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Background Child maltreatment recidivism substantially increases the likelihood of adverse life outcomes, but there is little evidence that family preservation services are effective at reducing recidivism. Mothers in child welfare have very high rates of trauma exposure; maternal post-traumatic stress disorder (PTSD) is an intervention target that has the potential to reduce abuse and neglect. The Safe Mothers, Safe Children (SMSC) intervention program involves the delivery of an innovative combination of interventions, including Skills Training in Affective and Interpersonal Regulation (STAIR) and Parent-Child Interaction Therapy (PCIT). The combined intervention, Parenting-STAIR (P-STAIR), targets maternal PTSD and comorbid depression symptoms to reduce the adverse effects of PTSD on parenting, improve positive parenting skills, and prevent maltreatment recidivism. Methods This study is a two-arm randomized controlled trial: P-STAIR (23 sessions) versus supportive counseling (23 sessions). Participants are mothers receiving child welfare family preservation services (FPS), with a child in the age range of 1–8 years old and meeting diagnostic criteria for PTSD (with/without depression). Clinical assessment occurs at pre-treatment (baseline), two in-treatment assessments (mid-assessment #1 after module 9 and mid-assessment #2 after module 15), post-treatment, and at a 6-month follow-up. Recidivism will be measured using the New York State Child Welfare Registry (NYSCWR). We will enroll a total of 220 participants over 4 years: half (N = 110) randomly assigned to the P-STAIR condition and half (N = 110) to the supportive counseling condition. Discussion This is the first RCT to investigate the efficacy of P-STAIR. The findings for the trial have the potential to contribute to the expansion of evidence-based practices for maternal PTSD, maltreatment, and child welfare.

A key component of the phase diagram of many iron-based superconductors and electron-doped cuprates is believed to be a quantum critical point (QCP), delineating the onset of antiferromagnetic spin-density wave order in a quasi-two-dimensional metal. The universality class of this QCP is believed to play a fundamental role in the description of the proximate non-Fermi liquid and superconducting phases. A minimal model for this transition is the $\mathrm{O}(3)$ spin-fermion model. Despite many efforts, a definitive characterization of its universal properties is still lacking. Here, we numerically study the $\mathrm{O}(3)$ spin-fermion model and extract the scaling exponents and functional form of the static and zero-momentum dynamical spin susceptibility. We do this using a Hybrid Monte Carlo (HMC) algorithm with a novel auto-tuning procedure, which allows us to study unprecedentedly large systems of $80 \times 80$ sites. We find a strong violation of the Hertz-Millis form, contrary to all previous results. Furthermore, the form that we do observe provides good evidence that the universal scaling is actually governed by the analytically tractable fixed point discovered near perfect ``hot-spot'" nesting, even for a larger nesting window. Our predictions can be directly tested with neutron scattering. Additionally, the HMC method we introduce is generic and can be used to study other fermionic models of quantum criticality, where there is a strong need to simulate large systems., Comment: 16 pages, 9 figures (main text) + 8 pages, 10 figures (appendix)

Poor quality of drinking water delivered to homes by state utilities, and a large reliance on brackish ground water resources in parts of urban India, has resulted in the adoption of in-home water treatment solutions. The only existing in-home water treatment solution capable of desalination is reverse osmosis (RO). However, existing RO products can recover only 25â50% of the feed water supplied as usable product water. In this study, an alternative solution that relies on electrodialysis (ED) was designed and experimentally shown to achieve a recovery of 80%, producing 12Â L/h of water at the desired salinity of 350Â ppm from a feed salinity of 3000Â ppm. The cost and size of the proposed system were also found to be comparable to existing in-home RO systems. In-home ED water treatment systems could compete with existing RO products while providing the advantage of improved water-conservation in water-stressed India. Keywords: Electrodialysis, Desalination, Reverse osmosis, Brackish water

PURPOSE. Jeune's asphyxiating thoracic dystrophy (JATD) is an autosomal recessive disorder with symptoms of retinal degeneration, kidney cysts, and chondrodysplasia and results from mutations in the ift80 gene. This study was conducted to characterize zebrafish lacking ift80 function for photoreceptor degeneration and defects in ciliogenesis to establish zebrafish as a vertebrate model for visual dysfunction in JATD and to determine whether ift80 interacts genetically with Bardet-Biedl syndrome (BBS) genes. METHODS. Zebrafish were injected with morpholinos (MOs) targeted to the ift80 gene. Retinas were analyzed by histology, transmission electron microscopy, and immunohistochemistry. Ear and kidney cilia were analyzed by whole-mount immunostaining. Intraflagellar transport (IFT) particle composition was subjected to Western blot analysis. Genetic interactions were tested by coinjection of MOs against ift80 and bbs4 or bbs8 followed by in situ hybridization. RESULTS. Zebrafish lacking ift80 function exhibited defects in photoreceptor outer segment formation and photoreceptor death. Staining with opsin antibodies revealed opsin mislocalization in both rods and cones. Ultrastructural analysis showed abnormal disc stacking and shortened photoreceptor outer segments. The kinocilia of the ear and motile cilia in the kidney were shorter and reduced in number. Western blot analysis revealed a slight increase in the stability of other IFT proteins. Coinjection of MOs against ift80 and BBS genes led to convergent-extension defects. CONCLUSIONS. Zebrafish lacking ift80 exhibited defects characteristic of JATD. Because the developing outer segments degenerated, Ift80 could possibly act as a maintenance factor for the IFT particle.

Desalination of high salinity water is an effective way of improving the aesthetic quality of drinking water and has been demonstrated to be a characteristic valued by consumers. Across India, 60% of the groundwater, the primary water source for millions, is brackish or contains a high salt content with total dissolved solids (TDS) ranging from 500 parts per million (ppm) to 3,000ppm. The government does not provide sufficient desalination treatment before the water reaches the tap of a consumer. Therefore consumers have turned to in-home desalination. However, current products are either expensive or have low recovery, product water output per untreated feed water, (∼30%) wasting water resources. Electrodialysis (ED) is a promising technology that desalinates water while maintaining higher recovery (up to 95%) compared to existing consumer reverse osmosis (RO) products. This paper first explores the in-home desalination market to determine critical design requirements for an in-home ED system. A model was then used to evaluate and optimize the performance of an ED stack at this scale and designated salinity range. Additionally, testing was conducted in order to validate the model and demonstrate feasibility. Finally, cost estimates of the proposed in-home ED system and product design concept are presented. The results of this work identified a system design that provides consumers with up to 80% recovery of feed water with cost and size competitive to currently available in-home RO products.Copyright © 2015 by ASME

In many biomedical studies, the observed data may violate the assumptions of standard parametric methods. In these situations, Bayesian methods are appealing since nonparametric priors, such as the Dirichlet process (DP), can incorporate a priori knowledge regarding the shape or location of an unknown distribution and exact inferences are available using Markov chain Monte Carlo methods. Despite the promise of Bayesian nonparametric methods, computation can be difficult under large sample sizes. In addition, there is a paucity of methods for multiple event time data and for testing across multiple groups. In this dissertation, we propose three methods which address important computational, modelling, and testing issues in Bayesian nonparametrics. Our first method is a computationally simple approach to fitting Bayesian semiparametric random effects models to large longitudinal data sets. Our approach involves fitting a model to a smaller set of pseudo-data, which is constructed using expert opinion. The research was motivated by data from the Collaborative Perinatal Project, which was a prospective epidemiology study consisting of over 30,000 children. We next develop a dynamic frailty model which accounts for age-dependent changes in susceptibility to a repeated health event, such as the occurrence of new tumors. Our model generalizes the traditional shared frailty model for multiple event time data to accommodate smooth, time dependent trends in the frailty, baseline hazard, and covariate effects. We also relax our assumptions on the frailty using DP priors. Lastly, we present a Bayesian nonparametric method for testing for changes in a response distribution with an ordinal predictor. The research was motivated by data from toxicology studies, in which dose may affect both the shape and location of the response distribution. Using a generalization of the dynamic mixture of DPs (Dunson, 2006, Biostatistics, to appear), we test for equivalence in the unknown distribution across dose groups and estimate threshold doses. Our method accommodates multivariate responses without complication.