Negotiated Investment Strategy

The Negotiated Investment Strategy (NIS) was created by the urban affairs program at the Kettering Foundation as a vehicle for cities to shape their own future. The creators of the NIS, in the late 1970\u27s, observed that while most major cities needed help, such help was hard to come by. Three reasons account for this. First, the assistance that was available to cities, particularly from the federal government, was often in the form of categorical grants, and it was difficult to tailor the assistance to the particular needs of the city. Second, there was a great deal of duplication of existing programs and a lack of coordination between them. Finally, cities had not discovered how they might capitalize upon their own assets, particularly: the facilities that were in place, the city\u27s infrastructure, and the commitment to the city by people from both the public and private sector

Exome-wide association study of pancreatic cancer risk

We conducted a case-control exome-wide association study to discover germline variants in coding regions that affect risk for pancreatic cancer, combining data from 5 studies. We analyzed exome and genome sequencing data from 437 patients with pancreatic cancer (cases) and 1922 individuals not known to have cancer (controls). In the primary analysis, BRCA2 had the strongest enrichment for rare inactivating variants (17/437 cases vs 3/1922 controls) (P=3.27x10(-6); exome-wide statistical significance threshold P<2.5x10(-6)). Cases had more rare inactivating variants in DNA repair genes than controls, even after excluding 13 genes known to predispose to pancreatic cancer (adjusted odds ratio, 1.35, P=.045). At the suggestive threshold (P<.001), 6 genes were enriched for rare damaging variants (UHMK1, AP1G2, DNTA, CHST6, FGFR3, and EPHA1) and 7 genes had associations with pancreatic cancer risk, based on the sequence-kernel association test. We confirmed variants in BRCA2 as the most common high-penetrant genetic factor associated with pancreatic cancer and we also identified candidate pancreatic cancer genes. Large collaborations and novel approaches are needed to overcome the genetic heterogeneity of pancreatic cancer predisposition

Modeling Perennial Bioenergy Crops in the E3SM Land Model (ELMv2)

Perennial bioenergy crops are increasingly important for the production of ethanol and other renewable fuels, and as part of an agricultural system that alters the climate through its impact on biogeophysical and biogeochemical properties of the terrestrial ecosystem. Few Earth System Models (ESMs) represent such crops, however. In this study, we expand the Energy Exascale Earth System Land Model to include perennial bioenergy crops with a high potential for mitigating climate change. We focus on high-productivity miscanthus and switchgrass, estimating various parameters associated with their different growth stages and performing a global sensitivity analysis to identify and optimize these parameters. The sensitivity analysis identifies five parameters associated with phenology, carbon/nitrogen allocation, stomatal conductance, and maintenance respiration as the most sensitive parameters for carbon and energy fluxes. We calibrated and validated the model against observations and found that the model closely captures the observed seasonality and the magnitude of carbon fluxes. The validated model represents the latent heat flux fairly well, but sensible heat flux for miscanthus is not well captured. Finally, we validated the model against observed leaf area index (LAI) and harvest amount and found modeled LAI captured observed seasonality, although the model underestimates LAI and harvest amount. This work provides a foundation for future ESM analyses of the interactions between perennial bioenergy crops and carbon, water, and energy dynamics in the larger Earth system, and sets the stage for studying the impact of future biofuel expansion on climate and terrestrial systems

Challenge of Reducing Perinatal Mortality in Rural Congo: Findings of a Prospective, Population-based Study

Each year, an estimated six million perinatal deaths occur worldwide, and 98% of these deaths occur in lowand middle-income countries. These estimates are based on surveys in both urban and rural areas, and they may underrepresent the problem in rural areas. This study was conducted to quantify perinatal mortality, to identify the associated risk factors, and to determine the most common causes of early neonatal death in a rural area of the Democratic Republic of the Congo (DRC). Data were collected on 1,892 births. Risk factors associated with perinatal deaths were identified using multivariate analysis with logistic regression models. Causes of early neonatal deaths were determined by physician-review of information describing death. The perinatal mortality rate was 61 per 1,000 births; the stillbirth rate was 30 per 1,000 births; and the early neonatal death rate was 32 per 1,000 livebirths. Clinically-relevant factors independently associated with perinatal death included: low birthweight [odds ratio (OR)=13.51, 95% confidence interval (CI) 7.82-23.35], breech presentation (OR)=12.41; 95% CI 4.62-33.33), lack of prenatal care (OR=2.70, 95% CI 1.81-4.02), and parity greater than 4 (OR=1.93 95% CI 1.11-3.37). Over one-half of early neonatal deaths (n=37) occurred during the first two postnatal days, and the most common causes were low birthweight/prematurity (47%), asphyxia (34%), and infection (8%). The high perinatal mortality rate in rural communities in the DRC, approximately one-half of which is attributable to early neonatal death, may be modifiable. Specifically, deaths due to breech presentation, the second most common risk factor, may be reduced by making available emergency obstetric care. Most neonatal deaths occur soon after birth, and nearly three-quarters are caused by low birthweight/prematurity or asphyxia. Neonatal mortality might be reduced by targeting interventions to improve neonatal resuscitation and care of larger preterm infants

Full Connectivity: Corners, edges and faces

We develop a cluster expansion for the probability of full connectivity of high density random networks in confined geometries. In contrast to percolation phenomena at lower densities, boundary effects, which have previously been largely neglected, are not only relevant but dominant. We derive general analytical formulas that show a persistence of universality in a different form to percolation theory, and provide numerical confirmation. We also demonstrate the simplicity of our approach in three simple but instructive examples and discuss the practical benefits of its application to different models.Comment: 28 pages, 8 figure

Reduced perinatal mortality following enhanced training of birth attendants in the Democratic Republic of Congo: a time-dependent effect

<p>Abstract</p> <p>Background</p> <p>In many developing countries, the majority of births are attended by traditional birth attendants, who lack formal training in neonatal resuscitation and other essential care required by the newly born infant. In these countries, the major causes of neonatal mortality are birth asphyxia, infection, and low-birth-weight/prematurity. Death from these causes is potentially modifiable using low-cost interventions, including neonatal resuscitation training. The purpose of this study was to evaluate the effect on perinatal mortality of training birth attendants in a rural area of the Democratic Republic of Congo (DRC) using two established programs.</p> <p>Methods</p> <p>This study, a secondary analysis of DRC-specific data collected during a multi-country study, was conducted in two phases. The effect of training using the WHO Essential Newborn Care (ENC) program was evaluated using an active baseline design, followed by a cluster randomized trial of training using an adaptation of a neonatal resuscitation program (NRP). The perinatal mortality rates before ENC, after ENC training, and after randomization to additional NRP training or continued care were compared. In addition, the influence of time following resuscitation training was investigated by examining change in perinatal mortality during sequential three-month increments following ENC training.</p> <p>Results</p> <p>More than two-thirds of deliveries were attended by traditional birth attendants and occurred in homes; these proportions decreased after ENC training. There was no apparent decline in perinatal mortality when the outcome of all deliveries prior to ENC training was compared to those after ENC but before NRP training. However, there was a gradual but significant decline in perinatal mortality during the year following ENC training (RR 0.73; 95% CI: 0.56-0.96), which was independently associated with time following training. The decline was attributable to a decline in early neonatal mortality. NRP training had no demonstrable effect on early neonatal mortality.</p> <p>Conclusion</p> <p>Training DRC birth attendants using the ENC program reduces perinatal mortality. However, a period of utilization and re-enforcement of training may be necessary before a decline in mortality occurs. ENC training has the potential to be a low cost, high impact intervention in developing countries.</p> <p>Trial registration</p> <p>This trial has been registered at <url>http://www.clinicaltrials.gov</url> (identifier <a href="http://www.clinicaltrials.gov/ct2/show/NCT00136708">NCT00136708</a>).</p

The Exoplanet Modeling and Analysis Center at NASA Goddard

The Exoplanet Modeling and Analysis Center (EMAC) at NASA Goddard Space Flight Center is a web-based catalog, repository, and integration platform for modeling and analysis resources focused on the study of exoplanet characteristics and environments. EMAC hosts user-submitted resources ranging in category from planetary interior models to data visualization tools. Other features of EMAC include integrated web tools developed by the EMAC team in collaboration with the tools' original author(s) and video demonstrations of a growing number of hosted tools. EMAC aims to be a comprehensive repository for researchers to access a variety of exoplanet resources that can assist them in their work, and currently hosts a growing number of code bases, models, and tools. EMAC is a key project of the NASA GSFC Sellers Exoplanet Environments Collaboration (SEEC) and can be accessed at https://emac.gsfc.nasa.gov.Comment: 3 pages and 1 figure. Published in RNAA

Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settings

BACKGROUND: To describe quantitative data quality monitoring and performance metrics adopted by the Global Network´s (GN) Maternal Newborn Health Registry (MNHR), a maternal and perinatal population-based registry (MPPBR) based in low and middle income countries (LMICs). METHODS: Ongoing prospective, population-based data on all pregnancy outcomes within defined geographical locations participating in the GN have been collected since 2008. Data quality metrics were defined and are implemented at the cluster, site and the central level to ensure data quality. Quantitative performance metrics are described for data collected between 2010 and 2013. RESULTS: Delivery outcome rates over 95% illustrate that all sites are successful in following patients from pregnancy through delivery. Examples of specific performance metric reports illustrate how both the metrics and reporting process are used to identify cluster-level and site-level quality issues and illustrate how those metrics track over time. Other summary reports (e.g. the increasing proportion of measured birth weight compared to estimated and missing birth weight) illustrate how a site has improved quality over time. CONCLUSION: High quality MPPBRs such as the MNHR provide key information on pregnancy outcomes to local and international health officials where civil registration systems are lacking. The MNHR has measures in place to monitor data collection procedures and improve the quality of data collected. Sites have increasingly achieved acceptable values of performance metrics over time, indicating improvements in data quality, but the quality control program must continue to evolve to optimize the use of the MNHR to assess the impact of community interventions in research protocols in pregnancy and perinatal health.Fil: Goudar, Shivaprasad S.. KLE University. Jawaharlal Nehru Medical College; IndiaFil: Stolka, Kristen B.. Research Triangle Institute International; Estados UnidosFil: Koso Thomas, Marion. Eunice Kennedy Shriver National Institute of Child Health and Human Development; Estados UnidosFil: Honnungar, Narayan V.. KLE University. Jawaharlal Nehru Medical College; IndiaFil: Mastiholi, Shivanand C.. KLE University. Jawaharlal Nehru Medical College; IndiaFil: Ramadurg, Umesh Y.. S. Nijalingappa Medical College; IndiaFil: Dhaded, Sangappa M.. KLE University. Jawaharlal Nehru Medical College; IndiaFil: Pasha, Omrana. Aga Khan University; PakistánFil: Patel, Archana. Indira Gandhi Government Medical College and Lata Medical Research Foundation; IndiaFil: Esamai, Fabian. University School of Medicine; KeniaFil: Chomba, Elwyn. University of Zambia; ZambiaFil: Garces, Ana. Universidad de San Carlos; GuatemalaFil: Althabe, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Carlo, Waldemar A.. University of Alabama at Birmingahm; Estados UnidosFil: Goldenberg, Robert L.. Columbia University; Estados UnidosFil: Hibberd, Patricia L.. Massachusetts General Hospital for Children; Estados UnidosFil: Liechty, Edward A.. Indiana University; Estados UnidosFil: Krebs, Nancy F.. University of Colorado School of Medicine; Estados UnidosFil: Hambidge, Michael K.. University of Colorado School of Medicine; Estados UnidosFil: Moore, Janet L.. Research Triangle Institute International; Estados UnidosFil: Wallace, Dennis D.. Research Triangle Institute International; Estados UnidosFil: Derman, Richard J. Christiana Care Health Services; Estados UnidosFil: Bhalachandra, Kodkany S.. KLE University. Jawaharlal Nehru Medical College; IndiaFil: Bose, Carl L.. University of North Carolina; Estados Unido

Keeping weight off: Mindfulness-Based Stress Reduction alters amygdala functional connectivity during weight loss maintenance in a randomized control trial

Obesity is associated with significant comorbidities and financial costs. While behavioral interventions produce clinically meaningful weight loss, weight loss maintenance is challenging. The objective was to improve understanding of the neural and psychological mechanisms modified by mindfulness that may predict clinical outcomes. Individuals who intentionally recently lost weight were randomized to Mindfulness-Based Stress Reduction (MBSR) or a control healthy living course. Anthropometric and psychological factors were measured at baseline, 8 weeks and 6 months. Functional connectivity (FC) analysis was performed at baseline and 8 weeks to examine FC changes between regions of interest selected a priori, and independent components identified by independent component analysis. The association of pre-post FC changes with 6-month weight and psychometric outcomes was then analyzed. Significant group x time interaction was found for FC between the amygdala and ventromedial prefrontal cortex, such that FC increased in the MBSR group and decreased in controls. Non-significant changes in weight were observed at 6 months, where the mindfulness group maintained their weight while the controls showed a weight increase of 3.4% in BMI. Change in FC at 8-weeks between ventromedial prefrontal cortex and several ROIs was associated with change in depression symptoms but not weight at 6 months. This pilot study provides preliminary evidence of neural mechanisms that may be involved in MBSR\u27s impact on weight loss maintenance that may be useful for designing future clinical trials and mechanistic studies