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Introduction: A substantial proportion of hospital admissions and readmissions are directly attributable to preventable medication-related harm. Interventions that reduce these harms could avert significant suffering and healthcare costs.Objectives: The Discharge Medications Reconciliation (DCMedsRec) trial will evaluate a structured medication reconciliation service by community pharmacists post hospital discharge on the risk of 30-day unplanned readmission. Electronic access to the Hospital Discharge Summary via My Health Record will underpin this service.Methods: DCMedsRec is a non-blinded randomised controlled trial of an intervention by community pharmacists within 30 days of hospital discharge in Melbourne, Australia. Patients discharged from hospital will be assessed by a hospital pharmacist for trial eligibility. If eligible, patients will be randomised to either a control or intervention group by sequentially marked sealed envelopes. Intervention patients receive an invitation to the DCMedsRec service at a participating community pharmacy, who will be reimbursed. Control patients will receive usual care. A Number Needed to Treat of 20 will require 293 DCMedsRec interventions to achieve 80% power. With a predicted 30% uptake, a minimum sample of 977 in the intervention arm is required.Outcomes: The primary outcome will be the rate of 30-day unplanned hospital readmission in intervention (DCMedsRec) versus usual care groups. Secondary analyses will evaluate the economic impact of the intervention and a qualitative thematic analysis of the experience and value of the service for both patients and service providers (community pharmacists).Analysis: An intention-to-treat analysis will be used to assess intervention efficacy and results will be reported using risk ratios with 95% confidence intervals. Cost-effectiveness analysis will compare within-trial costs and outcomes of the DCMedsRec versus usual care from a health-system perspective.Trial Registration and Funding: This trial is registered with the Australian and New Zealand Clinical Trials Register and funded by the Australian Digital Health Agency. [ABSTRACT FROM AUTHOR]

Abstract: Inclined settlers may be used to improve algal-harvesting economics by enhancing the clarification rate for a fixed sedimentation velocity and areal footprint. For a fixed plate area, smaller inclination angles from horizontal result in increased settling area and clarification rate. To ensure flow of the settled-cell sediment for continuous operation, standard designs utilize a minimum angle of 55° from horizontal. If reliable, shallow-angle flow of sedimented algae is achieved, increased clarification rates may be realized (e.g., 63% enhancement at 20° versus 55° from horizontal). To study the critical sediment-flow angle, we use an angle-of-repose model, which includes an additional normal-force term to account for adhesion. The inclusion of this term is supported by observations that the critical sliding angle decreases with the sediment mass/thickness. To reduce the critical sliding angle, we evaluated the sediment flow of settled, green alga Chlorella vulgaris on several low-adhesion surfaces described in the biofouling literature and demonstrated sediment flow at angles as low as 10° using a negatively-charged surface. This surface fouled after immersion for 24h in spent culture medium, presumably due to the deposition of residual organic matter. Additionally, applied vibration is demonstrated to achieve sediment flow at angles as shallow as 20°. [Copyright &y& Elsevier]

Abstract: A promising renewable energy scenario involves growing photosynthetic microalgae as a biofuel feedstock that can be converted into fungible, energy-dense fuels. Microalgae transform the energy in sunlight into a variety of reduced-carbon storage products, including triacylglycerols, which can be readily transformed into diesel fuel surrogates. To develop an economically viable algal biofuel industry, it is important to maximize the production and accumulation of these targeted bioenergy carriers in selected strains. In an effort to identify promising feedstock isolates we developed, evaluated and optimized contemporary high-throughput cell-sorting techniques to establish a collection of microalgae isolated from highly diverse ecosystems near geographic areas that are potential sites for large-scale algal cultivation in the Southwest United States. These efforts resulted in a culture collection containing 360 distinct microalgal strains. We report on the establishment of this collection and some preliminary qualitative screening studies to identify important biofuel phenotypes including neutral lipid accumulation and growth rates. As part of this undertaking we determined suitable cultivation media and evaluated cryopreservation techniques critical for the long-term storage of the microorganisms in this collection. This technique allows for the rapid isolation of extensive strain biodiversity that can be leveraged for the selection of promising bioenergy feedstock strains, as well as for providing fundamental advances in our understanding of fundamental algal biology. [Copyright &y& Elsevier]

Microbial based biofuels represent a potential promising solution as an environmentally favorable transportation fuel. Cyanobacteria have many of the same advantages as microalgae: ability for rapid growth in otherwise non-arable regions, suitability for genetic engineering, and simple nutritional needs. Additionally, cyanobacteria can be engineered to secrete valuable co-products that can be harvested independent from the produced biomass. However, little work has been done to identify the processes and the economic and environmental impacts associated with a large-scale cyanobacteria-to-fuels facility. The present study is a concurrent techno-economic and life cycle assessment of a facility that generates fuels and methyl laurate, an oleochemical, from the cyanobacterial species Synechocystis sp. PCC 6803. The biorefinery model includes all aspects of cultivation, separation of the secreted methyl laurate, biomass harvesting and fuel processing via hydrothermal liquefaction (HTL) of the dewatered biomass. The assessments leverage Monte Carlo analysis (MCA) to address uncertainty and variability inherent in the most significant input parameters, replacing them with probabilistic functions. For the facility configuration producing both fuels and the oleochemical co-product, the MCA average minimum fuel selling price (MFSP) is $2.47 per decimeter (dm3) or $9.34 per gallon of gasoline equivalent (gge) with the corresponding average global warming potential determined to be 118 g CO 2 -eq-MJ−1. The case producing only fuels results in an MCA average MFSP of $2.01-(dm3)−1 ($7.60-gge−1) and an average environmental impact of 100 g CO 2 -eq-MJ−1. These results are compared to static optimistic and conservative scenario analysis estimates, illustrating the over- and under-estimation of outcomes associated with non-stochastic methods. Suggested facility improvements include increases in pond productivity of both the biomass and methyl laurate oil production, as well as improvements to carbon utilization and bio-crude yield from HTL processing. • Techno-economic and life cycle assessment of a cyanobacteria-based biorefinery • Products include secreted methyl laurate and fuels via hydrothermal liquefaction. • Monte Carlo analysis with detailed input distribution information using @RISK • Monte Carlo analysis avoids the compounding effect of static scenario analysis. [ABSTRACT FROM AUTHOR]

• Insights on real-world driving patterns, health and functional changes of older drivers. • Reduced annual distance was associated with being female, increasing age, and health drop-out status. • Reduced annual trip frequency was associated with age and health drop-out status. • Results suggest self-regulation and may reflect adaptation to health or functional changes. This paper describes changes in driving patterns over a five-year period of drivers aged 75 years and older (Year 1: Male = 68.9%; Age = M = 79.5 years, SD = 3.4 years, Range: 75.0–88.0 years) in the Candrive/Ozcandrive cohort study. Participants completed various functional and health assessments and self-reported driving questionnaires. In-vehicle data-loggers, installed in participants' own vehicles, also monitored spatio-temporal characteristics of participants' everyday driving trips. Data for a subset of one hundred and ninety-one Ozcandrive participants from Melbourne, Australia were analysed. Reductions in driving trip distance and frequency were observed over the five years. On average, in Year 1, participants drove 1223 (SD = 502) trips, totalling 8993 (SD = 5169) kilometers annually, decreasing significantly to 1028 trips (SD = 559) trips and 6787 (SD = 4624) kilometers in Year 5. On average, in Year 1, participants' driving trips were around 7.5 km (SD = 3.2), decreasing in distance significantly to 6.9 km (SD 3.9) in Year 5. Log-normal General Estimating Equation (GEE) modelling was conducted for selected driving exposure measures (annual distance driven, annual trip frequency, trip distance, etc.). Reductions in overall annual distance driven were significantly associated with being female, increasing age, withdrawal from the study for health reasons and lower night-time driving comfort scores (marginally significant). Reductions in annual trip frequency were associated with increasing age and withdrawal from the study for health reasons. Results suggest drivers practiced self-regulation, which may reflect adaption to deterioration in health and functional status. [ABSTRACT FROM AUTHOR]

The aim of the current study was to examine how self-reported aberrant driving behaviours change across a three time-points in a group of older drivers. Two hundred and twenty-seven older drivers (males = 69.6%) from the Candrive/Ozcandrive longitudinal study completed the Driving Behaviour Questionnaire (DBQ) each yearacross three time-points (i.e., Year 1, Year 2, Year 3). At the third time-point, older drivers ranged in age from 77 to 96 years (M = 81.74 years; SD = 3.44 years). A longitudinal confirmatory factor analysis showed that a modified 21-item, 3-factor (errors, lapses and violations) DBQ was invariant across the time period, suggesting that the structure of the questionnaire was stable across each time-point. Further, multiple domain latent growth analysis on the resultant factors for errors, lapses and violations showed that the frequency of errors remained similar across the three-year period, while violations and lapses showed very marginal decreases in frequency. These changes were independent of the absolute number of these behaviours; Drivers with higher violations or lapses in Year one, showed similar decreases in frequency as those who self-reported lower frequencies of the behaviours. These results suggest that the DBQ is a reliable tool to measure older drivers’ self-reported aberrant driving behaviours, and that these behaviours do not show much change across time. Future research should validate the self-reported responses from the DBQ with more objective measures such as those collected through naturalistic driving study (NDS) methodology or on-road driving tasks. [ABSTRACT FROM AUTHOR]

• 208 older drivers completed a naturalistic on-road driving task (eDOS) • Compared driving patterns during the eDOS and real-world driving (RWD) trips. • Sub-trips of home-to-first-destination during the eDOS resembled RWD trips that started from home. • Potential to use eDOS to assess at-risk older drivers for modified (local area) licences. This study compared older drivers' driving patterns during a naturalistic on-road driving task (i.e., eDOS driving task) with their real-world driving from the preceding four-month period. Two hundred and eight participants (Male: 68.8%; Mean age = 81.5 years, SD = 3.3 years) completed the eDOS driving task in their own vehicle which commenced from their home and followed a self-selected route. Participants' driving patterns were collected via an in-car recording device that was installed in their vehicle. This study examined the sub-trip from participants' homes to their first destination during the eDOS driving task. The median sub-trip distance was 4.4 km (Q1 = 2.8, Q3 = 6.4). Across the four-month period of real-world driving, participants completed a median of 151 driving trips from their home (Q1 = 103.0, Q3 = 202.7), with a median trip distance of 2.7 km (Q1 = 1.1, Q3 = 5.8). Most participants' eDOS driving task trip distance was classified as representative of their real-world driving trip distances (95.2%). By mapping GPS coordinates for driving pattern data with road types and roadways, most eDOS driving task trips included roadways that were actively used during their real-world driving (85.0%). During the preceding four-month period of real-world driving, most participants had visited the first nominated destination during the eDOS driving task at least once per month (77.4%). Given the increasing international interest and use of modified (local area) licences, these findings suggest that naturalistic on-road driving tasks could be used by licensing authorities to assess potentially at-risk older drivers within their own driving environments. [ABSTRACT FROM AUTHOR]