Learning Left Main Bifurcation Shape Features with an Autoencoder

Geometric characteristics of the coronary arteries have been suggested as potential markers for disease risk. However, evaluation of such characteristics rely on judgement by human experts, and are thus variable and may lack sophistication. Here we apply recent advances in 3D deep learning to automatically obtain shape representation of the Left Main Bifurcation (LMB) of the coronary artery. We train a Variational Auto-Encoder based on the FoldingNet architecture to encode LMB shape features in a 450-dimension feature vector. The geometric features of patient-specific LMBs can then be manipulated by modifying, combining or interpolating the feature vectors before decoding. We also show that these vectors, on average, perform better than hand-crafted features in predicting measures of adverse blood flow (oscillating shear index or 'OSI', relative residence time 'RRT' and time averaged wall shear stress 'TAWSS') with a R2 goodness of fit value of 84.1% compared to 79.7%. These learned representations can also be used in other downstream predictive modelling tasks where an encoded version of a LMB is needed

Recoil correction to the bound-electron g factor in H-like atoms to all orders in αZ\alpha Z

The nuclear recoil correction to the bound-electron g factor in H-like atoms is calculated to first order in $m/M$ and to all orders in $\alpha Z$. The calculation is performed in the range Z=1-100. A large contribution of terms of order $(\alpha Z)^5$ and higher is found. Even for hydrogen, the higher-order correction exceeds the $(\alpha Z)^4$ term, while for uranium it is above the leading $(\alpha Z)^2$ correction.Comment: 6 pages, 3 tables, 1 figur

Recoil correction to the ground state energy of hydrogenlike atoms

The recoil correction to the ground state energy of hydrogenlike atoms is calculated to all orders in \alpha Z in the range Z = 1-110. The nuclear size corrections to the recoil effect are partially taken into account. In the case of hydrogen, the relativistic recoil correction beyond the Salpeter contribution and the nonrelativistic nuclear size correction to the recoil effect, amounts to -7.2(2) kHz. The total recoil correction to the ground state energy in hydrogenlike uranium (^{238}U^{91+}) constitutes 0.46 eV.Comment: 16 pages, 1 figure (eps), Latex, submitted to Phys.Rev.

Screened self-energy correction to the 2p3/2-2s transition energy in Li-like ions

We present an ab initio calculation of the screened self-energy correction for (1s)^2 2p3/2 and (1s)^2 2s states of Li-like ions with nuclear charge numbers in the range Z = 12-100. The evaluation is carried out to all orders in the nuclear-strength parameter Z \alpha. This investigation concludes our calculations of all two-electron QED corrections for the 2p3/2-2s transition energy in Li-like ions and thus considerably improves theoretical predictions for this transition for high-Z ions

How much vector control is needed to achieve malaria elimination?

Roll Back Malaria's ambitious goals for global malaria reduction by 2015 represent a dilemma for National Malaria Control Programs (NMCPs) that are still far from malaria elimination. Current vector control efforts by NMCPs generally fall short of their potential, leaving many NMCPs wondering how much vector control it will take to achieve malaria elimination. We believe the answer is detailed in the relationships between the entomological inoculation rate (EIR) and four epidemiological measures of malaria in humans. To achieve adequate vector control, NMCPs must evaluate EIRs to identify problematic foci of transmission and reduce annual EIRs to less than one infectious bite per person

The Role of Landscape Connectivity in Planning and Implementing Conservation and Restoration Priorities. Issues in Ecology

Landscape connectivity, the extent to which a landscape facilitates the movements of organisms and their genes, faces critical threats from both fragmentation and habitat loss. Many conservation efforts focus on protecting and enhancing connectivity to offset the impacts of habitat loss and fragmentation on biodiversity conservation, and to increase the resilience of reserve networks to potential threats associated with climate change. Loss of connectivity can reduce the size and quality of available habitat, impede and disrupt movement (including dispersal) to new habitats, and affect seasonal migration patterns. These changes can lead, in turn, to detrimental effects for populations and species, including decreased carrying capacity, population declines, loss of genetic variation, and ultimately species extinction. Measuring and mapping connectivity is facilitated by a growing number of quantitative approaches that can integrate large amounts of information about organisms’ life histories, habitat quality, and other features essential to evaluating connectivity for a given population or species. However, identifying effective approaches for maintaining and restoring connectivity poses several challenges, and our understanding of how connectivity should be designed to mitigate the impacts of climate change is, as yet, in its infancy. Scientists and managers must confront and overcome several challenges inherent in evaluating and planning for connectivity, including: •characterizing the biology of focal species; •understanding the strengths and the limitations of the models used to evaluate connectivity; •considering spatial and temporal extent in connectivity planning; •using caution in extrapolating results outside of observed conditions; •considering non-linear relationships that can complicate assumed or expected ecological responses; •accounting and planning for anthropogenic change in the landscape; •using well-defined goals and objectives to drive the selection of methods used for evaluating and planning for connectivity; •and communicating to the general public in clear and meaningful language the importance of connectivity to improve awareness and strengthen policies for ensuring conservation. Several aspects of connectivity science deserve additional attention in order to improve the effectiveness of design and implementation. Research on species persistence, behavioral ecology, and community structure is needed to reduce the uncertainty associated with connectivity models. Evaluating and testing connectivity responses to climate change will be critical to achieving conservation goals in the face of the rapid changes that will confront many communities and ecosystems. All of these potential areas of advancement will fall short of conservation goals if we do not effectively incorporate human activities into connectivity planning. While this Issue identifies substantial uncertainties in mapping connectivity and evaluating resilience to climate change, it is also clear that integrating human and natural landscape conservation planning to enhance habitat connectivity is essential for biodiversity conservation