Are older drivers’ driving patterns during an on-road driving task representative of their real-world driving patterns?

Abstract

Objective: The current study investigated whether older drivers’ driving patterns during a customized on-road driving task were representative of their real-world driving patterns.

Methods: Two hundred and eight participants (male: 68.80%; mean age?=?81.52 years, SD?=?3.37 years, range?=?76.00–96.00 years) completed a customized on-road driving task that commenced from their home and was conducted in their own vehicle. Participants’ real-world driving patterns for the preceding 4-month period were also collected via an in-car recording device (ICRD) that was installed in each participant’s vehicle.

Results: During the 4-month period prior to completing the on-road driving task, participants’ median real-world driving trip distance was 2.66?km (interquartile range [IQR]?=?1.14–5.79?km) and their median on-road driving task trip distance was 4.41?km (IQR?=?2.83–6.35?km). Most participants’ on-road driving task trip distances were classified as representative of their real-world driving trip distances (95.2%, n?=?198).

Conclusions: These findings suggest that most older drivers were able to devise a driving route that was representative of their real-world driving trip distance. Future research will examine whether additional aspects of the on-road driving task (e.g., average speed, proportion of trips in different speed zones) are representative of participants’ real-world driving patterns.     

COVID-19 effects on municipality waste collection services for households: statistical modelling of perspectives from Guyana and Nigeria

Journal of Material Cycles and Waste Management - The novel COVID-19 pandemic has disrupted the functioning of solid waste management globally as households experience an increase in their waste...     

Surface modification of polypropylene non-woven fibers with TiO2 nanoparticles via layer-by-layer self assembly method: Preparation and photocatalytic activity

Polypropylene (PP) meltblown fibers were coated with titanium dioxide (TiO₂) nanoparticles using layer-by-layer (LbL) deposition technique. The fibers were first modified with 3 layers of poly(4-styrenesulfonic acid) (PSS) and poly(diallyl-dimethylammonium chloride) (PDADMAC) to improve the anchoring of the TiO₂ nanoparticle clusters. PDADMAC, which is positively charged, was then used as counter polyelectrolyte in tandem with anionic TiO₂ nanoparticles to construct TiO₂/PDADMAC bilayer in the LbL fashion. The number of deposited TiO₂/PDADMAC layers was varied from 1 to 7 bilayer, and could be used to adjust TiO₂ loading. The LbL technique showed higher TiO₂ loading efficiency than the impregnation approach. The modified fibers were tested for their photocatalytic activity against a model dye, Methylene Blue (MB). Results showed that the TiO₂ modified fibers exhibited excellent photocatalytic activity efficiency similar to that of TiO₂ powder dispersed in solution. The deposition of TiO₂ 3 bilayer on the PP substrate was sufficient to produce nanocomposite fibers that could bleach the MB solution in less than 4 hr. TiO₂-LbL constructions also preserved TiO₂ adhesion on substrate surface after 1 cycle of photocatalytic test. Successive photocatalytic test showed decline in MB reduction rate with loss of TiO₂ particles from the substrate outer surface. However, even in the third cycle, the TiO₂ modified fibers are still moderately effective as it could remove more than 95% of MB after 8 hr of treatment.     

Development and implementation of eco-genomic tools for aquatic ecosystem biomonitoring: the SYNAQUA French-Swiss program

The effectiveness of environmental protection measures is based on the early identification and diagnosis of anthropogenic pressures. Similarly, restoration actions require precise monitoring of changes in the ecological quality of ecosystems, in order to highlight their effectiveness. Monitoring the ecological quality relies on bioindicators, which are organisms revealing the pressures exerted on the environment through the composition of their communities. Their implementation, based on the morphological identification of species, is expensive because it requires time and experts in taxonomy. Recent genomic tools should provide access to reliable and high-throughput environmental monitoring by directly inferring the composition of bioindicators’ communities from their DNA (metabarcoding). The French-Swiss program SYNAQUA (INTERREG France-Switzerland 2017–2019) proposes to use and validate the tools of environmental genomic for biomonitoring and aims ultimately at their implementation in the regulatory bio-surveillance. SYNAQUA will test the metabarcoding approach focusing on two bioindicators, diatoms, and aquatic oligochaetes, which are used in freshwater biomonitoring in France and Switzerland. To go towards the renewal of current biomonitoring practices, SYNAQUA will (1) bring together different actors: scientists, environmental managers, consulting firms, and biotechnological companies, (2) apply this approach on a large scale to demonstrate its relevance, (3) propose robust and reliable tools, and (4) raise public awareness and train the various actors likely to use these new tools. Biomonitoring approaches based on such environmental genomic tools should address the European need for reliable, higher-throughput monitoring to improve the protection of aquatic environments under multiple pressures, guide their restoration, and follow their evolution.     

When experts disagree: the need to rethink indicator selection for assessing sustainability of agriculture

Sustainability indicators are well recognized for their potential to assess and monitor sustainable development of agricultural systems. A large number of indicators are proposed in various sustainability assessment frameworks, which raises concerns regarding the validity of approaches, usefulness and trust in such frameworks. Selecting indicators requires transparent and well-defined procedures to ensure the relevance and validity of sustainability assessments. The objective of this study, therefore, was to determine whether experts agree on which criteria are most important in the selection of indicators and indicator sets for robust sustainability assessments. Two groups of experts (Temperate Agriculture Research Network and New Zealand Sustainability Dashboard) were asked to rank the relative importance of eleven criteria for selecting individual indicators and of nine criteria for balancing a collective set of indicators. Both ranking surveys reveal a startling lack of consensus amongst experts about how best to measure agricultural sustainability and call for a radical rethink about how complementary approaches to sustainability assessments are used alongside each other to ensure a plurality of views and maximum collaboration and trust amongst stakeholders. To improve the transparency, relevance and robustness of sustainable assessments, the context of the sustainability assessment, including prioritizations of selection criteria for indicator selection, must be accounted for. A collaborative design process will enhance the acceptance of diverse values and prioritizations embedded in sustainability assessments. The process by which indicators and sustainability frameworks are established may be a much more important determinant of their success than the final shape of the assessment tools. Such an emphasis on process would make assessments more transparent, transformative and enduring.     

A phenomenological approach shows a high coherence of warming patterns in dimictic aquatic systems across latitude

To predict the coherence in local responses to large-scale climatic forcing among aquatic systems, we developed a generalized approach to compare long-term data of dimictic water bodies based on phenomenologically defined hydrographic events. These climate-sensitive phases (inverse stratification, spring overturn, early thermal stratification, summer stagnation) were classified in a dual code (cold/warm) based on threshold temperatures. Accounting for a latitudinal gradient in seasonal timing of phases derived from gradients in cumulative irradiation (2.2?days per degree latitude), we found a high spatial and temporal coherence in warm–cold patterns for six lakes (84?%) and the Baltic Sea (78?%), even when using the same thresholds for all sites. Similarity to CW-codes for the North Sea still was up to 72?%. The approach allows prediction of phase-specific warming trends and resulting instantaneous or time-delayed ecological responses. Exemplarily, we show that warming during early thermal stratification controls food-web-mediated effects on key species during summer.     

Modelling the fate of hydrophobic organic contaminants in a boreal forest catchment: A cross disciplinary approach to assessing diffuse pollution to surface waters

The fate of hydrophobic organic compounds (HOCs) in soils and waters in a northern boreal catchment was explored through the development of a chemical fate model in a well-characterised catchment system dominated by two land types: forest and mire. Input was based solely on atmospheric deposition, dominated by accumulation in the winter snowpack. Release from soils was governed by the HOC concentration in soil, the soil organic carbon fraction and soil-water DOC content. The modelled export of selected HOCs in surface waters ranged between 11 and 250 ng day⁻¹ during the snow covered period, compared to 200 and 9600 ng/d during snow-melt; highlighting the importance of the snow pack as a source of these chemicals. The predicted levels of HOCs in surface water were in reasonable agreement to a limited set of measured values, although the model tended to over predict concentrations of HOCs for the forested sub-catchment, by over an order of magnitude in the case of hexachlorobenzene and PCB 180. This possibly reflects both the heterogeneity of the forest soils and the complicated and changing hydrology experienced between the different seasons.     

Analysis of phytochelatin complexes in the lead tolerant vetiver grass [Vetiveria zizanioides (L.)] using liquid chromatography and mass spectrometry

Ethylenediamene tetraacetic acid (EDTA) has been used to mobilize soil lead (Pb) and enhance plant uptake for phytoremediation. Chelant bound Pb is considered less toxic compared to free Pb ions and hence might induce less stress on plants. Characterization of possible Pb complexes with phytochelatins (PC_n, metal-binding peptides) and EDTA in plant tissues will enhance our understanding of Pb tolerance mechanisms. In a previous study, we showed that vetiver grass (Vetiveria zizanioides L.) can accumulate up to 19,800 and 3350 mg Pb kg⁻¹ dry weight in root and shoot tissues, respectively; in a hydroponics set-up. Following the basic incubation study, a greenhouse experiment was conducted to elucidate the efficiency of vetiver grass (with or without EDTA) in remediating Pb-contaminated soils from actual residential sites where Pb-based paints were used. The levels of total thiols, PC_n, and catalase (an antioxidant enzyme) were measured in vetiver root and shoot following chelant-assisted phytostabilization. In the presence of 15 mM kg ⁻¹ EDTA, vetiver accumulated 4460 and 480 mg Pb kg⁻¹ dry root and shoot tissue, respectively; that are 15- and 24-fold higher compared to those in untreated controls. Despite higher Pb concentrations in the plant tissues, the amount of total thiols and catalase activity in EDTA treated vetiver tissues was comparable to chelant unamended controls, indicating lowered Pb toxicity by chelation with EDTA. The identification of glutathione (referred as PC₁) (m/z 308.2), along with chelated complexes like Pb-EDTA (m/z 498.8) and PC₁-Pb-EDTA (m/z 805.3) in vetiver root tissue using electrospray tandem mass spectrometry (ES-MS) highlights the possible role of such species towards Pb tolerance in vetiver grass.     

The effects of low frequency noise on mental performance and annoyance

Low frequency noise (LFN) as background noise in urban and work environments is emitted from many artificial sources such as road vehicles, aircraft, and air movement machinery including wind turbines, compressors, and ventilation or air conditioning units. In addition to objective effects, LFN could also cause noise annoyance and influence mental performance; however, there are no homogenous findings regarding this issue. The purpose of this research was to study the effects of LFN on mental performance and annoyance, as well as to consider the role of extraversion and neuroticism on the issue. This study was conducted on 90 students of Iran University of Medical Sciences (54 males and 36 females). The mean age of the students was 23.46 years (SD?=?1.97). Personality traits and noise annoyance were measured by using Eysenck Personality Inventory and a 12-scale self-reported questionnaire, respectively. Stroop and Cognitrone computerized tests measured mental performance of participants each exposed to 50 and 70 dBA of LFN and silence. LFNs were produced by Cool Edit Pro 2.1 software. There was no significant difference between mental performance parameters under 50 and 70 dBA of LFN, whereas there were significant differences between most mental performance parameters in quiet and under LFN (50 and 70 dBA). This research showed that LFN, compared to silence, increased the accuracy and the test performance speed (p?<?0.01). There was no association between LFN and noise annoyance (p?>?0.01). Introverts conducted the tests faster than extraverts (p?<?0.05). This research showed that neuroticism does not influence mental performance. It seems that LFN has increased arousal level of participants, and extraversion has a considerable impact on mental performance.     

A multi-agent simulation model for spatial optimisation of manure allocation

The EU Nitrate Directive has spurred many countries to regulate manure production and manure application. Farmers have three allocation options: spreading manure on their own land, transporting manure to other farmers' land or processing manure. The manure problem can be seen as an allocation problem. To better understand this allocation problem, we have developed the spatial mathematical programming multi-agent simulation (MP-MAS) model. This model has been applied in Flanders, Belgium, a region with a high concentration of livestock. The model evaluates the cost efficiency of policy intervention in the manure market through obliged processing. We propose to further optimise the policy using a regionally differentiated manure pressure indicator, which is directly derived from the dual outcome of the mathematical programme. This indicator increases transparency in the manure and processing market, leading to better decision support about location and type of manure processing.