Future research directions in injury biomechanics and passive safety research

There has been an increasing trend within the safety environment for funding to be directed towards applied research or towards research developing commercially-exploitable systems. Funding mechanisms such as the EU’s 6th Framework Programme and many national programmes focus on research of likely immediate social benefit, reflecting the use of public finances. These programmes will continue to play an important role in funding safety research, but they typically do not have guidelines specifically directed towards fundamental research questions. Additionally, impartial advice is not always available to help programme managers identify research priorities. This review of biomechanics and passive safety research is intended for use by researchers who may be contemplating research in certain areas and wish independent guidance on specific research questions. It is also intended for use by research funding groups and programme managers who would like impartial guidance on basic research to be supported. It covers engineering research directed at improving vehicles and safety systems for all types of road user. It includes the main research and development tools such as dummy development and humanoid modelling and the important area of crash injury data

Multispecies QSAR Modeling for Predicting the Aquatic Toxicity of Diverse Organic Chemicals for Regulatory Toxicology

The research aims to develop multispecies quantitative structure–activity relationships (QSARs) modeling tools capable of predicting the acute toxicity of diverse chemicals in various Organization for Economic Co-operation and Development (OECD) recommended test species of different trophic levels for regulatory toxicology. Accordingly, the ensemble learning (EL) approach based classification and regression QSAR models, such as decision treeboost (DTB) and decision tree forest (DTF) implementing stochastic gradient boosting and bagging algorithms were developed using the algae (<i>P. subcapitata</i>) experimental toxicity data for chemicals. The EL-QSAR models were successfully applied to predict toxicities of wide groups of chemicals in other test species including algae (<i>S. obliguue</i>), daphnia, fish, and bacteria. Structural diversity of the selected chemicals and those of the end-point toxicity data of five different test species were tested using the Tanimoto similarity index and Kruskal–Wallis (K–W) statistics. Predictive and generalization abilities of the constructed QSAR models were compared using statistical parameters. The developed QSAR models (DTB and DTF) yielded a considerably high classification accuracy in complete data of model building (algae) species (97.82%, 99.01%) and ranged between 92.50%–94.26% and 92.14%–94.12% in four test species, respectively, whereas regression QSAR models (DTB and DTF) rendered high correlation (<i>R</i>²) between the measured and model predicted toxicity end-point values and low mean-squared error in model building (algae) species (0.918, 0.15; 0.905, 0.21) and ranged between 0.575 and 0.672, 0.18–0.51 and 0.605–0.689 and 0.20–0.45 in four different test species. The developed QSAR models exhibited good predictive and generalization abilities in different test species of varied trophic levels and can be used for predicting the toxicities of new chemicals for screening and prioritization of chemicals for regulation

QSTR Modeling for Qualitative and Quantitative Toxicity Predictions of Diverse Chemical Pesticides in Honey Bee for Regulatory Purposes

Pesticides are designed toxic chemicals for specific purposes and can harm nontarget species as well. The honey bee is considered a nontarget test species for toxicity evaluation of chemicals. Global QSTR (quantitative structure–toxicity relationship) models were established for qualitative and quantitative toxicity prediction of pesticides in honey bee (<i>Apis mellifera</i>) based on the experimental toxicity data of 237 structurally diverse pesticides. Structural diversity of the chemical pesticides and nonlinear dependence in the toxicity data were evaluated using the Tanimoto similarity index and Brock–Dechert–Scheinkman statistics. Probabilistic neural network (PNN) and generalized regression neural network (GRNN) QSTR models were constructed for classification (two and four categories) and function optimization problems using the toxicity end point in honey bees. The predictive power of the QSTR models was tested through rigorous validation performed using the internal and external procedures employing a wide series of statistical checks. In complete data, the PNN-QSTR model rendered a classification accuracy of 96.62% (two-category) and 95.57% (four-category), while the GRNN-QSTR model yielded a correlation (<i>R</i>²) of 0.841 between the measured and predicted toxicity values with a mean squared error (MSE) of 0.22. The results suggest the appropriateness of the developed QSTR models for reliably predicting qualitative and quantitative toxicities of pesticides in honey bee. Both the PNN and GRNN based QSTR models constructed here can be useful tools in predicting the qualitative and quantitative toxicities of the new chemical pesticides for regulatory purposes

Interface interactions between insecticide carbofuran and tea waste biochars produced at different pyrolysis temperatures

<p>Biochars showed a potential as adsorbents for organic contaminants, however, have not been tested for carbofuran, which has been detected frequently in water. This study provides evidences for the use of infused tea residue derived biochar for carbofuran removal. Biochars were produced at 300, 500 and 700 °C by slow pyrolysis and were characterized by proximate and ultimate analysis, FT-IR, SEM, BET and pore size distribution. Pyrolysis temperature showed a pronounced effect on biochar properties. The maximum carbofuran removal was achieved at pH 5. Freundlich and Temkin models best fit the equilibrium data. Biochars produced at 700 °C showed the highest sorption intensity. The adsorption process was likely to be a favorable chemisorption process with electrostatic interactions between carbofuran molecules and biochar surface. Acid-base interactions, electrophilic addition reactions and amide bond formations are the possible mechanisms of carbofuran adsorption. Overall, biochars prepared from tea waste can be utilized as effective adsorbents for removal of aqueous carbofuran.</p

Removal of antimonate and antimonite from water by schwertmannite granules

<p>In order to overcome the drawbacks of small particle-sized adsorbents, schwertmannite powder was fabricated into granules in the present study. These granules were evaluated for Sb(III) and Sb(V) removal from water and intraparticle mass transfer resistance of Sb(III) and Sb(V) onto the porous adsorbent was modeled. Schwertmannite granules (SG) exhibited capacities of 32.9 mg/g for Sb(III) and 23.2 mg/g for Sb(V), respectively, which are superior to many reported granular adsorbents and even powder adsorbents. Mass transfer was separately modeled using the pore volume diffusion model and surface diffusion model. The film diffusion coefficients, <i>k</i>_L, range from 1.09 × 10⁻⁵ to 3.08 × 10⁻⁵ cm/s. The pore diffusion coefficients, <i>D</i>_ep, range from 6.20 × 10⁻⁵ to 10.85 × 10⁻⁵ cm²/s, and the surface diffusion coefficients, <i>D</i>_s, range from 1.12 × 10⁻⁹ to 3.57 × 10⁻⁹ cm²/s. The concentration decay data-sets were successfully fitted with these best obtained parameters. Sb(III) was effectively removed over a wide pH range, while the removal of Sb(V) was pH dependent and could be enhanced by lowering solution pH. Sb(III)-loaded SG was regenerated with 91.2% re-adsorption capacity retained after five cycles when using 0.6% NaOH as the stripping solution. The desorption of Sb(V) was not as successful as Sb(III). Before breakthrough (5 μg/L) occurred, 1,690 and 712 bed volumes (BVs) of Sb(III), and 769 and 347 BVs of Sb(V) were treated when operating at space velocity values of 2 and 6 h⁻¹, respectively. Considering the low cost and the granular form of schwertmannite, the adsorbent is a promising modestly priced adsorbent and can be easily used in packed bed or filter units for practical application.</p

A systematic review and meta-analysis of the impact of curbs on crash outcomes

Road traffic crashes involving vertical curbs are commonly reported to occur on highways and expressways in India. We found a gap in terms of systematically assessing the evidence of the impact of curbs on road safety outcomes in the real world. We conducted a systematic review and meta-analysis of the impact of curbs on the risk of road traffic injuries. We used keywords in a database of records prepared by an earlier evidence gap map (EGM). The EGM used a comprehensive search strategy including 6 academic database, 17 organizational websites, hand searching, contacting experts and back referencing. We found 4 studies that evaluated impact of a curbed median or a curbed shoulder. We found that the presence of a curb on a median increases the risk for all crashes, all single-vehicle crashes, all median-related crashes and median-related injury crashes. The data also indicate that the severity of accidents reduces for curbs on median while it increases for curbs on shoulder, though the latter effect is not statistically significant. All the epidemiological studies were conducted on rural highways and did not report effects for different traffic speeds or vehicle types. However, our review of crash tests and simulation studies indicates that the impact of a curb design may be highly sensitive to speed and vehicle types. The safety impacts of a curb depend on the context of the road. In an urban road, a curb should ensure safety of pedestrians from an errant vehicle. On high-speed rural roads, curbs should be avoided and treatments should facilitate safe departure of the vehicle from the roadway.</p

Developing a national database of police-reported fatal road traffic crashes for road safety research and management in India

Strengthening crash surveillance is an urgent priority for road safety in low- and middle-income countries. We reviewed the online availability and completeness of First Information Reports (FIRs; police reports) of road traffic crashes in India. We developed a relational database to record information extracted from FIRs, and implemented it for one state (Chhattisgarh, 2017–2019). We found that FIRs can be downloaded in bulk from government websites of 15 states and union territories. Another 14 provide access online but restrict bulk downloading, and 7 do not provide online access. For Chhattisgarh, 87% of registered FIRs could be downloaded. Most FIRs reported the date, time, collision-type, and vehicle-types, but important crash characteristics (e.g. infrastructure attributes) were missing. India needs to invest in building the crash surveillance capacity for research and safety management. However, in the interim, maintaining a national database of a sample of FIRs can provide useful policy guidance.</p

Biochar Adsorbents with Enhanced Hydrophobicity for Oil Spill Removal

Oil spills cause massive loss of aquatic life. Oil spill cleanup can be very expensive, have secondary environmental impacts, or be difficult to implement. This study employed five different adsorbents: (1) commercially available byproduct Douglas fir biochar (BC) (SA ∼ 695 m2/g, pore volume ∼ 0.26 cm3/g, and pore diameter ∼ 13–19.5 Å); (2) BC modified with lauric acid (LBC); (3) iron oxide-modified biochar (MBC); (4) LBC modified with iron oxide (LMBC); and (5) MBC modified with lauric acid (MLBC) for oil recovery. Transmission, engine, machine, and crude oils were used to simulate oil spills and perform adsorption experiments. All five adsorbents adsorbed large quantities of each oil in fresh and simulated seawater with only a slight pH dependence, fast kinetics (sorptive equilibrium reached before 15 min), and high regression fits to the pseudo-second-order kinetic model. The Sips isotherm model oil sorption capacities for these sorbents were in the range ∼3–11 g oil/1 g adsorbent. Lauric acid-decorated (60–2 wt %) biochars gave higher oil adsorption capacities than the undecorated biochar. Lauric acid enhances biochar hydrophobicity and its water contact angle and reduces water influx into biochar’s porosity preventing it from sinking in water for 3 weeks. These features were observed even at 2% wt of lauric acid (sinks only after 2 weeks). Magnetization by magnetite nanoparticle deposition onto BC and LBC allows the recovery of the exhausted adsorbent by a magnetic field as an alternative to filtration. Oil sorption was endothermic. Recycling was demonstrated after toluene stripping. The oil-laden adsorbents’ heating values were obtained, suggesting an alternative use of these spent adsorbents as a low-cost fuel after recovery, avoiding waste disposal costs. The initial and oil-laden adsorbents were characterized by scanning electron microscopy, transmission electron microscopy, energy-dispersive X-ray spectroscopy, Fourier transform infrared spectroscopy, X-ray diffraction, Brunauer–Emmet–Teller surface area, contact angle, thermogravimetric analyses, differential scanning calorimetry, vibrating sample magnetometry, elemental analysis, and X-ray photoelectron spectroscopy