis function (RBF) network with a Gaussian function was used in this study. The RBF employed the orthogonal least square learning method. When predictions of experimental data from MLR and ANN were compared, an agreement was found for ANN models than MLR models for SG than WL. The regression coefficient for determination (R2) for SG in MLR models was 0.31, and for ANN was 0.91. The R2 in MLR for WL was 0.89, whereas ANN was 0.84.Osmotic dehydration experiments found that the amount of WL and SG occurred in the following descending order: Golden Delicious apple > Cox apple > potato > banana. The effect of temperature and concentration of osmotic solution on WL and SG of the plant materials followed a descending order as: 55 > 40 > 32.2C and 70 > 60 > 50 > 40%, respectively.

Risk adjustment for hospital use using social security data: cross sectional small area analysis

Objectives: To identify demographic and socioeconomic determinants of need for acute hospital treatment at small area level. To establish whether there is a relation between poverty and use of inpatient services. To devise a risk adjustment formula for distributing public funds for hospital services using, as far as possible, variables that can be updated between censuses. Design: Cross sectional analysis. Spatial interactive modelling was used to quantify the proximity of the population to health service facilities. Two stage weighted least squares regression was used to model use against supply of hospital and community services and a wide range of potential needs drivers including health, socioeconomic census variables, uptake of income support and family credit, and religious denomination. Setting: Northern Ireland. Main outcome measure: Intensity of use of inpatient services. Results: After endogeneity of supply and use was taken into account, a statistical model was produced that predicted use based on five variables: income support, family credit, elderly people living alone, all ages standardised mortality ratio, and low birth weight. The main effect of the formula produced is to move resources from urban to rural areas. Conclusions: This work has produced a population risk adjustment formula for acute hospital treatment in which four of the five variables can be updated annually rather than relying on census derived data. Inclusion of the social security data makes a substantial difference to the model and to the results produced by the formula.

A recursive rule base adjustment algorithm for a fuzzy logic controller

This paper introduces a recursive rule base adjustment to enhance the performance of fuzzy logic controllers. Here the fuzzy controller is constructed on the basis of a decision table (DT), relying on membership functions and fuzzy rules that incorporate heuristic knowledge and operator experience. If the controller performance is not satisfactory, it has previously been suggested that the rule base be altered by combined tuning of membership functions and controller scaling factors. The alternative approach proposed here entails alteration of the fuzzy rule base. The recursive rule base adjustment algorithm proposed in this paper has the benefit that it is computationally more efficient for the generation of a DT, and advantage for online realization. Simulation results are presented to support this thesis. (c) 2005 Elsevier B.V. All rights reserved.