scholarly journals COMBINATORIAL RECONSTRUCTION OF HALF-SIBLING GROUPS FROM MICROSATELLITE DATA

2010 ◽  
Vol 08 (02) ◽  
pp. 337-356 ◽  
Author(s):  
SAAD I. SHEIKH ◽  
TANYA Y. BERGER-WOLF ◽  
ASHFAQ A. KHOKHAR ◽  
ISABEL C. CABALLERO ◽  
MARY V. ASHLEY ◽  
...  
Keyword(s):  
Exact Solutions ◽  
Experimental Results ◽  
Microsatellite Data ◽  
Reconstruction Problem ◽  
Full Sibling ◽  
Synthetic Datasets ◽  
Sibling Group ◽  
Half Sibling ◽  
Sibling Groups

While full-sibling group reconstruction from microsatellite data is a well-studied problem, reconstruction of half-sibling groups is much less studied, theoretically challenging, and computationally demanding. In this paper, we present a formulation of the half-sibling reconstruction problem and prove its APX-hardness. We also present exact solutions for this formulation and develop heuristics. Using biological and synthetic datasets we present experimental results and compare them with the leading alternative software COLONY. We show that our results are competitive and allow half-sibling group reconstruction in the presence of polygamy, which is prevalent in nature.

scholarly journals Survival and Growth of Amur maackia Seedlings Across North America

HortScience ◽  
1997 ◽  
Vol 32 (3) ◽  
pp. 508B-508
Author(s):  
Anthony S. Aiello ◽  
William R. Graves
Keyword(s):  
North America ◽  
Field Trials ◽  
Stem Length ◽  
Site Location ◽  
Growing Seasons ◽  
Survival And Growth ◽  
Sibling Group ◽  
Selection Of ◽  
Half Sibling ◽  
Sibling Groups

Amur maackia (Maackia amurensis Rupr. & Maxim.) has potential for use in small, urban, or cold landscapes. Although Amur maackia is becoming increasingly popular, plants are currently grown from open-pollinated seed populations, and there has been no selection of cultivars. We have addressed the effects of climate on growth and have begun field trials for selection of horticulturally superior genotypes. In May 1995, a field trial near Ames was begun with 337 plants. These were selected from more than 2000 greenhouse-grown seedlings to represent 32 half-sibling seed groups from 16 arboreta across North America. After two growing seasons, the increase in stem length among seed groups ranged from 3% to 75%. Survival rate did not vary with seed group. In a related study, 30 plants from six half-sibling groups have been established at each of 10 sites in the U.S. and four in Canada to assess effects of location on survival and growth. The influence of seed group on survival after 1 year varied with the trial site location. Survival among combinations of half-sibling group and trial location ranged from 0% to 100% (mean = 54%). Half-sibling group and trial location affected growth without interaction. The greatest growth across locations, an 83% increase in stem length, was shown by seeds that originated from a tree at the Arnold Arboretum. At the 14 locations, changes in stem length over half-sibling groups varied from <0% in Ithaca, N.Y., to 179% in Puyallup, Wash.

Socialisation Tactics of the Spectacled Parrotlet (Forpus Conspicillatus)

Behaviour ◽  
1991 ◽  
Vol 119 (1-2) ◽  
pp. 1-29 ◽  
Author(s):  
Kyra Garnetzke-Stollmann ◽  
Dierk Franck
Keyword(s):  
Sexual Behaviour ◽  
Early Stage ◽  
Rank Order ◽  
Host Group ◽  
Pair Bonds ◽  
Group Members ◽  
The One ◽  
And Function ◽  
Sibling Group ◽  
Sibling Groups

AbstractSpectacled parrotlets live in a complex system of individual relationships throughout their lives. The adults form exclusive pair bonds, addressing all friendly and sexual behaviour patterns to each other. Pair mates cooperate in agonistic situations. As long as they stay close together they hold the same rank-order position. In mate-choice experiments females (not males) significantly preferred a mate which formerly held a high social position. There are also non-exclusive pair bonds, which are far less stable than exclusive ones. Only exclusive pairs have a good chance to occupy a breeding cavity. All group members are synchronized in many of their activities, such as foraging, preening or resting. They are keenly interested in unusual activities of other group members. Social learning, including copying sexual techniques, seems to be essential. After fledging the parents keep their offspring at a distance from a very early stage. Instead of a close parent-offspring relationship the fledglings form sibling groups with their nest mates. Over a period of months siblings remain the main interaction partners for all friendly and playful activities. They also support one another in agonistic situations. In the first months of life even courtship feeding and sexual behaviour are addressed predominantly to siblings. Thus a pair-like relationship is established between siblings, anticipating the permanent pair bond of adults. Single fledglings, deprived of the experience of a sibling group, remained poorly integrated into the group. They developed alternative socialisation tactics, namely (1) joining a host group of unrelated siblings, (2) renewing a friendly partnership with the parents, (3) helping to protect and feed younger siblings or even unrelated fledglings and (4) seeking early partnership with unrelated group members. Out of 10 single fledglings only the one that was accepted by a host sibling group immediately after fledging became well integrated into the whole group and reproduced well. It is argued that sibling groups offer good opportunities for learning partnership and function as a safe basis for exploring the social environment. It is tentatively proposed that single fledglings have a decreased probability of reproductive success.

scholarly journals Differentiated Attentive Representation Learning for Sentence Classification

2018 ◽  
Author(s):  
Qianrong Zhou ◽  
Xiaojie Wang ◽  
Xuan Dong
Keyword(s):  
Representation Learning ◽  
Learning Model ◽  
Attention Mechanism ◽  
Experimental Results ◽  
Sentence Classification ◽  
Synthetic Datasets

Attention-based models have shown to be effective in learning representations for sentence classification. They are typically equipped with multi-hop attention mechanism. However, existing multi-hop models still suffer from the problem of paying much attention to the most frequently noticed words, which might not be important to classify the current sentence. And there is a lack of explicitly effective way that helps the attention to be shifted out of a wrong part in the sentence. In this paper, we alleviate this problem by proposing a differentiated attentive learning model. It is composed of two branches of attention subnets and an example discriminator. An explicit signal with the loss information of the first attention subnet is passed on to the second one to drive them to learn different attentive preference. The example discriminator then selects the suitable attention subnet for sentence classification. Experimental results on real and synthetic datasets demonstrate the effectiveness of our model.

scholarly journals Multiple weak supervision for short text classification

2022 ◽  
Author(s):  
Li-Ming Chen ◽  
Bao-Xin Xiu ◽  
Zhao-Yun Ding
Keyword(s):  
Text Classification ◽  
Classification Problem ◽  
Experimental Results ◽  
Prior Work ◽  
Weak Supervision ◽  
Short Text ◽  
Imbalanced Classification ◽  
Distant Supervision ◽  
Synthetic Datasets ◽  
Independent Model

AbstractFor short text classification, insufficient labeled data, data sparsity, and imbalanced classification have become three major challenges. For this, we proposed multiple weak supervision, which can label unlabeled data automatically. Different from prior work, the proposed method can generate probabilistic labels through conditional independent model. What’s more, experiments were conducted to verify the effectiveness of multiple weak supervision. According to experimental results on public dadasets, real datasets and synthetic datasets, unlabeled imbalanced short text classification problem can be solved effectively by multiple weak supervision. Notably, without reducing precision, recall, and F1-score can be improved by adding distant supervision clustering, which can be used to meet different application needs.

scholarly journals Adaptive Double-Exploration Tradeoff for Outlier Detection

2020 ◽  
Vol 34 (04) ◽  
pp. 6837-6844
Author(s):  
Xiaojin Zhang ◽  
Honglei Zhuang ◽  
Shengyu Zhang ◽  
Yuan Zhou
Keyword(s):  
Confidence Interval ◽  
Outlier Detection ◽  
Real World ◽  
Efficient Algorithm ◽  
Experimental Results ◽  
Sample Complexity ◽  
Bandit Problem ◽  
Real World Datasets ◽  
Synthetic Datasets ◽  
The Individual

We study a variant of the thresholding bandit problem (TBP) in the context of outlier detection, where the objective is to identify the outliers whose rewards are above a threshold. Distinct from the traditional TBP, the threshold is defined as a function of the rewards of all the arms, which is motivated by the criterion for identifying outliers. The learner needs to explore the rewards of the arms as well as the threshold. We refer to this problem as "double exploration for outlier detection". We construct an adaptively updated confidence interval for the threshold, based on the estimated value of the threshold in the previous rounds. Furthermore, by automatically trading off exploring the individual arms and exploring the outlier threshold, we provide an efficient algorithm in terms of the sample complexity. Experimental results on both synthetic datasets and real-world datasets demonstrate the efficiency of our algorithm.

scholarly journals Researching Why-Not Questions in Skyline Query Based on Orthogonal Range

Electronics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 500 ◽  
Author(s):  
Ping Sun ◽  
Caimei Liang ◽  
Guohui Li ◽  
Ling Yuan
Keyword(s):  
Experimental Results ◽  
Skyline Query ◽  
High Quality ◽  
Query Refinement ◽  
Skyline Queries ◽  
The Real ◽  
Query Efficiency ◽  
Synthetic Datasets

This paper aims to answer “why-not” questions in skyline queries based on the orthogonal query range (i.e., ORSQ). These queries retrieve skyline points within a rectangular query range, which improves query efficiency. Answering why-not questions in ORSQ can help users analyze query results and make decisions. We discuss the causes of why-not questions in ORSQ. Then, we outline how to modify the why-not point and the orthogonal query range so that the why-not point is included in the result of the skyline query based on the orthogonal range. When the why-not point is in the orthogonal range, we show how to modify the why-not point and narrow the orthogonal range. We also present how to expand the orthogonal range when the why-not point is not in the orthogonal range. We effectively combine query refinement and data modification techniques to produce meaningful answers. The experimental results demonstrate that the proposed algorithms have high-quality explanations for why-not questions in ORSQ in the real and synthetic datasets.

Marriage with Kin

2018 ◽  
pp. 107-134
Author(s):  
S. C. Humphreys
Keyword(s):  
Full Sibling ◽  
Direct Descendant ◽  
The Law ◽  
Half Sibling

Marriage was often used to strengthen links between kin: an Athenian could marry any kinswoman except a direct ascendant, a direct descendant, a full sibling, or a matrilateral half-sibling. This chapter covers the law governing the marriages of epikleroi, interests in property, status anomaly, and propinquity.

Even-Sized Clustering Based on Optimization and its Variants

2018 ◽  
Vol 22 (1) ◽  
pp. 62-69 ◽  
Author(s):  
Yasunori Endo ◽  
Yukihiro Hamasuna ◽  
Tsubasa Hirano ◽  
Naohiko Kinoshita ◽  
◽  
...  
Keyword(s):  
Linear Programming ◽  
Simplex Method ◽  
Benchmark Dataset ◽  
Experimental Results ◽  
Clustering Method ◽  
Initial Value ◽  
Cluster Number ◽  
Clustering Problem ◽  
Dataset Size ◽  
Synthetic Datasets

A clustering method referred to as K-member clustering classifies a dataset into certain clusters, the size of which is more than a given constant K. Even-sized clustering, which classifies a dataset into even-sized clusters, is also considered along with K-member clustering. In our previous study, we proposed Even-sized Clustering Based on Optimization (ECBO) to output adequate results by formulating an even-sized clustering problem as linear programming. The simplex method is used to calculate the belongingness of each object to clusters in ECBO. In this study, ECBO is extended by introducing ideas that were introduced in K-means or fuzzy c-means to resolve problems of initial-value dependence, robustness against outliers, calculation costs, and nonlinear boundaries of clusters. We also reconsider the relation between the dataset size, the cluster number, and K in ECBO. Moreover, we verify the effectiveness of the variants of ECBO based on experimental results using synthetic datasets and a benchmark dataset.

Self-employment: the significance of ability, desire and opportunity

2018 ◽  
Vol 24 (2) ◽  
pp. 538-552
Author(s):  
Per Broomé ◽  
Henrik Ohlsson
Keyword(s):  
Design Methodology ◽  
Genetic Factor ◽  
Content Type ◽  
Sibling Pairs ◽  
Full Sibling ◽  
Twin Model ◽  
Self Employment ◽  
Family Factor ◽  
Internal And External Factors ◽  
Half Sibling

PurposeThe purpose of this paper is to examine the influence of ability, desire and opportunity on the individual’s intention to be self-employed.Design/methodology/approachThe authors created a database from Swedish national registers consisting of all individuals residing in Sweden sometime during the period 1997-2010 and selected all 333,001 full sibling pairs, 12,810 maternal half sibling pairs and 15,944 paternal half sibling pairs. Three types of entrepreneurs were defined based on information from the Swedish Tax Register. The authors divided the intention to be self-employed into ability and desire and defined ability as a genetic factor and desire as a common family factor. A classical twin model was used to separate the variance of the outcome variables into genetic, common and unshared environmental factors.FindingsThe study demonstrates that the influence from opportunity on the intention to be self-employed is generally strong and that all factors, ability, desire and opportunity, differ, both in size and content, for the three outcomes of entrepreneurs.Originality/valueThe authors divide self-employment into three distinct company types, which enables a sophisticated additive genetic analysis of the ability, desire and opportunity to be self-employed. The authors contribute to the understanding of why individuals become self-employed by examining the influences from internal and external factors of family on the intentions of self-employment.

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