The Effect of Masterbatch Addition on the Mechanical, Thermal, Optical and Surface Properties of Poly(lactic acid)

There has been considerable interest in the use of the biodegradable polymer poly(lactic acid) (PLA) as a replacement for petroleum derived polymers due to ease of processability and its high mechanical strength. Other material properties have however limited its wider application. These include its brittle properties, low impact strength and yellow tint. In an attempt to overcome these drawbacks, PLA was blended with four commercially available additives, commonly known as masterbatches. The effect of the addition of 1.5 wt% of the four masterbatches on the mechanical, thermal, optical and surface properties of the polymer was evaluated. All four masterbatches had a slight negative effect on the tensile strength of PLA (3–5% reduction). There was a four fold increase in impact resistance however with the addition of one of the masterbatches. Differential scanning calorimetry demonstrated that this increase corresponded to a decrease in the polymer crystallinity. However there was an associated increase in polymer haze with the addition of this masterbatch. The clarity of PLA was improved through the addition of an optical brightener masterbatch, but the impact resistance remained low. The glass transition and melting temperatures of PLA were not affected by the addition of the masterbatches, and no change was observed in surface energy. Some delay in PLA degradation, in a PBS degradation medium at 50 °C, was observed due to blending with these masterbatches.     

Seat Belt Use in States and Territories with Primary and Secondary Laws -- United States, 2006

Problem

Motor-vehicle crashes are a leading cause of death in the United States. In the event of a crash, seat belts are highly effective in preventing serious injury and death.

Methods

Data from the 2006 Behavioral Risk Factor Surveillance System were used to calculate prevalence of seat belt use by state and territory and by type of state seat belt law (primary vs. secondary enforcement).

Results

In 2006, seat belt use among adults ranged from 58.3% to 91.9% in the states and territories. Seat belt use was 86.0% in states and territories with primary enforcement laws and 75.9% in states with secondary enforcement laws.

Discussion

Seat belt use continues to increase in the United States. Primary enforcement laws remain a more effective strategy than secondary enforcement laws in getting motor-vehicle occupants to wear their seat belts.     

A note on the effectiveness of the house-arrest alternative for motivating DWI offenders to install ignition interlocks

Introduction

The effectiveness of ignition interlocks at reducing drunk driving has been limited by the ability of driving-while-intoxicated (DWI) offenders to avoid court orders to install the devices.

Methods

In a pilot program in New Mexico, four Santa Fe County judges imposed home confinement (via electronic monitoring bracelets) on offenders who claimed to have no car or no intention to drive. Interlock installation rates for Santa Fe County were compared with all other counties in New Mexico over a 2-year program and 2-year post-program period.

Results

During the two program years, 70% of the drivers convicted of DWI in Santa Fe County installed interlocks, compared to only 17% in the other counties, but when the program was terminated, the Santa Fe installation rate fell by 18.8 percentage points.

Summary

Mandating the alternative sanction of house arrest led to the highest reported interlock installation rate for DWI offenders.

Impact on Industry

Impaired driving is a substantial expense to employers, particularly when it bars driving that interferes with employment. Interlocks provide a method of protecting the public while permitting the offender to drive sober. This study was directed at increasing interlock use by DWI offenders.     

Effects of time-gap settings of adaptive cruise control (ACC) on driving performance and subjective acceptance in a bus driving simulator

A study was conducted to investigate the effects of time-gap settings and contents of secondary tasks on a fix-based bus driving simulator on drivers’ performance while reclaiming control from ACC in a car-following scenario of emergency brake by the lead vehicle. Thirty professional bus drivers drove on the simulator with the scenario of highway traffic flow under 12 random time-gap settings: from 0.64 s to 2.40 s with the interval of 0.16 s. As for the effects of secondary tasks, subjects were evenly divided into three conditions: no secondary task interference, simple secondary task, and complex task. The results demonstrated that different safety demarcations of time-gaps on subjective acceptance and driving performance can be found out. The integrated demarcations separated time-gaps into divisions that represented different levels of danger. It revealed that the safer time-gaps for different situations were: longer than 1.60 s for none-secondary task distraction and longer than 2.08 s for being continuously distracted by secondary tasks. The demand for simple tasks is relatively high, so a larger time-gap is needed for the driver to remain safe. This research has implications for the time-gap selection of ACC and effects of secondary task distraction on buses. A next logical step will focus on determining time-gaps for lead vehicles on curves or slopes, when multiple vehicles are present ahead, and modeling driver behavior and performance with ACC for cars, buses, and other types of vehicles.     

Handling data uncertainties in event tree analysis

Event tree analysis (ETA) is an established risk analysis technique to assess likelihood (in a probabilistic context) of an accident. The objective data available to estimate the likelihood is often missing (or sparse), and even if available, is subject to incompleteness (partial ignorance) and imprecision (vagueness). Without addressing incompleteness and imprecision in the available data, ETA and subsequent risk analysis give a false impression of precision and correctness that undermines the overall credibility of the process. This paper explores two approaches to address data uncertainties, namely, fuzzy sets and evidence theory, and compares the results with Monte Carlo simulations. A fuzzy-based approach is used for handling imprecision and subjectivity, whereas evidence theory is used for handling inconsistent, incomplete and conflicting data. Application of these approaches in ETA is demonstrated using the example of an LPG release near a processing facility.     

Perceptions matter: household adaptive capacity and capability in two Australian coastal communities

Regional Environmental Change - This paper presents empirical data on household perceptions of capability to adapt to climate hazards and associated capacity needs. Households play an important...     

Fourth-corner correlation is a score test statistic in a log-linear trait–environment model that is useful in permutation testing

Ecologists wish to understand the role of traits of species in determining where each species occurs in the environment. For this, they wish to detect associations between species traits and environmental variables from three data tables, species count data from sites with associated environmental data and species trait data from data bases. These three tables leave a missing part, the fourth-corner. The fourth-corner correlations between quantitative traits and environmental variables, heuristically proposed 20 years ago, fill this corner. Generalized linear (mixed) models have been proposed more recently as a model-based alternative. This paper shows that the squared fourth-corner correlation times the total count is precisely the score test statistic for testing the linear-by-linear interaction in a Poisson log-linear model that also contains species and sites as main effects. For multiple traits and environmental variables, the score test statistic is proportional to the total inertia of a doubly constrained correspondence analysis. When the count data are over-dispersed compared to the Poisson or when there are other deviations from the model such as unobserved traits or environmental variables that interact with the observed ones, the score test statistic does not have the usual chi-square distribution. For these types of deviations, row- and column-based permutation methods (and their sequential combination) are proposed to control the type I error without undue loss of power (unless no deviation is present), as illustrated in a small simulation study. The issues for valid statistical testing are illustrated using the well-known Dutch Dune Meadow data set.     

Microbial mediated arsenic biotransformation in wetlands

Arsenic (As) is a pervasive environmental toxin and carcinogenic metalloid. It ranks at the top of the US priority List of Hazardous Substances and causes worldwide human health problems. Wetlands, including natural and artificial ecosystems (i.e. paddy soils) are highly susceptible to As enrichment; acting not only as repositories for water but a host of other elemental/chemical moieties. While macroscale processes (physical and geological) supply As to wetlands, it is the micro-scale biogeochemistry that regulates the fluxes of As and other trace elements from the semi-terrestrial to neighboring plant/aquatic/atmospheric compartments. Among these fine-scale events, microbial mediated As biotransformations contribute most to the element’s changing forms, acting as the ‘switch’ in defining a wetland as either a source or sink of As. Much of our understanding of these important microbial catalyzed reactions follows relatively recent scientific discoveries. Here we document some of these key advances, with focuses on the implications that wetlands and their microbial mediated transformation pathways have on the global As cycle, the chemistries of microbial mediated As oxidation, reduction and methylation, and future research priorities areas.

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Green Toxicology: a strategy for sustainable chemical and material development

Green Toxicology refers to the application of predictive toxicology in the sustainable development and production of new less harmful materials and chemicals, subsequently reducing waste and exposure. Built upon the foundation of “Green Chemistry” and “Green Engineering”, “Green Toxicology” aims to shape future manufacturing processes and safe synthesis of chemicals in terms of environmental and human health impacts. Being an integral part of Green Chemistry, the principles of Green Toxicology amplify the role of health-related aspects for the benefit of consumers and the environment, in addition to being economical for manufacturing companies. Due to the costly development and preparation of new materials and chemicals for market entry, it is no longer practical to ignore the safety and environmental status of new products during product development stages. However, this is only possible if toxicologists and chemists work together early on in the development of materials and chemicals to utilize safe design strategies and innovative in vitro and in silico tools. This paper discusses some of the most relevant aspects, advances and limitations of the emergence of Green Toxicology from the perspective of different industry and research groups. The integration of new testing methods and strategies in product development, testing and regulation stages are presented with examples of the application of in silico, omics and in vitro methods. Other tools for Green Toxicology, including the reduction of animal testing, alternative test methods, and read-across approaches are also discussed.