A Glass Polyalkenoate Cement Carrier for Bone Morphogenetic Proteins

This work considers a glass polyalkenoate cement (GPC)-based carrier for the effective delivery of bone morphogenetic proteins (BMPs) at an implantation site. A 0.12 CaO–0.04 SrO–0.36 ZnO–0.48 SiO2 based glass and poly(acrylic acid) (PAA, Mw 213,000) were employed for the fabrication of the GPC. The media used for the water source in the GPC reaction was altered to produce a series of GPCs. The GPC liquid media was either 100 % distilled water with additions of albumin at 0, 2, 5 and 8 wt% of the glass content, 100 % formulation buffer (IFB), and 100 % BMP (150 µg rhBMP-2/ml IFB). Rheological properties, compressive strength, ion release profiles and BMP release were evaluated. Working times (Tw) of the formulated GPCs significantly increased with the addition of 2 % albumin and remained constant with further increases in albumin content or IFB solutions. Setting time (Ts) experienced an increase with 2 and 5 % albumin content, but a decrease with 8 % albumin. Changing the liquid source to IFB containing 5 % albumin had no significant effect on Ts compared to the 8 % albumin-containing BT101. Replacing the albumin with IFB/BMP-2 did not significantly affect Tw. However, Ts increased for the BT101_BMP-2 containing GPCs, compared to all other samples. The compressive strength evaluated 1 day post cement mixing was not affected significantly by the incorporation of BMPs, but the ion release did increase from the cements, particularly for Zn and Sr. The GPCs released BMP after the first day, which decreased in content during the following 6 days. This study has proven that BMPs can be immobilized into GPCs and may result in novel materials for clinical applications

Determinants of wage and employment disparities for TVET and High School graduates

Technical Vocational Education and Training (TVET) was institutionalized by the Philippine government in order to fill in the gaps left by the higher education system in transitioning students to the formal workforce. However, recent studies suggest that TVET graduates have a difficult time gaining employment and wage increases because of skills supply and demand mismatches and the devaluation of TVET degrees. The mismatch is observed through the high unemployment rates of TVET graduates and various job availabilities that could not be filled up by these graduates due to the incompatibility of skills formation with job requirements which is evident in several sectors including ICT, Health Services, Agriculture, and Tourism. This paper used Naive Bayesian Regression and Propensity Score Matching methods to measure the direction and magnitude of labor market outcome differentials between TVET and High School graduates, as well as the Blinder Oaxaca Decomposition to measure how much endogenous and exogenous sources explain said wage and employment differentials

Non-Traditional Methods to Obtain Annual Average Daily Traffic (AADT)

693JJ319C000015The use of passive data from location-based smartphone applications (LBS) and Global Positioning Services (GPS) to collect Annual Average Daily Traffic (AADT) has the potential to greatly reduce costs to State Department of Transportations (DOTs) and Metropolitan Planning Organizations (MPOs) and expand the coverage of up-to-date counts. This report evaluates the technical and statistical validity of traffic data derived from these sources using machine learning methods. Validity was determined by comparison to 4255 permanent counters, and a survey of recent publications about accuracy expectations. The document covers the input data and the development of the machine learning models and model validation. The results include the error by road volume, roadway and regional characteristics compared to typical estimation. The effects of reduced trip sample, ping rate, spatial accuracy and reference counters were also tested. The applicability of Probe Data was tested for other factors including, day of week, month of year, directional and ramp AADT, work zones ADT, K and D factors, peak hour truck data, special events or unusual weather and AADT by vehicle type

Guidelines for Obtaining AADT Estimates from Non-Traditional Sources

693JJ319C000015The use of passive data from location-based smartphone applications (LBS) and Global Positioning Services (GPS) to collect Annual Average Daily Traffic (AADT) has the potential to greatly reduce costs to State Department of Transportations (DOTs) and Metropolitan Planning Organizations (MPOs) and expand the coverage of up-to-date counts. This report evaluates the technical and statistical validity of traffic data derived from these sources using machine learning methods. Validity was determined by comparison to 4255 permanent counters, and a survey of recent publications about accuracy expectations. The document covers the input data and the development of the machine learning models and model validation. The results include the error by road volume, roadway and regional characteristics compared to typical estimation. The effects of reduced trip sample, ping rate, spatial accuracy and reference counters were also tested. The applicability of Probe Data was tested for other factors including, day of week, month of year, directional and ramp AADT, work zones ADT, K and D factors, peak hour truck data, special events or unusual weather and AADT by vehicle type

High-Dimensional Coexistence of Temperate Tree Species: Functional Traits, Demographic Rates, Life-History Stages, and Their Physical Context

Theoretical models indicate that trade-offs between growth and survival strategies of tree species can lead to coexistence across life history stages (ontogeny) and physical conditions experienced by individuals. There exist predicted physiological mechanisms regulating these trade-offs, such as an investment in leaf characters that may increase survival in stressful environments at the expense of investment in bole or root growth. Confirming these mechanisms, however, requires that potential environmental, ontogenetic, and trait influences are analyzed together. Here, we infer growth and mortality of tree species given size, site, and light characteristics from forest inventory data from Wisconsin to test hypotheses about growth-survival trade-offs given species functional trait values under different ontogenetic and environmental states. A series of regression analyses including traits and rates their interactions with environmental and ontogenetic stages supported the relationships between traits and vital rates expected from the expectations from tree physiology. A combined model including interactions between all variables indicated that relationships between demographic rates and functional traits supports growth-survival trade-offs and their differences across species in high-dimensional niche space. The combined model explained 65% of the variation in tree growth and supports a concept of community coexistence similar to Hutchinson's n-dimensional hypervolume and not a low-dimensional niche model or neutral model

Comparing tropical forest tree size distributions with the predictions of metabolic ecology and equilibrium models

Tropical forests vary substantially in the densities of trees of different sizes and thus in above-ground biomass and carbon stores. However, these tree size distributions show fundamental similarities suggestive of underlying general principles. The theory of metabolic ecology predicts that tree abundances will scale as the -2 power of diameter. Demographic equilibrium theory explains tree abundances in terms of the scaling of growth and mortality. We use demographic equilibrium theory to derive analytic predictions for tree size distributions corresponding to different growth and mortality functions. We test both sets of predictions using data from 14 large-scale tropical forest plots encompassing censuses of 473 ha and \u3e 2 million trees. The data are uniformly inconsistent with the predictions of metabolic ecology. In most forests, size distributions are much closer to the predictions of demographic equilibrium, and thus, intersite variation in size distributions is explained partly by intersite variation in growth and mortality. © 2006 Blackwell Publishing Ltd/CNRS

Evaluation of methods and marker systems in genomic selection of oil palm (Elaeis guineensis Jacq.)

Background Genomic selection (GS) uses genome-wide markers as an attempt to accelerate genetic gain in breeding programs of both animals and plants. This approach is particularly useful for perennial crops such as oil palm, which have long breeding cycles, and for which the optimal method for GS is still under debate. In this study, we evaluated the effect of different marker systems and modeling methods for implementing GS in an introgressed dura family derived from a Deli dura x Nigerian dura (Deli x Nigerian) with 112 individuals. This family is an important breeding source for developing new mother palms for superior oil yield and bunch characters. The traits of interest selected for this study were fruit-to-bunch (F/B), shell-to-fruit (S/F), kernel-to-fruit (K/F), mesocarp-to-fruit (M/F), oil per palm (O/P) and oil-to-dry mesocarp (O/DM). The marker systems evaluated were simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs). RR-BLUP, Bayesian A, B, Cπ, LASSO, Ridge Regression and two machine learning methods (SVM and Random Forest) were used to evaluate GS accuracy of the traits. Results The kinship coefficient between individuals in this family ranged from 0.35 to 0.62. S/F and O/DM had the highest genomic heritability, whereas F/B and O/P had the lowest. The accuracies using 135 SSRs were low, with accuracies of the traits around 0.20. The average accuracy of machine learning methods was 0.24, as compared to 0.20 achieved by other methods. The trait with the highest mean accuracy was F/B (0.28), while the lowest were both M/F and O/P (0.18). By using whole genomic SNPs, the accuracies for all traits, especially for O/DM (0.43), S/F (0.39) and M/F (0.30) were improved. The average accuracy of machine learning methods was 0.32, compared to 0.31 achieved by other methods. Conclusion Due to high genomic resolution, the use of whole-genome SNPs improved the efficiency of GS dramatically for oil palm and is recommended for dura breeding programs. Machine learning slightly outperformed other methods, but required parameters optimization for GS implementation

Travel Tales of a Worldwide Weed: Genomic Signatures of Plantago major L. Reveal Distinct Genotypic Groups With Links to Colonial Trade Routes

Retracing pathways of historical species introductions is fundamental to understanding the factors involved in the successful colonization and spread, centuries after a species’ establishment in an introduced range. Numerous plants have been introduced to regions outside their native ranges both intentionally and accidentally by European voyagers and early colonists making transoceanic journeys; however, records are scarce to document this. We use genotyping-by-sequencing and genotype-likelihood methods on the selfing, global weed, Plantago major, collected from 50 populations worldwide to investigate how patterns of genomic diversity are distributed among populations of this global weed. Although genomic differentiation among populations is found to be low, we identify six unique genotype groups showing very little sign of admixture and low degree of outcrossing among them. We show that genotype groups are latitudinally restricted, and that more than one successful genotype colonized and spread into the introduced ranges. With the exception of New Zealand, only one genotype group is present in the Southern Hemisphere. Three of the most prevalent genotypes present in the native Eurasian range gave rise to introduced populations in the Americas, Africa, Australia, and New Zealand, which could lend support to the hypothesis that P. major was unknowlingly dispersed by early European colonists. Dispersal of multiple successful genotypes is a likely reason for success. Genomic signatures and phylogeographic methods can provide new perspectives on the drivers behind the historic introductions and the successful colonization of introduced species, contributing to our understanding of the role of genomic variation for successful establishment of introduced taxa.info:eu-repo/semantics/publishedVersio

Travel Tales of a Worldwide Weed: Genomic Signatures of Plantago major L. Reveal Distinct Genotypic Groups With Links to Colonial Trade Routes

Retracing pathways of historical species introductions is fundamental to understanding the factors involved in the successful colonization and spread, centuries after a species’ establishment in an introduced range. Numerous plants have been introduced to regions outside their native ranges both intentionally and accidentally by European voyagers and early colonists making transoceanic journeys; however, records are scarce to document this. We use genotyping-by-sequencing and genotype-likelihood methods on the selfing, global weed, Plantago major, collected from 50 populations worldwide to investigate how patterns of genomic diversity are distributed among populations of this global weed. Although genomic differentiation among populations is found to be low, we identify six unique genotype groups showing very little sign of admixture and low degree of outcrossing among them. We show that genotype groups are latitudinally restricted, and that more than one successful genotype colonized and spread into the introduced ranges. With the exception of New Zealand, only one genotype group is present in the Southern Hemisphere. Three of the most prevalent genotypes present in the native Eurasian range gave rise to introduced populations in the Americas, Africa, Australia, and New Zealand, which could lend support to the hypothesis that P. major was unknowlingly dispersed by early European colonists. Dispersal of multiple successful genotypes is a likely reason for success. Genomic signatures and phylogeographic methods can provide new perspectives on the drivers behind the historic introductions and the successful colonization of introduced species, contributing to our understanding of the role of genomic variation for successful establishment of introduced taxa.publishedVersio