The impact of predation by marine mammals on Patagonian toothfish longline fisheries

Predatory interaction of marine mammals with longline fisheries is observed globally, leading to partial or complete loss of the catch and in some parts of the world to considerable financial loss. Depredation can also create additional unrecorded fishing mortality of a stock and has the potential to introduce bias to stock assessments. Here we aim to characterise depredation in the Patagonian toothfish (Dissostichus eleginoides) fishery around South Georgia focusing on the spatio-temporal component of these interactions. Antarctic fur seals (Arctocephalus gazella), sperm whales (Physeter macrocephalus), and orcas (Orcinus orca) frequently feed on fish hooked on longlines around South Georgia. A third of longlines encounter sperm whales, but loss of catch due to sperm whales is insignificant when compared to that due to orcas, which interact with only 5% of longlines but can take more than half of the catch in some cases. Orca depredation around South Georgia is spatially limited and focused in areas of putative migration routes, and the impact is compounded as a result of the fishery also concentrating in those areas at those times. Understanding the seasonal behaviour of orcas and the spatial and temporal distribution of “depredation hot spots” can reduce marine mammal interactions, will improve assessment and management of the stock and contribute to increased operational efficiency of the fishery. Such information is valuable in the effort to resolve the human-mammal conflict for resources

Heavy Flavour Production at Tevatron and Parton Shower Effects

We present hadron-level predictions from the Monte Carlo generator Cascade and numerical calculations of charm and beauty production at the Fermilab Tevatron within the framework of the $k_T$-factorization QCD approach. Our consideration is based on the CCFM-evolved unintegrated gluon densities in a proton. The performed analysis covers the total and differential cross sections of open charm and beauty quarks, $B$ and $D$ mesons (or rather muons from their semileptonic decays) and the total and differential cross sections of $b \bar b$ di-jet hadroproduction. We study the theoretical uncertainties of our calculations and investigate the effects coming from parton showers in initial and final states. Our predictions are compared with the recent experimental data taken by the D0 and CDF collaborations. Special attention is put on the specific angular correlations between the final-state particles. We demonstrate that the final state parton shower plays a crucial role in the description of such observables. The decorrelated part of angular separations can be fully described, if the process $gg^*\rightarrow gg$ is included.Comment: Fig 8,9 10 replaced, small corrections in text A discussion of the delta phi results is adde

The effect of Ku on telomere replication time is mediated by telomere length but is independent of histone tail acetylation

Peer reviewedPublisher PD

Quantum nondemolition measurement of mechanical motion quanta

The fields of opto- and electromechanics have facilitated numerous advances in the areas of precision measurement and sensing, ultimately driving the studies of mechanical systems into the quantum regime. To date, however, the quantization of the mechanical motion and the associated quantum jumps between phonon states remains elusive. For optomechanical systems, the coupling to the environment was shown to preclude the detection of the mechanical mode occupation, unless strong single photon optomechanical coupling is achieved. Here, we propose and analyse an electromechanical setup, which allows to overcome this limitation and resolve the energy levels of a mechanical oscillator. We find that the heating of the membrane, caused by the interaction with the environment and unwanted couplings, can be suppressed for carefully designed electromechanical systems. The results suggest that phonon number measurement is within reach for modern electromechanical setups.Comment: 8 pages, 5 figures plus 24 pages, 11 figures supplemental materia

Effects of gestational age at birth on cognitive performance : a function of cognitive workload demands

Objective: Cognitive deficits have been inconsistently described for late or moderately preterm children but are consistently found in very preterm children. This study investigates the association between cognitive workload demands of tasks and cognitive performance in relation to gestational age at birth. Methods: Data were collected as part of a prospective geographically defined whole-population study of neonatal at-risk children in Southern Bavaria. At 8;5 years, n = 1326 children (gestation range: 23–41 weeks) were assessed with the K-ABC and a Mathematics Test. Results: Cognitive scores of preterm children decreased as cognitive workload demands of tasks increased. The relationship between gestation and task workload was curvilinear and more pronounced the higher the cognitive workload: GA2 (quadratic term) on low cognitive workload: R2 = .02, p<0.001; moderate cognitive workload: R2 = .09, p<0.001; and high cognitive workload tasks: R2 = .14, p<0.001. Specifically, disproportionally lower scores were found for very (<32 weeks gestation) and moderately (32–33 weeks gestation) preterm children the higher the cognitive workload of the tasks. Early biological factors such as gestation and neonatal complications explained more of the variance in high (12.5%) compared with moderate (8.1%) and low cognitive workload tasks (1.7%). Conclusions: The cognitive workload model may help to explain variations of findings on the relationship of gestational age with cognitive performance in the literature. The findings have implications for routine cognitive follow-up, educational intervention, and basic research into neuro-plasticity and brain reorganization after preterm birth

Collaborative denoising autoencoder for high glycated haemoglobin prediction.

A pioneering study is presented demonstrating that the presence of high glycated haemoglobin (HbA1c) levels in a patient’s blood can be reliably predicted from routinely collected clinical data. This paves the way for performing early detection of Type-2 Diabetes Mellitus (T2DM). This will save healthcare providers a major cost associated with the administration and assessment of clinical tests for HbA1c. A novel collaborative denoising autoencoder framework is used to address this challenge. The framework builds an independent denoising autoencoder model for the high and low HbA1c level, which extracts feature representations in the latent space. A baseline model using just three features: patient age together with triglycerides and glucose level achieves 76% F1-score with an SVM classifier. The collaborative denoising autoencoder uses 78 features and can predict HbA1c level with 81% F1-score