Modelling the spatial behaviour of a tropical tuna purse seine fleet.

Industrial tuna fisheries operate in the Indian, Atlantic and Pacific Oceans, but concerns over sustainability and environmental impacts of these fisheries have resulted in increased scrutiny of how they are managed. An important but often overlooked factor in the success or failure of tuna fisheries management is the behaviour of fishers and fishing fleets. Uncertainty in how a fishing fleet will respond to management or other influences can be reduced by anticipating fleet behaviour, although to date there has been little research directed at understanding and anticipating the human dimension of tuna fisheries. The aim of this study was to address gaps in knowledge of the behaviour of tuna fleets, using the Indian Ocean tropical tuna purse seine fishery as a case study. We use statistical modelling to examine the factors that influence the spatial behaviour of the purse seine fleet at broad spatiotemporal scales. This analysis reveals very high consistency between years in the use of seasonal fishing grounds by the fleet, as well as a forcing influence of biophysical ocean conditions on the distribution of fishing effort. These findings suggest strong inertia in the spatial behaviour of the fleet, which has important implications for predicting the response of the fleet to natural events or management measures (e.g., spatial closures)

Evaluating unsupervised methods to size and classify suspended particles using digital in-line holography

Substantial information can be gained from digital in-line holography of marine particles, eliminating depth-of-field and focusing errors associated with standard lens-based imagingmethods.However, for the technique to reach its full potential in oceanographic research, fully unsupervised (automated) methods are required for focusing, segmentation, sizing, and classification of particles. These computational challenges are the subject of this paper, in which the authors draw upon data collected using a variety of holographic systems developed at Plymouth University, United Kingdom, from a significant range of particle types, sizes, and shapes. A new method for noise reduction in reconstructed planes is found to be successful in aiding particle segmentation and sizing. The performance of an automated routine for deriving particle characteristics (and subsequent size distributions) is evaluated against equivalent size metrics obtained by a trained operative measuring grain axes on screen. The unsupervised method is found to be reliable, despite some errors resulting from oversegmentation of particles. A simple unsupervised particle classification system is developed and is capable of successfully differentiating sand grains, bubbles, and diatoms from within the surfzone. Avoiding miscounting bubbles and biological particles as sand grains enables more accurate estimates of sand concentrations and is especially important in deployments of particle monitoring instrumentation in aerated water. Perhaps the greatest potential for further development in the computational aspects of particle holography is in the area of unsupervised particle classification. The simple method proposed here provides a foundation upon which further development could lead to reliable identification of more complex particle populations, such as those containing phytoplankton, zooplankton, flocculated cohesive sediments, and oil droplets

Validation tools: can they indicate the information content of macromolecular crystal structures?

AbstractThe explosive increase in the number of published three-dimensionsal structures of macromolecules determined by X-ray analysis places a responsibility on experimentalists, referees and curators of databases to ensure correspondence between the structure parameters and data. Validation tools will evolve as more appropriate statistical techniques and new information, such as that from proteins analysed at atomic resolution, becomes available

From movement to motivation: a proposed framework to understand the antidepressant effect of exercise

Depression is the leading cause of disability worldwide, exerting a profound negative impact on quality of life in those who experience it. Depression is associated with disruptions to several closely related neural and cognitive processes, including dopamine transmission, fronto-striatal brain activity and connectivity, reward processing and motivation. Physical activity, especially aerobic exercise, reduces depressive symptoms, but the mechanisms driving its antidepressant effects are poorly understood. Here we propose a novel hypothesis for understanding the antidepressant effects of exercise, centred on motivation, across different levels of explanation. There is robust evidence that aerobic exercise decreases systemic inflammation. Inflammation is known to reduce dopamine transmission, which in turn is strongly implicated in effort-based decision making for reward. Drawing on a broad range of research in humans and animals, we propose that by reducing inflammation and boosting dopamine transmission, with consequent effects on effort-based decision making for reward, exercise initially specifically improves ‘interest-activity’ symptoms of depression—namely anhedonia, fatigue and subjective cognitive impairment - by increasing propensity to exert effort. Extending this framework to the topic of cognitive control, we explain how cognitive impairment in depression may also be conceptualised through an effort-based decision-making framework, which may help to explain the impact of exercise on cognitive impairment. Understanding the mechanisms underlying the antidepressant effects of exercise could inform the development of novel intervention strategies, in particular personalised interventions and boost social prescribing

The role of industry studies and public policies in production and operations management

The research domain Industry Studies and Public Policy (IS&PP) seeks to further our understanding of industrial practices and managerial challenges by explicitly considering contextual details in the design and interpretation of research studies. These details can be vital considerations when shaping public policies. This article reviews a sample of IS&PP publications and analyzes the content of 180 selected papers — 85 papers published in the $\textit{Production and Operations Management}$ (POM) journal and 95 papers published in related journals between 1992 and 2014. Our analysis of the sample dataset and examination of exemplar papers provide four findings. First, studies in different industries emphasize different themes of operational decisions. This difference in emphasis reveals potential research opportunities, especially for conducting inter-industry studies. Second, our analysis reveals a shift in focus over time. Earlier studies contain a mix of benchmarks and inter-industry comparisons, while later studies tend to be context-specific, intra-industry studies. Third, we report on empirics→ analytics→ empirics cycles that reveal gaps for building novel theories. Finally, we observe that the relationship between POM decisions and public policy is bi-directional. This highlights the need to jointly examine operational decisions with policy considerations, especially in information goods, healthcare, sustainable operations and high-tech manufacturing industries

The role of industry studies and public policies in production and operations management

The research domain Industry Studies and Public Policy (IS&PP) seeks to further our understanding of industrial practices and managerial challenges by explicitly considering contextual details in the design and interpretation of research studies. These details can be vital considerations when shaping public policies. This article reviews a sample of IS&PP publications and analyzes the content of 180 selected papers — 85 papers published in the $\textit{Production and Operations Management}$ (POM) journal and 95 papers published in related journals between 1992 and 2014. Our analysis of the sample dataset and examination of exemplar papers provide four findings. First, studies in different industries emphasize different themes of operational decisions. This difference in emphasis reveals potential research opportunities, especially for conducting inter-industry studies. Second, our analysis reveals a shift in focus over time. Earlier studies contain a mix of benchmarks and inter-industry comparisons, while later studies tend to be context-specific, intra-industry studies. Third, we report on empirics→ analytics→ empirics cycles that reveal gaps for building novel theories. Finally, we observe that the relationship between POM decisions and public policy is bi-directional. This highlights the need to jointly examine operational decisions with policy considerations, especially in information goods, healthcare, sustainable operations and high-tech manufacturing industries

Pre-Meal Whey Protein Alters Postprandial Insulinemia by Enhancing β-Cell Function and Reducing Insulin Clearance in T2D

CONTEXT: Treatments that reduce postprandial glycemia (PPG) independent of stimulating insulin secretion are appealing for the management of type 2 diabetes (T2D). Consuming pre-meal whey protein (WP) reduces PPG by delaying gastric emptying and increasing plasma insulin concentrations. However, its effects on β-cell function and insulin kinetics remains unclear. OBJECTIVE: To examine the PPG-regulatory effects of pre-meal WP by modeling insulin secretion rates (ISR), insulin clearance, and β-cell function. METHODS: This was a single-blind, randomized, placebo-controlled, crossover design study in 18 adults with T2D (HbA1c, 56.7 ± 8.8 mmol/mol) who underwent 2 240-minute mixed-meal tolerance tests. Participants consumed WP (15 g protein) or placebo (0 g protein) 10 minutes before a mixed-macronutrient breakfast meal. PPG, pancreatic islet, and incretin hormones were measured throughout. ISR was calculated by C-peptide deconvolution. Estimates of insulin clearance and β-cell function were modeled from glucose, insulin, and ISR. Changes in PPG incremental area under the curve (iAUC; prespecified) and insulin clearance (post hoc) were measured. RESULTS: β-cell function was 40% greater after WP (P = .001) and was accompanied with a -22% reduction in postprandial insulin clearance vs placebo (P < .0001). Both the peak change and PPG iAUC were reduced by WP (-1.5 mmol/L and -16%, respectively; both P < .05). Pre-meal WP augmented a 5.9-fold increase in glucagon and glucagon-like peptide 1 iAUC (both P < .0001), and a 1.5-fold increase in insulin iAUC (P < .001). Although the plasma insulin response was greater following WP, ISR was unaffected (P = .133). CONCLUSION: In adults with T2D, pre-meal WP reduced PPG by coordinating an enhancement in β-cell function with a reduction in insulin clearance. This enabled an efficient postprandial insulinemic profile to be achieved without requiring further β-cell stimulation.Trial registry ISRCTN ID: ISRCTN17563146 Website link: www.isrctn.com/ISRCTN17563146

A systematic review of interventions to enhance access to best practice primary health care for chronic disease management, prevention and episodic care

Background: Although primary health care (PHC) is a key component of all health care systems, services are not always readily available, accessible or affordable. This systematic review examines effective strategies to enhance access to best practice processes of PHC in three domains: chronic disease management, prevention and episodic care. Methods. An extensive search of bibliographic data bases to identify peer and non-peer reviewed literature was undertaken. Identified papers were screened to identify and classify intervention studies that measured the impact of strategies (singly or in combination) on change in use or the reach of services in defined population groups (evaluated interventions). Results: The search identified 3,148 citations of which 121 were intervention studies and 75 were evaluated interventions. Evaluated interventions were found in all three domains: prevention (n=45), episodic care (n=19), and chronic disease management (n=11). They were undertaken in a number of countries including Australia (n=25), USA (n=25), and UK (n=15). Study quality was ranked as high (31% of studies), medium (61%) and low (8%). The 75 evaluated interventions tested a range of strategies either singly (n=46 studies) or as a combination of two (n=20) or more strategies (n=9). Strategies targeted both health providers and patients and were categorised to five groups: practice re-organisation (n=43 studies), patient support (n=29), provision of new services (n=19), workforce development (n=11), and financial incentives (n=9). Strategies varied by domain, reflecting the complexity of care needs and processes. Of the 75 evaluated interventions, 55 reported positive findings with interventions using a combination of strategies more likely to report positive results. Conclusions: This review suggests that multiple, linked strategies targeting different levels of the health care system are most likely to improve access to best practice PHC. The proposed changes in the structure of PHC in Australia may provide opportunities to investigate the factors that influence access to best practice PHC and to develop and implement effective, evidence based strategies to address these. © 2012 Comino et al.; licensee BioMed Central Ltd

Two-loop RGEs with Dirac gaugino masses

The set of renormalisation group equations to two loop order for general supersymmetric theories broken by soft and supersoft operators is completed. As an example, the explicit expressions for the RGEs in a Dirac gaugino extension of the (N)MSSM are presented.Comment: 10 pages + 24 pages of RGEs in appendix; no figure