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This study aimed at evaluating the effects of different environmental conditions (irradiance, temperature, pH and dissolved oxygen) on a microalgae-bacteria consortium cultivated in a pilot-scale open pond and fed on the liquid fraction of anaerobic digestate. A standardized photo-respirometry protocol was followed to evaluate the activity of microalgae under different conditions. Two datasets (specific photosynthetic oxygen production rates and respiratory oxygen consumption rates) were obtained for each environmental parameter, throughout the entire range of conditions found in the outdoor cultivation system. Different kinetic models available in literature were fitted to experimental data and the resulting outputs were compared through model selection estimators, in order to select the most appropriate equations. The proposed set of equations constitute a modelling tool for the prediction of algal growth rates in algae-bacteria systems, as a function of environmental conditions. In this study, three pilot-scale solid-phase denitrification (SPD) systems filled with poly-3-hydroxybutyrate-co-hyroxyvelate (PHBV), PHBV-Rice hulls (PHBV-RH) and PHBV-Sawdust (PHBV-S) were operated to treat effluent of waste water treatment pangts (WWTPs). The fast start-up and intensified nitrogen removal performance were obtained in PHBV-RH and PHBV-S systems. Besides, the optimal total nitrogen (TN) removal efficiency was obtained in PHBV-S system (91.65 ± 4.12%) with less ammonia accumulation and dissolved organic carbon (DOC) release. The significant enrichment of amx 16S rRNA and nirS genes in PHBV-RH and PHBV-S systems indicated the possible coexistence of anammox and denitrification. Miseq sequencing analysis exhibited more complex community diversity, more abundant denitrifying and fermenting bacteria in PHBV-RH and PHBV-S systems. The co-existence of denitrification and anammox might contribute to better control of nitrogen and dissolved organic carbon in PHBV-S system. The outcomes provide an economical and eco-friendly alternative to improve nitrogen removal of WWTPs effluent. Neurotoxic amyloid-β peptide (Aβ) 42/43 species generated by β-secretase and γ-secretase from the β-amyloid precursor protein (APP) are believed to trigger Alzheimer's disease (AD). Relative increases of these species due to mutations in APP and presenilin/γ-secretase are associated with the vast majority of early onset familial AD cases. Important breakthroughs have recently been made in elucidating the mechanism(s) of these mutations, showing that altered substrate interactions and substrate-enzyme complex stabilities are underlying their pathogenic Aβ generation. Moreover, first structures of γ-secretase in complex with APP and Notch1 substrates allow insight into how substrate cleavage could be initiated and further progress has been made in the mechanistic understanding of γ-secretase modulators, advanced Aβ-lowering drugs. These insights could be exploited for future AD clinical trials. Inter-national benchmarking of road safety, with the purpose of achieving continuous improvement by learning lessons from existing best practices, has currently been widely encouraged by most countries as an emerging management tool to improve the level of road safety. However, performing a successful road safety benchmarking practice is by no means easy. Challenges exist from ascertaining the benchmarking framework at the very beginning to making final policy decisions. In this study, based on the identification of leading road safety risk factors, a comprehensive set of hierarchically structured safety performance indicators was developed, some necessary data processing procedures were conducted, and the use of data envelopment analysis (DEA) for composite indicator (CI) construction was elaborated. An interval multiple layer DEA-based CI model was proposed to take both the hierarchical structure of the indicators and the data uncertainty into account, and was used to benchmark road safety performance for a set of European countries. Based on the model output, best-performing and underperforming countries were distinguished and all the countries were further ranked by computing their cross-index score. Moreover, by taking the characteristics of each country in the data set into account, country-specific benchmarks for those underperforming countries were identified, and useful insight in the areas of underperformance in each country was gained. find more Meanwhile, by summarizing the risk aspects that need urgent policy action for all these countries, some specific road safety enhancing recommendations for this region as a whole were formulated. The objective of this paper was to develop an injury risk model relating real world injury outcomes in near-side crashes with U.S. New Car Assessment Program (NCAP) test performance, crash, and occupant properties. The study was motivated by the longer-term goal of predicting injury outcomes in a future fleet in which all vehicles are expected to have passive safety performance equivalent to a 5-star NCAP rating level (the highest star rating and lowest risk of injury). The dataset used to evaluate injury risk was the National Automotive Sampling System / Crashworthiness Data System (NASS/CDS). Case years 2010-2015 were used. An injured occupant was defined as a vehicle occupant who experienced an injury of maximum Abbreviated Injury Scale (AIS) of 2 or greater, or who were fatally injured. Injury severity was scored using AIS-2005 (2008 update). Cases were selected in which front-row occupants of late-model vehicles were exposed to a near-side crash. Logistic regression was used to develop an injury model with delta-v, belt status, age, and gender as predictor variables. The side crash performance of each vehicle was identified and added to the model by matching each case with the associated performance in the NCAP moving deformable barrier side impact crash test. NCAP MDB test performance, delta-v, and occupant age, sex, and BMI were found to be significant predictors of injury risk. The effect of a 5 % higher risk in the MDB test (approximately one star rating worse) was comparable to a 2.84 km/h increase in delta-v. This model informs the development of active safety systems in a future fleet where vehicle passive safety performance is higher, quantified by the NCAP MDB test.