1,159 research outputs found
AMS measurements of cosmogenic and supernova-ejected radionuclides in deep-sea sediment cores
Samples of two deep-sea sediment cores from the Indian Ocean are analyzed
with accelerator mass spectrometry (AMS) to search for traces of recent
supernova activity around 2 Myr ago. Here, long-lived radionuclides, which are
synthesized in massive stars and ejected in supernova explosions, namely 26Al,
53Mn and 60Fe, are extracted from the sediment samples. The cosmogenic isotope
10Be, which is mainly produced in the Earths atmosphere, is analyzed for dating
purposes of the marine sediment cores. The first AMS measurement results for
10Be and 26Al are presented, which represent for the first time a detailed
study in the time period of 1.7-3.1 Myr with high time resolution. Our first
results do not support a significant extraterrestrial signal of 26Al above
terrestrial background. However, there is evidence that, like 10Be, 26Al might
be a valuable isotope for dating of deep-sea sediment cores for the past few
million years.Comment: 5 pages, 2 figures, Proceedings of the Heavy Ion Accelerator
Symposium on Fundamental and Applied Science, 2013, will be published by the
EPJ Web of conference
Combinatorial Assortment Optimization
Assortment optimization refers to the problem of designing a slate of
products to offer potential customers, such as stocking the shelves in a
convenience store. The price of each product is fixed in advance, and a
probabilistic choice function describes which product a customer will choose
from any given subset. We introduce the combinatorial assortment problem, where
each customer may select a bundle of products. We consider a model of consumer
choice where the relative value of different bundles is described by a
valuation function, while individual customers may differ in their absolute
willingness to pay, and study the complexity of the resulting optimization
problem. We show that any sub-polynomial approximation to the problem requires
exponentially many demand queries when the valuation function is XOS, and that
no FPTAS exists even for succinctly-representable submodular valuations. On the
positive side, we show how to obtain constant approximations under a
"well-priced" condition, where each product's price is sufficiently high. We
also provide an exact algorithm for -additive valuations, and show how to
extend our results to a learning setting where the seller must infer the
customers' preferences from their purchasing behavior
Role of EG-VEGF in Human Placentation: Physiological and Pathological Implications
International audienc
IgG light chain-independent secretion of heavy chain dimers: consequence for therapeutic antibody production and design
Rodent monoclonal antibodies with specificity towards important biological targets are developed for therapeutic use by a process of humanisation. This process involves the creation of molecules, which retain the specificity of the rodent antibody but contain predominantly human coding sequence. Here we show that some humanised heavy chains can fold, form dimers and be secreted even in the absence of light chain. Quality control of recombinant antibody assembly in vivo is thought to rely upon folding of the heavy chain CH1 domain. This domain acts as a switch for secretion, only folding upon interaction with the light chain CL domain. We show that the secreted heavy-chain dimers contain folded CH1 domains and contribute to the heterogeneity of antibody species secreted during the expression of therapeutic antibodies. This subversion of the normal quality control process is dependent upon the heavy chain variable domain, is prevalent with engineered antibodies and can occur when only the Fab fragments are expressed. This discovery will impact on the efficient production of both humanised antibodies as well as the design of novel antibody formats
Line-distortion, Bandwidth and Path-length of a graph
We investigate the minimum line-distortion and the minimum bandwidth problems
on unweighted graphs and their relations with the minimum length of a
Robertson-Seymour's path-decomposition. The length of a path-decomposition of a
graph is the largest diameter of a bag in the decomposition. The path-length of
a graph is the minimum length over all its path-decompositions. In particular,
we show:
- if a graph can be embedded into the line with distortion , then
admits a Robertson-Seymour's path-decomposition with bags of diameter at most
in ;
- for every class of graphs with path-length bounded by a constant, there
exist an efficient constant-factor approximation algorithm for the minimum
line-distortion problem and an efficient constant-factor approximation
algorithm for the minimum bandwidth problem;
- there is an efficient 2-approximation algorithm for computing the
path-length of an arbitrary graph;
- AT-free graphs and some intersection families of graphs have path-length at
most 2;
- for AT-free graphs, there exist a linear time 8-approximation algorithm for
the minimum line-distortion problem and a linear time 4-approximation algorithm
for the minimum bandwidth problem
Thresholded Covering Algorithms for Robust and Max-Min Optimization
The general problem of robust optimization is this: one of several possible
scenarios will appear tomorrow, but things are more expensive tomorrow than
they are today. What should you anticipatorily buy today, so that the
worst-case cost (summed over both days) is minimized? Feige et al. and
Khandekar et al. considered the k-robust model where the possible outcomes
tomorrow are given by all demand-subsets of size k, and gave algorithms for the
set cover problem, and the Steiner tree and facility location problems in this
model, respectively.
In this paper, we give the following simple and intuitive template for
k-robust problems: "having built some anticipatory solution, if there exists a
single demand whose augmentation cost is larger than some threshold, augment
the anticipatory solution to cover this demand as well, and repeat". In this
paper we show that this template gives us improved approximation algorithms for
k-robust Steiner tree and set cover, and the first approximation algorithms for
k-robust Steiner forest, minimum-cut and multicut. All our approximation ratios
(except for multicut) are almost best possible.
As a by-product of our techniques, we also get algorithms for max-min
problems of the form: "given a covering problem instance, which k of the
elements are costliest to cover?".Comment: 24 page
The Age-Redshift Relation for Standard Cosmology
We present compact, analytic expressions for the age-redshift relation
for standard Friedmann-Lema\^ \itre-Robertson-Walker (FLRW)
cosmology. The new expressions are given in terms of incomplete Legendre
elliptic integrals and evaluate much faster than by direct numerical
integration.Comment: 13 pages, 3 figure
Detecting and Characterizing Small Dense Bipartite-like Subgraphs by the Bipartiteness Ratio Measure
We study the problem of finding and characterizing subgraphs with small
\textit{bipartiteness ratio}. We give a bicriteria approximation algorithm
\verb|SwpDB| such that if there exists a subset of volume at most and
bipartiteness ratio , then for any , it finds a set
of volume at most and bipartiteness ratio at most
. By combining a truncation operation, we give a local
algorithm \verb|LocDB|, which has asymptotically the same approximation
guarantee as the algorithm \verb|SwpDB| on both the volume and bipartiteness
ratio of the output set, and runs in time
, independent of the size of the
graph. Finally, we give a spectral characterization of the small dense
bipartite-like subgraphs by using the th \textit{largest} eigenvalue of the
Laplacian of the graph.Comment: 17 pages; ISAAC 201
How asynchrony affects rumor spreading time
International audienceIn standard randomized (push-pull) rumor spreading, nodes communicate in synchronized rounds. In each round every node contacts a random neighbor in order to exchange the rumor (i.e., either push the rumor to its neighbor or pull it from the neighbor). A natural asynchronous variant of this algorithm is one where each node has an independent Poisson clock with rate 1, and every node contacts a random neighbor whenever its clock ticks. This asynchronous variant is arguably a more realistic model in various settings, including message broadcasting in communication networks, and information dissemination in social networks. In this paper we study how asynchrony affects the rumor spreading time, that is, the time before a rumor originated at a single node spreads to all nodes in the graph. Our first result states that the asynchronous push-pull rumor spreading time is asymptotically bounded by the standard synchronous time. Precisely, we show that for any graph G on n nodes, where the synchronous push-pull protocol informs all nodes within T (G) rounds with high probability, the asynchronous protocol needs at most time O(T (G) + log n) to inform all nodes with high probability. On the other hand, we show that the expected synchronous push-pull rumor spreading time is bounded by O(√ n) times the expected asynchronous time. These results improve upon the bounds for both directions shown recently by Acan et al. (PODC 2015). An interesting implication of our first result is that in regular graphs, the weaker push-only variant of synchronous rumor spreading has the same asymptotic performance as the synchronous push-pull algorithm
Near-optimal asymmetric binary matrix partitions
We study the asymmetric binary matrix partition problem that was recently
introduced by Alon et al. (WINE 2013) to model the impact of asymmetric
information on the revenue of the seller in take-it-or-leave-it sales.
Instances of the problem consist of an binary matrix and a
probability distribution over its columns. A partition scheme
consists of a partition for each row of . The partition acts
as a smoothing operator on row that distributes the expected value of each
partition subset proportionally to all its entries. Given a scheme that
induces a smooth matrix , the partition value is the expected maximum
column entry of . The objective is to find a partition scheme such that
the resulting partition value is maximized. We present a -approximation
algorithm for the case where the probability distribution is uniform and a
-approximation algorithm for non-uniform distributions, significantly
improving results of Alon et al. Although our first algorithm is combinatorial
(and very simple), the analysis is based on linear programming and duality
arguments. In our second result we exploit a nice relation of the problem to
submodular welfare maximization.Comment: 17 page
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