Constant Factor Approximation for Balanced Cut in the PIE model

We propose and study a new semi-random semi-adversarial model for Balanced Cut, a planted model with permutation-invariant random edges (PIE). Our model is much more general than planted models considered previously. Consider a set of vertices V partitioned into two clusters $L$ and $R$ of equal size. Let $G$ be an arbitrary graph on $V$ with no edges between $L$ and $R$. Let $E_{random}$ be a set of edges sampled from an arbitrary permutation-invariant distribution (a distribution that is invariant under permutation of vertices in $L$ and in $R$). Then we say that $G + E_{random}$ is a graph with permutation-invariant random edges. We present an approximation algorithm for the Balanced Cut problem that finds a balanced cut of cost $O(|E_{random}|) + n \text{polylog}(n)$ in this model. In the regime when $|E_{random}| = \Omega(n \text{polylog}(n))$, this is a constant factor approximation with respect to the cost of the planted cut.Comment: Full version of the paper at the 46th ACM Symposium on the Theory of Computing (STOC 2014). 32 page

Infancy and beyond: Parents supporting the healthy sexual and emotional development of their children

The purpose of this project is to bring parental awareness to the subject matter, expand their knowledge base, and increase the parenting skill set related to childhood sexual development. The goal of this project is to shed light on childhood sexual development in service of best practice parenting, ultimately leading to optimal child outcomes. Providing parents with the knowledge to foster the healthy sexual development of their children is the ultimate goal. The participants were recruited from the California State University, San Bernardino (CSUSB) student body and were asked to fill out a demographic questionnaire

Preface

Preface for NEW: Emerging scholars in Australian Indigenous Studies, 201

Stress and Emotion Classification Using Jitter and Shimmer Features

In this paper, we evaluate the use of appended jitter and shimmer speech features for the classification of human speaking styles and of animal vocalization arousal levels. Jitter and shimmer features are extracted from the fundamental frequency contour and added to baseline spectral features, specifically Mel-frequency cepstral coefficients (MFCCs) for human speech and Greenwood function cepstral coefficients (GFCCs) for animal vocalizations. Hidden Markov models (HMMs) with Gaussian mixture models (GMMs) state distributions are used for classification. The appended jitter and shimmer features result in an increase in classification accuracy for several illustrative datasets, including the SUSAS dataset for human speaking styles as well as vocalizations labeled by arousal level for African elephant and Rhesus monkey species

The Antarctic ozone hole: An update

In the 30 years since the ozone hole was discovered, our understanding of the polar atmosphere has become much more complete. The worldwide response to the discovery was fast, but the recovery is slow

Is the Number of Sick Persons in a Cohort Constant Over Time?

Objectives: To estimate the number of persons in a cohort who are sick, over time. Methods: We calculated the number of sick persons in the Cardiovascular Health Study (CHS), a cohort study of older adults followed up to 14 years, using eight definitions of “healthy” and “sick”. We projected the number in each health state over time for a birth cohort. Results: The number of sick persons in CHS was approximately constant for 14 years, for all definitions of “sick”. The estimated number of sick persons in the birth cohort was approximately constant from ages 55-75, after which it decreased. Discussion: The relative excess of older persons who are sick in later life is caused by a decline in the number of healthy persons rather than an increase in the number who are sick. Cohort data that include the number of deaths can detect interesting patterns in aging and health

Basic

Basic is a collection of interrelated short stories which follow Sylvia Jones' progress through Army Basic Training. The stories track Sylvia's struggle to find her place both within the Army and within the family she has left behind. Numerous physical and emotional trials force Sylvia to confront her choice to join the Army. As her understanding of her fellow soldiers deepens, she begins to understand more about who she has been and who she is becoming