81 research outputs found
Effectiveness of 10 polymorphic microsatellite markers for parentage and pedigree analysis in plateau pika (Ochotona curzoniae)
<p>Abstract</p> <p>Background</p> <p>The plateau pika <it>(Ochotona curzoniae) </it>is an underground-dwelling mammal, native to the Tibetan plateau of China. A set of 10 polymorphic microsatellite loci has been developed earlier. Its reliability for parentage assignment has been tested in a plateau pika population. Two family groups with a known pedigree were used to validate the power of this set of markers.</p> <p>Results</p> <p>The error in parentage assignment using a combination of these 10 loci was very low as indicated by their power of discrimination (0.803 - 0.932), power of exclusion (0.351 - 0.887), and an effectiveness of the combined probability of exclusion in parentage assignment of 99.999%.</p> <p>Conclusion</p> <p>All the offspring of a family could be assigned to their biological mother; and their father or relatives could also be identified. This set of markers therefore provides a powerful and efficient tool for parentage assignment and other population analyses in the plateau pika.</p
Extending Resource Monotones using Kan Extensions
In this paper we generalize the framework proposed by Gour and Tomamichel
regarding extensions of monotones for resource theories. A monotone for a
resource theory assigns a real number to each resource in the theory signifying
the utility or the value of the resource. Gour and Tomamichel studied the
problem of extending monotones using set-theoretical framework when a resource
theory embeds fully and faithfully into the larger theory. One can generalize
the problem of computing monotone extensions to scenarios when there exists a
functorial transformation of one resource theory to another instead of just a
full and faithful inclusion. In this article, we show that (point-wise) Kan
extensions provide a precise categorical framework to describe and compute such
extensions of monotones. To set up monontone extensions using Kan extensions,
we introduce partitioned categories (pCat) as a framework for resource theories
and pCat functors to formalize relationship between resource theories. We
describe monotones as pCat functors into , and describe
extending monotones along any pCat functor using Kan extensions. We show how
our framework works by applying it to extend entanglement monotones for
bipartite pure states to bipartite mixed states, to extend classical
divergences to the quantum setting, and to extend a non-uniformity monotone
from classical probabilistic theory to quantum theory.Comment: Accepted at Applied Category Theory 2022, 19 page
Node Copying: A Random Graph Model for Effective Graph Sampling
There has been an increased interest in applying machine learning techniques
on relational structured-data based on an observed graph. Often, this graph is
not fully representative of the true relationship amongst nodes. In these
settings, building a generative model conditioned on the observed graph allows
to take the graph uncertainty into account. Various existing techniques either
rely on restrictive assumptions, fail to preserve topological properties within
the samples or are prohibitively expensive for larger graphs. In this work, we
introduce the node copying model for constructing a distribution over graphs.
Sampling of a random graph is carried out by replacing each node's neighbors by
those of a randomly sampled similar node. The sampled graphs preserve key
characteristics of the graph structure without explicitly targeting them.
Additionally, sampling from this model is extremely simple and scales linearly
with the nodes. We show the usefulness of the copying model in three tasks.
First, in node classification, a Bayesian formulation based on node copying
achieves higher accuracy in sparse data settings. Second, we employ our
proposed model to mitigate the effect of adversarial attacks on the graph
topology. Last, incorporation of the model in a recommendation system setting
improves recall over state-of-the-art methods
Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation
Out-of-distribution (OOD) detection is important for deploying reliable
machine learning models on real-world applications. Recent advances in outlier
exposure have shown promising results on OOD detection via fine-tuning model
with informatively sampled auxiliary outliers. However, previous methods assume
that the collected outliers can be sufficiently large and representative to
cover the boundary between ID and OOD data, which might be impractical and
challenging. In this work, we propose a novel framework, namely, Diversified
Outlier Exposure (DivOE), for effective OOD detection via informative
extrapolation based on the given auxiliary outliers. Specifically, DivOE
introduces a new learning objective, which diversifies the auxiliary
distribution by explicitly synthesizing more informative outliers for
extrapolation during training. It leverages a multi-step optimization method to
generate novel outliers beyond the original ones, which is compatible with many
variants of outlier exposure. Extensive experiments and analyses have been
conducted to characterize and demonstrate the effectiveness of the proposed
DivOE. The code is publicly available at: https://github.com/tmlr-group/DivOE.Comment: accepted by NeurIPS 202
Complete Genome and Transcriptomes of Streptococcus parasanguinis FW213: Phylogenic Relations and Potential Virulence Mechanisms
Streptococcus parasanguinis, a primary colonizer of the tooth surface, is also an opportunistic pathogen for subacute endocarditis. The complete genome of strain FW213 was determined using the traditional shotgun sequencing approach and further refined by the transcriptomes of cells in early exponential and early stationary growth phases in this study. The transcriptomes also discovered 10 transcripts encoding known hypothetical proteins, one pseudogene, five transcripts matched to the Rfam and additional 87 putative small RNAs within the intergenic regions defined by the GLIMMER analysis. The genome contains five acquired genomic islands (GIs) encoding proteins which potentially contribute to the overall pathogenic capacity and fitness of this microbe. The differential expression of the GIs and various open reading frames outside the GIs at the two growth phases suggested that FW213 possess a range of mechanisms to avoid host immune clearance, to colonize host tissues, to survive within oral biofilms and to overcome various environmental insults. Furthermore, the comparative genome analysis of five S. parasanguinis strains indicates that albeit S. parasanguinis strains are highly conserved, variations in the genome content exist. These variations may reflect differences in pathogenic potential between the strains
Simulation study of BESIII with stitched CMOS pixel detector using ACTS
Reconstruction of tracks of charged particles with high precision is very
crucial for HEP experiments to achieve their physics goals. As the tracking
detector of BESIII experiment, the BESIII drift chamber has suffered from aging
effects resulting in degraded tracking performance after operation for about 15
years. To preserve and enhance the tracking performance of BESIII, one of the
proposals is to add one layer of thin CMOS pixel sensor in cylindrical shape
based on the state-of-the-art stitching technology, between the beam pipe and
the drift chamber. The improvement of tracking performance of BESIII with such
an additional pixel detector compared to that with only the existing drift
chamber is studied using the modern common tracking software ACTS, which
provides a set of detector-agnostic and highly performant tracking algorithms
that have demonstrated promising performance for a few high energy physics and
nuclear physics experiments
The Genomes of Oryza sativa: A History of Duplications
We report improved whole-genome shotgun sequences for the genomes of indica and japonica rice, both with multimegabase contiguity, or almost 1,000-fold improvement over the drafts of 2002. Tested against a nonredundant collection of 19,079 full-length cDNAs, 97.7% of the genes are aligned, without fragmentation, to the mapped super-scaffolds of one or the other genome. We introduce a gene identification procedure for plants that does not rely on similarity to known genes to remove erroneous predictions resulting from transposable elements. Using the available EST data to adjust for residual errors in the predictions, the estimated gene count is at least 38,000–40,000. Only 2%–3% of the genes are unique to any one subspecies, comparable to the amount of sequence that might still be missing. Despite this lack of variation in gene content, there is enormous variation in the intergenic regions. At least a quarter of the two sequences could not be aligned, and where they could be aligned, single nucleotide polymorphism (SNP) rates varied from as little as 3.0 SNP/kb in the coding regions to 27.6 SNP/kb in the transposable elements. A more inclusive new approach for analyzing duplication history is introduced here. It reveals an ancient whole-genome duplication, a recent segmental duplication on Chromosomes 11 and 12, and massive ongoing individual gene duplications. We find 18 distinct pairs of duplicated segments that cover 65.7% of the genome; 17 of these pairs date back to a common time before the divergence of the grasses. More important, ongoing individual gene duplications provide a never-ending source of raw material for gene genesis and are major contributors to the differences between members of the grass family
Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries
Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely
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