Judicial Review, Constitutional Interpretation, and the Democratic Dilemma: Proposing a “Controlled Activism” Alternative

No problem generates more debate among constitutional scholars than how to approach constitutional interpretation. This Article critiques two representative theories (or families of theories), originalism and nontextualism, and offers a principled alternative, which we call “controlled activism.” By candidly acknowledging the judge’s creative role in constitutional lawmaking, controlled activism promises real limits on judicial discretion

Judicial Review, Constitutional Interpretation, and the Democratic Dilemma: Proposing a “Controlled Activism” Alternative

No problem generates more debate among constitutional scholars than how to approach constitutional interpretation. This Article critiques two representative theories (or families of theories), originalism and nontextualism, and offers a principled alternative, which we call “controlled activism.” By candidly acknowledging the judge’s creative role in constitutional lawmaking, controlled activism promises real limits on judicial discretion

Machine learning to detect marine animals in UAV imagery: effect of morphology, spacing, behaviour and habitat

Machine learning algorithms are being increasingly used to process large volumes of wildlife imagery data from unmanned aerial vehicles (UAVs); however, suitable algorithms to monitor multiple species are required to enhance efficiency. Here, we developed a machine learning algorithm using a low-cost computer. We trained a convolutional neural network and tested its performance in: (1) distinguishing focal organisms of three marine taxa (Australian fur seals, loggerhead sea turtles and Australasian gannets; body size ranges: 0.8–2.5 m, 0.6–1.0 m, and 0.8–0.9 m, respectively); and (2) simultaneously delineating the fine-scale movement trajectories of multiple sea turtles at a fish cleaning station. For all species, the algorithm performed best at detecting individuals of similar body length, displaying consistent behaviour or occupying uniform habitat (proportion of individuals detected, or recall of 0.94, 0.79 and 0.75 for gannets, seals and turtles, respectively). For gannets, performance was impacted by spacing (huddling pairs with offspring) and behaviour (resting vs. flying shapes, overall precision: 0.74). For seals, accuracy was impacted by morphology (sexual dimorphism and pups), spacing (huddling and creches) and habitat complexity (seal sized boulders) (overall precision: 0.27). For sea turtles, performance was impacted by habitat complexity, position in water column, spacing, behaviour (interacting individuals) and turbidity (overall precision: 0.24); body size variation had no impact. For sea turtle trajectories, locations were estimated with a relative positioning error of <50 cm. In conclusion, we demonstrate that, while the same machine learning algorithm can be used to survey multiple species, no single algorithm captures all components optimally within a given site. We recommend that, rather than attempting to fully automate detection of UAV imagery data, semi-automation is implemented (i.e. part automated and part manual, as commonly practised for photo-identification). Approaches to enhance the efficiency of manual detection are required in parallel to the development of effective implementation of machine learning algorithms

Lithium in the Symbiotic Mira V407 Cyg

We report an identification of the lithium resonance doublet LiI 6708A in the spectrum of V407 Cyg, a symbiotic Mira with a pulsation period of about 745 days. The resolution of the spectra used was R~18500 and the measured equivalent width of the line is ~0.34A. It is suggested that the lithium enrichment is due to hot bottom burning in the intermediate mass AGB variable, although other possible origins cannot be totally ruled out. In contrast to lithium-rich AGB stars in the Magellanic clouds, ZrO 5551A, 6474A absorption bands were not found in the spectrum of V407Cyg. These are the bands used to classify the S-type stars at low-resolution. Although we identified weak ZrO 5718A, 6412A these are not visible in the low-resolution spectra, and we therefore classify the Mira in V407 Cyg as an M type. This, together with other published work, suggests lithium enrichment can precede the third dredge up of s-process enriched material in galactic AGB stars.Comment: 4 pages, 2 figures, to be published in MNRA

Co-production of light p-, s- and r-process isotopes in the high-entropy wind of type II supernovae

We have performed large-scale nucleosynthesis calculations within the high-entropy-wind (HEW) scenario of type II supernovae. The primary aim was to constrain the conditions for the production of the classical "p-only" isotopes of the light trans-Fe elements. We find, however, that for electron fractions in the range 0.458 $\le$ Y$_e$ $\le$ 0.478, sizeable abundances of p-, s- and r-process nuclei between $^{64}$Zn and $^{98}$Ru are coproduced in the HEW at low entropies (S $\le$ 100) by a primary charged-particle process after an $\alpha$-rich freezeout. With the above Y$_e$ -- S correlation, most of the predicted isotopic abundance ratios within a given element (e.g. $^{64}$Zn(p)/$^{70}$Zn(r) or $^{92}$Mo(p)/$^{94}$Mo(p)), as well as of neighboring elements (e.g. $^{70}$Ge(s+p)/$^{74}$Se(p) or $^{74}$Se(p)/$^{78}$Kr(p)) agree with the observed Solar-System ratios. Taking the Mo isotopic chain as a particularly challenging example, we show that our HEW model can account for the production of all 7 stable isotopes, from "p-only" $^{92}$Mo, via "s-only" $^{96}$Mo up to "r-only" $^{100}$Mo. Furthermore, our model is able to reproduce the isotopic composition of Mo in presolar SiC X-grains.}Comment: 10 pages, 2 figure

Defining marine important bird areas: Testing the foraging radius approach

International audienceRecent international initiatives have promoted a number of different approaches to identify marine Important Bird and biodiversity Areas (IBAs), which are important areas for foraging, migrating or over-wintering seabirds. The ‘Foraging Radius Approach’ is one of these and uses known foraging range and habitat preferences to predict the size and location of foraging areas around breeding colonies. Here we assess the performance of the Foraging Radius Approach using GPS tracking data from six seabird species with a variety of foraging modes. For each species we compared the population home-range areas of our six study species with the home-range areas defined using the Foraging Radius Approach. We also assessed whether basic information on depth preferences from tracking data could improve these home-range area estimates. Foraging Radius Approach home-range areas based on maximum foraging radii encompassed the entire population home-range of five out of six of our study species but overestimated the size of the population home-range area in every case. The mean maximum foraging radius overestimated the population home-range areas by a factor of 4–14 for five of the six species whilst the mean foraging radius overestimated the population home-range area for half of the species and underestimated for the rest. In the absence of other data, the Foraging Radius Approach appears to provide a reasonable basis for preliminary marine IBA identification. We suggest that using the mean value of all previously reported maximum foraging radii, informed by basic depth preferences provides the most appropriate prediction, balancing the needs of seabirds with efficient use of marine space