38,168 research outputs found
Age and growth of longfinned eels (Anguilla dieffenbachii) in pastoral and forested streams in the Waikato River basin, and in two hydro-electric lakes in the North Island, New Zealand
Growth rates of New Zealand endemic longfinned eels (Anguilla dieffenbachii) from streams in pasture and indigenous forest, and from two hydroelectric lakes (Lakes Karapiro and Matahina), were estimated by otolith examination. Habitat-specific growth was further investigated with measurement of widths of annual bands in otoliths. Longfinned eels 170-1095 mm in length ranged between 4 and 60 years old (N=252). Eels in pastoral streams grew faster (mean annual length increment ±95% CL = 24 ± 3 mm to 36 ± 7 mm) than eels in streams in indigenous forest (annual length increment 12 ± 2 mm to 15 ± 3 mm). Eels from the hydro-electric lakes had growth rates (annual length increments 19 ± 4 and 19 + 7 mm) similar to eels from pastoral streams. Otoliths of most eels showed annual band widths that indicated growth in several different habitats, corresponding to growth during upstream migration, and limited movement among adult habitats. Estimated age at marketable size (220 g) ranged between 7 and 26 years. The particularly slow growth of longfinned eels in streams in indigenous forest has considerable implications for management. The fast growth rates of eels in hydro-electric lakes provides evidence for the potential of increased eel production by stocking. The probable selective production of female eels in these lakes may be nationally important to allow enhancement of breeding stocks
Bounding Embeddings of VC Classes into Maximum Classes
One of the earliest conjectures in computational learning theory-the Sample
Compression conjecture-asserts that concept classes (equivalently set systems)
admit compression schemes of size linear in their VC dimension. To-date this
statement is known to be true for maximum classes---those that possess maximum
cardinality for their VC dimension. The most promising approach to positively
resolving the conjecture is by embedding general VC classes into maximum
classes without super-linear increase to their VC dimensions, as such
embeddings would extend the known compression schemes to all VC classes. We
show that maximum classes can be characterised by a local-connectivity property
of the graph obtained by viewing the class as a cubical complex. This geometric
characterisation of maximum VC classes is applied to prove a negative embedding
result which demonstrates VC-d classes that cannot be embedded in any maximum
class of VC dimension lower than 2d. On the other hand, we show that every VC-d
class C embeds in a VC-(d+D) maximum class where D is the deficiency of C,
i.e., the difference between the cardinalities of a maximum VC-d class and of
C. For VC-2 classes in binary n-cubes for 4 <= n <= 6, we give best possible
results on embedding into maximum classes. For some special classes of Boolean
functions, relationships with maximum classes are investigated. Finally we give
a general recursive procedure for embedding VC-d classes into VC-(d+k) maximum
classes for smallest k.Comment: 22 pages, 2 figure
Gravitational radiation from the r-mode instability
The instability in the r-modes of rotating neutron stars can (in principle)
emit substantial amounts of gravitational radiation (GR) which might be
detectable by LIGO and similar detectors. Estimates are given here of the
detectability of this GR based the non-linear simulations of the r-mode
instability by Lindblom, Tohline and Vallisneri. The burst of GR produced by
the instability in the rapidly rotating 1.4 solar mass neutron star in this
simulation is fairly monochromatic with frequency near 960 Hz and duration
about 100 s. A simple analytical expression is derived here for the optimal S/N
for detecting the GR from this type of source. For an object located at a
distance of 20 Mpc we estimate the optimal S/N to be in the range 1.2 to about
12.0 depending on the LIGO II configuration.Comment: 8 pages, 4 figure
Density Functional Theory screening of gas-treatment strategies for stabilization of high energy-density lithium metal anodes
To explore the potential of molecular gas treatment of freshly cut lithium
foils in non-electrolyte based passivation of high energy-density Li anodes,
density functional theory (DFT) has been used to study the decomposition of
molecular gases on metallic lithium surfaces. By combining DFT geometry
optimization and Molecular Dynamics, the effects of atmospheric (N2, O2, CO2)
and hazardous (F2, SO2) gas decomposition on Li(bcc) (100), (110), and (111)
surfaces on relative surface energies, work functions, and emerging electronic
and elastic properties are investigated. The simulations suggest that exposure
to different molecular gases can be used to induce and control reconstructions
of the metal Li surface and substantial changes (up to over 1 eV) in the work
function of the passivated system. Contrary to the other considered gases,
which form metallic adlayers, SO2 treatment emerges as the most effective in
creating an insulating passivation layer for dosages <= 1 mono-layer. The
substantial Li->adsorbate charge transfer and adlayer relaxation produce marked
elastic stiffening of the interface, with the smallest change shown by
nitrogen-treated adlayers
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