Advanced biofuel technologies : status and barriers

Large-scale production of crop based (first generation) biofuels may not be feasible without adversely affecting global food supply or encroaching on other important land uses. Because alternatives to liquid fossil fuels are important to develop in order to address greenhouse gas mitigation and other energy policy objectives, the potential for increased use of advanced (non-crop, second generation) biofuel production technologies has significant policy relevance. This study reviews the current status ofseveral advanced biofuel technologies. Technically, it would be possible to produce a large portion of transportation fuels using advanced biofuel technologies, specifically those that can be grown using a small portion of the world's land area (for example, microalgae), or those grown on arable lands without affecting food supply (for example, agricultural residues). However, serious technical barriers limit the near-term commercial application of advanced biofuels technologies. Key technical barriers include low conversion efficiency from biomass to fuel, limits on supply of key enzymes used in conversion, large energy requirements for operation, and dependence in many cases on commercially unproven technology. Despite a large future potential, large-scale expansion of advanced biofuels technologies is unlikely unless and until further research and development lead to lowering these barriers.Energy Production and Transportation,Climate Change Mitigation and Green House Gases,Renewable Energy,Crops&Crop Management Systems,Sanitation and Sewerage

Measuring and Correcting Response Heaping Arising From the Use of Prototypes

Imprecision in respondent recall can cause response heaping in frequency data for particular values (e.g., 5, 10, 15). In human dimensions research, heaping can occur for variables such as days of participation (e.g., hunting, fishing), animals/fish harvested, or money spent on licenses. Distributions with heaps can bias population estimates because the means and totals can be inflated or deflated. Because bias can result in poor management decisions, determining if the bias is large enough to matter is important. This note introduces the logic and flow of a deheaping program that estimates bias in means and totals when people use approximate responses (i.e., prototypes). The program can make estimates even when spikes occur due to bag limits. The program is available online, and smooths heaps at multiples of 5 (numbers ending in 5 and 0) and 7 (e.g., 7, 14, 21), and produces standard deviations in estimates

Expression of Hepatic Cytochrome P450 Drug Metabolizing Enzymes in Diabetes and Diabetic Nephropathy

The prevalence of diabetes worldwide is rapidly increasing. Polypharmacy, along with a high risk of adverse drug reactions, is common in diabetic patients. Cytochrome P450 (CYP) 3A and 2C drug metabolizing enzymes are reduced in chronic kidney disease (CKD), altering drug pharmacokinetics and contributing to adverse drug reactions. A large fraction of commonly prescribed drugs are metabolized by CYP3A and CYP2C. Approximately 40% of all CKD cases are attributed to diabetic nephropathy (DN) and early DN presents as mild kidney disease. This study aims to evaluate the impact of diabetes and DN on levels and activity of hepatic CYP3A and CYP2C drug-metabolizing enzymes. Diabetes was induced in male C57BL/6 mice and female hPXR/hCAR/CYP3A4 humanized mice using streptozotocin (STZ). Male STZ-treated mice showed no differences in mRNA levels of Cyp3a11 and Cyp2c29, while female STZ-treated mice had significantly decreased mRNA levels of hCAR and Cyp2e1. Male C57BL/6 mice had no differences in Cyp3a11 enzymatic activity, while female hPXR/hCAR/CYP3A4 STZ-treated mice had an increased CYP3A4 enzymatic activity. Small changes in CYP expression and activity in diabetes and DN may lead to altered drug pharmacokinetics. This study highlights the importance of understanding changes in drug disposition to reduce clinically significant adverse drug reactions

On identifying polycystic ovary syndrome in the Clinical Data Warehouse at Boston Medical Center

INTRODUCTION: Polycystic ovary syndrome (PCOS) is characterized by hyperandrogenemia, oligoanovulation, and numerous ovarian cysts. Although the most common cause of female factor infertility, its characteristics and metabolic risks are difficult to study due to its heterogeneity. Additionally, ethnic-specific data is scarce. Hospital electronic medical records and the diverse patient population at Boston Medical Center (BMC) may provide an avenue for investigating the longitudinal nature of PCOS and its race-specific characteristics. OBJECTIVES: 1. Describe the Clinical Data Warehouse (CDW) dataset available for studying PCOS. 2. Develop an automated method for extracting ovarian features from written ultrasound reports. 3. Identify PCOS patients from their record of the three cardinal PCOS features. METHODS: Patients evaluated on at least one of the three cardinal PCOS features, between October 1, 2003 and September 30, 2015 were queried from the BMC CDW. This thesis describes methods for cleaning the data, as well as the development of an ultrasound classifier based on natural language processing techniques. RESULTS: On a validation set of 1000 random ultrasounds, the automatic ultrasound classifier had a recall and precision for the presence of PCOM, 99.0% and 94.2%, respectively. Overall, 2421 cases of PCOS were identified, with 1010 not receiving a diagnosis. Black patients had twice the odds of being underdiagnosed compared to White patients (OR: 2.09; 95% CI: 1.69–2.59). CONCLUSIONS: Ascertaining PCOS through the medical record offers advantages over self-reported PCOS, including documentation of disease and recorded measurements. In the future, this PCOS dataset can be used in conjunction with cardiovascular and metabolic outcomes for developing a predictive model

Buckets of Water into the Ocean: Non-public Revenue in Public Charter and Traditional Public Schools

The funding of K-12 education remains a contentious public policy issue. Questions of funding adequacy and equity across school sectors, school districts and individual schools are prominent in discussions of how to improve educational outcomes, especially for students from disadvantaged backgrounds (Downes & Stiefel 2008; Ladd 2008). Although scholars are divided regarding the extent to which money affects student outcomes in K-12 education (Jackson, Johnson, & Persico 2015; Hanushek, 1997; Burtless 1996), there is basic agreement that more education revenue is better so long as the increased resources are directed towards productive educational activities and programs (Murnane & Levy 1996). If you ask education practitioners, the majority will say that more resources will make their schools better

Generalized wordlength patterns and strength

Xu and Wu (2001) defined the \emph{generalized wordlength pattern} $(A_1, ..., A_k)$ of an arbitrary fractional factorial design (or orthogonal array) on $k$ factors. They gave a coding-theoretic proof of the property that the design has strength $t$ if and only if $A_1 = ... = A_t = 0$. The quantities $A_i$ are defined in terms of characters of cyclic groups, and so one might seek a direct character-theoretic proof of this result. We give such a proof, in which the specific group structure (such as cyclicity) plays essentially no role. Nonabelian groups can be used if the counting function of the design satisfies one assumption, as illustrated by a couple of examples

Spatiomechanical Modulation of EphB4-Ephrin-B2 Signaling in Neural Stem Cell Differentiation.

Interactions between EphB4 receptor tyrosine kinases and their membrane-bound ephrin-B2 ligands on apposed cells play a regulatory role in neural stem cell differentiation. With both receptor and ligand constrained to move within the membranes of their respective cells, this signaling system inevitably experiences spatial confinement and mechanical forces in conjunction with receptor-ligand binding. In this study, we reconstitute the EphB4-ephrin-B2 juxtacrine signaling geometry using a supported-lipid-bilayer system presenting laterally mobile and monomeric ephrin-B2 ligands to live neural stem cells. This experimental platform successfully reconstitutes EphB4-ephrin-B2 binding, lateral clustering, downstream signaling activation, and neuronal differentiation, all in a configuration that preserves the spatiomechanical aspects of the natural juxtacrine signaling geometry. Additionally, the supported bilayer system allows control of lateral movement and clustering of the receptor-ligand complexes through patterns of physical barriers to lateral diffusion fabricated onto the underlying substrate. The results from this study reveal a distinct spatiomechanical effect on the ability of EphB4-ephrin-B2 signaling to induce neuronal differentiation. These observations parallel similar studies of the EphA2-ephrin-A1 system in a very different biological context, suggesting that such spatiomechanical regulation may be a common feature of Eph-ephrin signaling

Charter School Funding: Inequity Expands

The revenue study is based on Fiscal Year 2010‒11 (FY11) data for each of 30 selected states plus the District of Columbia (D.C.). Traditional school districts and public charter schools were analyzed and aggregated “statewide.” For each state, one to three “focus areas” were selected based on larger concentrations of charter students – most focus areas are large cities, some are metropolitan counties. Traditional school districts and charter schools were analyzed separately in each focus area. The analytic team collected and analyzed all revenues, public and private, flowing to traditional district and public charter schools. FY11 funding includes Federal, State, Local, Other, PublicIndeterminate, and Indeterminate sources

The Productivity of Public Charter Schools

This is the first national study of the productivity of public charter schools relative to district schools. This report is a follow up to the charter school revenue study, Charter School Funding: Inequity Expands, released in April 2014 by the School Choice Demonstration Project at the University of Arkansas. That study was authored by the same research team that crafted this report. In the revenue study, per pupil revenues for public charter schools and traditional public schools (TPS) were compared. The research team found that during the 2010-11 school year (FY11), charter-school students across 30 states and the District of Columbia on average received $3,814 less in funding than TPS students, a funding gap of 28.4 percent