Paid Family and Medical Leave in New Hampshire: Who Has It? Who Takes It?

This brief uses data collected by the Granite State Poll in 2016 to examine New Hampshire workers’ access to paid family and medical leave and the use of paid or unpaid leave for family and medical reasons. Understanding who lacks access to paid family and medical leave benefits and the underlying factors contributing to differences in those who take time away from work for family caregiving is important. Without access to paid family and medical leave, New Hampshire’s working families may face barriers to financial stability, employment, and future opportunities. Author Kristin Smith reports that about one-third of New Hampshire workers have jobs without extended paid leave to tend to their own illness; about half lack access to parental leave; and two-thirds lack access to paid leave to care for an ill family member. Less than a third of workers have access to all three types of extended paid leave (for their own illness, parental leave, and care for a family member). Workers living in families earning less than $60,000 a year have less access to extended paid family and medical leave benefits than do those with higher incomes. Women are less likely to have jobs that provide paid family and medical leave but are more likely to take leave. Sixty percent of employed women have taken paid or unpaid family and medical leave compared with 40 percent of employed men. New Hampshire men who know another man who has taken leave without negative consequences are twice as likely to take leave themselves compared to men who do not know another man taking leave (52 and 24 percent, respectively)

Hierarchical modeling of molecular energies using a deep neural network

We introduce the Hierarchically Interacting Particle Neural Network (HIP-NN) to model molecular properties from datasets of quantum calculations. Inspired by a many-body expansion, HIP-NN decomposes properties, such as energy, as a sum over hierarchical terms. These terms are generated from a neural network--a composition of many nonlinear transformations--acting on a representation of the molecule. HIP-NN achieves state-of-the-art performance on a dataset of 131k ground state organic molecules, and predicts energies with 0.26 kcal/mol mean absolute error. With minimal tuning, our model is also competitive on a dataset of molecular dynamics trajectories. In addition to enabling accurate energy predictions, the hierarchical structure of HIP-NN helps to identify regions of model uncertainty

Child care subsidies critical for low-income families amid rising child care expenses

The high cost of child care is a barrier to employment among low-income families with young children. Child care subsidies are designed to support both parental employment and child development by lowering the cost of child care and making high-quality child care affordable to low-income families. This policy brief compares the shares of income spent on child care in 2005 and 2011 using data collected by the U.S. Census Bureau. Authors Kristin Smith and Nicholas Adams report that child care expenditures were higher on average in 2011 than in 2005 (in constant 2011 dollars) and that employed, poor mothers with child care expenses spent more than one-third of their incomes on child care in 2005 and 201

The Recognition of State Crime and the Syrian Uprising

This study aims to establish why state crime is not always recognised as such. The criminological analysis of state crime is a fledgling field of interest, although over the past decade there have been significant developments. As a result of these recent developments it is possible to theoretically interact with state crime. Through theoretical engagement, within a real life context, the phenomenon of recognition of state crime is explored. A case study of the recognition of state crime during the first 15 months of the Syrian uprising provides the real life context. An ‘adaptive theory’ approach is adopted promoting the flexible use of theory to examine the underlying reasons as to why some state crime is recognised whilst some is not. Appreciating that recognition of state crime does not occur in a vacuum, the context within which the Syrian uprising occurred was examined. Recognition of state crime during the first 15 months of the Syrian uprising was then subject to investigation through a multi-level structural framework influenced by the state crime literature. Theoretical concepts from the state crime literature are also employed as an analytical tool for understanding the complexities involved in the subject matter. In determining the underlying reasons as to why only some state crime is recognised the study proposes an account of recognition of state crime. Finally, potential areas for further research are highlighted to establish state crime, and the recognition of state crime, as worthy of concentrated inquiry across the social sciences

Cultivar diversity as a means of ecologically intensifying dry matter production in a perennial forage stand

The relationship between genotypic diversity and productivity has not been adequately explored in perennial forage production systems despite strong theoretical and empirical evidence supporting diversity\u27s role in ecosystem functioning in other managed and unmanaged systems. We conducted a two-year field experiment with six cultivars of an agriculturally important forage grass, Lolium perenne L. (perennial ryegrass). Dry matter production of L. perenne and the weed community that emerged from the soil seed bank were measured each year in treatments that ranged from cultivar monocultures to three- and six-way cultivar mixtures, all sown at a constant seeding rate. Mean L. perenne dry matter production increased with increasing cultivar diversity and was highest in mixtures that contained cultivars representing the greatest additive trait range (calculated on rankings of three traits: winter hardiness, heading date, and tolerance to grazing). Mixtures had greater yields than those predicted by the mean of their component monoculture yields, but there was evidence that highly productive cultivars may have dampened over-yielding in mixtures. Weed abundance was correlated with L. perenne dry matter, but not L. perenne cultivar diversity. These results suggest that multi-cultivar mixtures may have utility as an approach to ecologically intensifying perennial forage production. Additional research will be necessary to determine the mechanisms responsible for the over-yielding observed in this study and the generality of these findings

Bayesian Modelling of Direct and Indirect Effects of Marine Reserves on Fishes : A thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Statistics at Massey University, Albany, New Zealand.

This thesis reviews and develops modern advanced statistical methodology for sampling and modelling count data from marine ecological studies, with specific applications to quantifying potential direct and indirect effects of marine reserves on fishes in north eastern New Zealand. Counts of snapper (Pagrus auratus: Sparidae) from baited underwater video surveys from an unbalanced, multi-year, hierarchical sampling programme were analysed using a Bayesian Generalised Linear Mixed Model (GLMM) approach, which allowed the integer counts to be explicitly modelled while incorporating multiple fixed and random effects. Overdispersion was modelled using a zero-inflated negative-binomial error distribution. A parsimonious method for zero inflation was developed, where the mean of the count distribution is explicitly linked to the probability of an excess zero. Comparisons of variance components identified marine reserve status as the greatest source of variation in counts of snapper above the legal size limit. Relative densities inside reserves were, on average, 13-times greater than outside reserves. Small benthic reef fishes inside and outside the same three reserves were surveyed to evaluate evidence for potential indirect effects of marine reserves via restored populations of fishery-targeted predators such as snapper. Sites for sampling were obtained randomly from populations of interest using spatial data and geo-referencing tools in R—a rarely used approach that is recommended here more generally to improve field-based ecological surveys. Resultant multispecies count data were analysed with multivariate GLMMs implemented in the R package MCMCglmm, based on a multivariate Poisson lognormal error distribution. Posterior distributions for hypothesised effects of interest were calculated directly for each species. While reserves did not appear to affect densities of small fishes, reserve-habitat interactions indicated that some endemic species of triplefin (Tripterygiidae) had different associations with small-scale habitat gradients inside vs outside reserves. These patterns were consistent with a behavioural risk effect, where small fishes may be more strongly attracted to refuge habitats to avoid predators inside vs outside reserves. The approaches developed and implemented in this thesis respond to some of the major current statistical and logistic challenges inherent in the analysis of counts of organisms. This work provides useful exemplar pathways for rigorous study design, modelling and inference in ecological systems

Modelling the Galactic bar using OGLE-II Red Clump Giant Stars

Red clump giant stars can be used as distance indicators to trace the mass distribution of the Galactic bar. We use RCG stars from 44 bulge fields from the OGLE-II microlensing collaboration database to constrain analytic tri-axial models for the Galactic bar. We find the bar major axis is oriented at an angle of 24 - 27 degrees to the Sun-Galactic centre line-of-sight. The ratio of semi-major and semi-minor bar axis scale lengths in the Galactic plane x_0, y_0, and vertical bar scale length z_0, is x_0 : y_0 : z_0 = 10 : 3.5 : 2.6, suggesting a slightly more prolate bar structure than the working model of Gerhard (2002) which gives the scale length ratios as x_0 : y_0 : z_0 = 10 : 4 : 3 .Comment: 15 pages, 10 figures, accepted for publication in MNRAS. Supplementary material available online: 10 pages, 10 figure

Intrusion Detection Systems for Community Wireless Mesh Networks

Wireless mesh networks are being increasingly used to provide affordable network connectivity to communities where wired deployment strategies are either not possible or are prohibitively expensive. Unfortunately, computer networks (including mesh networks) are frequently being exploited by increasingly profit-driven and insidious attackers, which can affect their utility for legitimate use. In response to this, a number of countermeasures have been developed, including intrusion detection systems that aim to detect anomalous behaviour caused by attacks. We present a set of socio-technical challenges associated with developing an intrusion detection system for a community wireless mesh network. The attack space on a mesh network is particularly large; we motivate the need for and describe the challenges of adopting an asset-driven approach to managing this space. Finally, we present an initial design of a modular architecture for intrusion detection, highlighting how it addresses the identified challenges