Does individual variation in metabolic phenotype predict fish behaviour and performance?

There is increasing interest in documenting and explaining the existence of marked intraspecific variation in metabolic rate in animals, with fishes providing some of the best-studied examples. After accounting for variation due to other factors, there can typically be a two to three-fold variation among individual fishes for both standard and maximum metabolic rate (SMR and MMR). This variation is reasonably consistent over time (provided that conditions remain stable), and its underlying causes may be influenced by both genes and developmental conditions. In this paper, current knowledge of the extent and causes of individual variation in SMR, MMR and aerobic scope (AS), collectively its metabolic phenotype, is reviewed and potential links among metabolism, behaviour and performance are described. Intraspecific variation in metabolism has been found to be related to other traits: fishes with a relatively high SMR tend to be more dominant and grow faster in high food environments, but may lose their advantage and are more prone to risk-taking when conditions deteriorate. In contrast to the wide body of research examining links between SMR and behavioural traits, very little work has been directed towards understanding the ecological consequences of individual variation in MMR and AS. Although AS can differ among populations of the same species in response to performance demands, virtually nothing is known about the effects of AS on individual behaviours such as those associated with foraging or predator avoidance. Further, while factors such as food availability, temperature, hypoxia and the fish's social environment are known to alter resting and MMRs in fishes, there is a paucity of studies examining how these effects vary among individuals, and how this variation relates to behaviour. Given the observed links between metabolism and measures of performance, understanding the metabolic responses of individuals to changing environments will be a key area for future research because the environment will have a strong influence on which animals survive predation, become dominant and ultimately have the highest reproductive success. Although current evidence suggests that variation in SMR may be maintained within populations via context-dependent fitness benefits, it is suggested that a more integrative approach is now required to fully understand how the environment can modulate individual performance via effects on metabolic phenotypes encompassing SMR, MMR and AS

Особливості формування етнічного складу селянської верстви Степового Побужжя

In this short paper we sketch a brief introduction to our Krimp algorithm. Moreover, we briefly discuss some of the large body of follow up research. Pointers to the relevant papers are provided in the bibliography

NGC 2362: a Template for Early Stellar Evolution

We present UBVRI photometry for the young open cluster NGC 2362. From analysis of the appropriate color-color and color-magnitude diagrams we derive the fundamental parameters of the NGC 2362 cluster to be: age = 5 (+1-2) Myr, distance = 1480 pc, E(B-V)=0.10 mag. The cluster age was independently determined for both high mass (2.1 - 36Msun) and low mass (0.7 - 1.2Msun) stars with excellent agreement between the ages derived using post-main sequence and pre-main sequence evolutionary tracks for the high and low mass stars respectively. Analysis of this cluster's color-magnitude diagram reveals a well defined pre-main sequence (covering DeltaV ~ 9 magnitudes in V and extending from early A stars to near the hydrogen burning limit) which makes this cluster an ideal laboratory for pre-main sequence evolution studies.Comment: 9 pages, 3 figures, to be published in ApJ

CO2-dosering bij roos onder verschillende temperaturen en belichtingniveaus : vervolgonderzoek kwantificering van CO2-effecten op productie en kwaliteit bij roos

Uit eerder onderzoek van PPO bleek dat met een hogere CO2-dosering en meer assimilatiebelichting een hogere productie van een betere kwaliteit kon worden gerealiseerd. De gegevens uit dat onderzoek werden gebruikt om een groeimodel voor groente (ECP) te valideren. Omdat het ECP-productiemodel niet geschikt bleek te zijn voor roos, is een vervolgonderzoek gestart om een dynamisch productiemodel te ontwikkelen specifiek voor roos. Zo kan de teler de productie en kwaliteit sturen door middel van drie "knoppen": CO2, licht en temperatuur. In deze publicatie staat een beschrijving van dit vervolgonderzoek. Twee CO2-concentraties (700 en 1400 ppm), twee lichtintensiteiten (3750 en 7100 lux), drie teelttemperaturen (17, 20 en 23°C) en twee gewasleeftijden (een jonge aanplant en een twee jaar oud gewas van ‘Indian Femma’) zijn onderling gecombineerd in 6 verschillende afdelingen. Daarnaast zijn twee extra afdelingen in gebruik genomen, waarin door middel van koelen met behulp van verneveling geprobeerd is CO2-verlies door ventilatie te vermindere

Seismic wavefield redatuming with regularized multi-dimensional deconvolution

In seismic imaging the aim is to obtain an image of the subsurface using reflection data. The reflection data are generated using sound waves and the sources and receivers are placed at the surface. The target zone, for example an oil or gas reservoir, lies relatively deep in the subsurface below several layers. The area above the target zone is called the overburden. This overburden will have an imprint on the image. Wavefield redatuming is an approach that removes the imprint of the overburden on the image by creating so-called virtual sources and receivers above the target zone. The virtual sources are obtained by determining the impulse response, or Green's function, in the subsurface. The impulse response is obtained by deconvolving all up- and downgoing wavefields at the desired location. In this paper, we pose this deconvolution problem as a constrained least-squares problem. We describe the constraints that are involved in the deconvolution and show that they are associated with orthogonal projection operators. We show different optimization strategies to solve the constrained least-squares problem and provide an explicit relation between them, showing that they are in a sense equivalent. We show that the constrained least-squares problem remains ill-posed and that additional regularizati

Comparing RSVD and Krylov methods for linear inverse problems

In this work we address regularization parameter estimation for ill-posed linear inverse problems with an penalty. Regularization parameter selection is of utmost importance for all of inverse problems and estimating it generally relies on the experience of the practitioner. For regularization with an penalty there exist a lot of parameter selection methods that exploit the fact that the solution and the residual can be written in explicit form. Parameter selection methods are functionals that depend on the regularization parameter where the minimizer is the desired regularization parameter that should lead to a good solution. Evaluation of these parameter selection methods still requires solving the inverse problem multiple times. Efficient evaluation of the parameter selection methods can be done through model order reduction. Two popular model order reduction techniques are Lanczos based methods (a Krylov subspace method) and the Randomized Singular Value Decomposition (RSVD). In this work we compare the two approaches. We derive error bounds for the parameter selection methods using the RSVD. We compare the performance of the Lanczos process versus the performance of RSVD for efficient parameter selection. The RSVD algorithm we use i

Helping Made Easy: Ease of Argument Generation Enhances Intentions to Help

Previous work has shown that self-generating arguments is more persuasive than reading arguments provided by others, particularly if self-generation feels easy. The present study replicates and extends these findings by providing evidence for fluency effects on behavioral intention in the realm of helping. In two studies, participants were instructed to either self-generate or read two versus ten arguments about why it is good to help. Subsequently, a confederate asked them for help. Results show that self-generating few arguments is more effective than generating many arguments. While this pattern reverses for reading arguments, easy self-generation is the most effective strategy compared to all other conditions. These results have important implications for fostering behavioral change in all areas of life

How molecular imaging will enable robotic precision surgery: the role of artificial intelligence, augmented reality, and navigation

Molecular imaging is one of the pillars of precision surgery. Its applications range from early diagnostics to therapy planning, execution, and the accurate assessment of outcomes. In particular, molecular imaging solutions are in high demand in minimally invasive surgical strategies, such as the substantially increasing field of robotic surgery. This review aims at connecting the molecular imaging and nuclear medicine community to the rapidly expanding armory of surgical medical devices. Such devices entail technologies ranging from artificial intelligence and computer-aided visualization technologies (software) to innovative molecular imaging modalities and surgical navigation (hardware). We discuss technologies based on their role at different steps of the surgical workflow, i.e., from surgical decision and planning, over to target localization and excision guidance, all the way to (back table) surgical verification. This provides a glimpse of how innovations from the technology fields can realize an exciting future for the molecular imaging and surgery communities.Imaging- and therapeutic targets in neoplastic and musculoskeletal inflammatory diseas