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Sepsis is a dysregulated host response of severe bloodstream infections, and given its frequency of occurrence and high mortality rate, therapeutic improvements are imperative. A reliable biomimetic strategy for the targeting and separation of bacterial pathogens in bloodstream infections involves the use of the broad-spectrum binding motif of human GP-340, a pattern-recognition receptor of the scavenger receptor cysteine rich (SRCR) superfamily that is expressed on epithelial surfaces but not found in blood. Here we show that these peptides, when conjugated to superparamagnetic iron oxide nanoparticles (SPIONs), can separate various bacterial endotoxins and intact microbes (E. coli, S. aureus, P. aeruginosa and S. marcescens) with high efficiency, especially at low and thus clinically relevant concentrations. This is accompanied by a subsequent strong depletion in cytokine release (TNF, IL-6, IL-1β, Il-10 and IFN-γ), which could have a direct therapeutic impact since escalating immune responses complicates severe bloodstream infections and sepsis courses. SPIONs are coated with aminoalkylsilane and capture peptides are orthogonally ligated to this surface. The particles behave fully cyto- and hemocompatible and do not interfere with host structures. Thus, this approach additionally aims to dramatically reduce diagnostic times for patients with suspected bloodstream infections and accelerate targeted antibiotic therapy. Sepsis is often associated with excessive release of cytokines. This aspect and slow diagnostic procedures are the major therapeutic obstacles. The use of magnetic particles conjugated with small peptides derived from the binding motif of a broad-spectrum mucosal pathogen recognition protein GP-340 provides a highly efficient scavenging platform. These peptides are not found in blood and therefore are not subject to inhibitory mechanisms like in other concepts (mannose binding lectine, aptamers, antibodies). In this work, data are shown on the broad bacterial binding spectrum, highly efficient toxin depletion, which directly reduces the release of cytokines. Host cells are not affected and antibiotics not adsorbed. The particle bound microbes can be recultured without restriction and thus be used directly for diagnostics. [Display omitted] [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a combined method for short-term forecasting of detector counts in urban networks and subsequent traffic demand estimation using the forecasted counts as constraints to estimate origin–destination (OD) flows, route and link volumes. The method is intended to be used in the framework of an adaptive traffic control strategy with consecutive optimization intervals of 15min. The method continuously estimates the forthcoming traffic demand that can be used as input data for the optimization. The forecasting uses current and reference space–time-patterns of detector counts. The reference patterns are derived from data collected in the past. The current pattern comprises all detector counts of the last four time intervals. A simple but effective pattern matching is used for forecasting. The subsequent demand estimation is based on the information minimization model that has been integrated into an iterative procedure with repeated traffic assignment and matrix estimation until a stable solution is found. Some enhancements including the improvement of constraints, redundancy elimination of these constraints and a travel time estimation based on a macroscopic simulation using the Cell Transmission Model have been implemented. The overall method, its modules and its performance, which has been assessed using artificially created data for a real sub-network in Hannover, Germany, by means of a microsimulation with Aimsun NG, are presented in this paper. [Copyright &y& Elsevier]

• Specific fundamental diagrams at intersections make more realistic urban traffic models. • Signal's capacity can be measured from trajectories and approximations can be substituted. • Sampled trajectories alone can inform about cycle length and green time of a signal. • When accumulated on one plot, trajectories are analyzed collectively to retrieve field characteristics. This work presents a methodology for measuring traffic quantities from crowd-sourced trajectories for the purpose of estimating saturation flow rates. First, the observed trajectories are clustered to identify the signal programs that occur over the data collection period. Trajectories with known cycle lengths are accumulated on one space–time plot with their respective green start times at the origin, and then Edie's generalized definitions of traffic variables are adapted to construct a full-scale fundamental diagram. The approach is tested empirically, and the averages and variances of the estimated quantities were within the expected ranges for each type of movement. Results from several movements were also verified against field measurements from a short video recording. The proposed method enables estimations of saturation flow rates over entire networks based on long-term datasets, instead of short-term field measurements. The approach is particularly advantageous for estimations under the unpredictable conditions associated with conflicting movements. [ABSTRACT FROM AUTHOR]

• Control-embedded CAV Platoon Trajectory Planning. • Two-Dimensional Empirically String Stable CAV Trajectory Planning. • CAV Trajectory Planning on Random and Complex Geometric Settings. • A New Control-embedded Solving Algorithm based on the Rapid Random Tree Technique. This paper presents a cooperative two-dimensional trajectory planning algorithm for connected and automated vehicle (CAV) platoons. Specifically, the proposed algorithm generates two-dimensional optimal trajectories for CAVs with car-following relationships cooperatively within a complex road geometry. By extending the simplified Newell's car-following model, we propose a two-dimensional Newell's car-following model as an equilibrium car-following policy for CAVs. Based on this, a multi-objective constrained optimization is systematically formulated under a Cartesian coordinate. Due to the constraint's complexity, a new solving algorithm based on the rapid random tree (RRT) technique is proposed. To test the effectiveness of our proposed models and algorithm, numerical simulation experiments with a real-world road geometry are conducted. Results indicate that our proposed method is able to generate trajectories for CAV platoons which are close to the equilibrium condition with smooth controls, while avoiding road obstacles. We further extend the definition of a one-dimensional car-following control string stability to a two-dimensional case. By this definition, we find that the proposed method can achieve empirical two-dimensional string stability, ensuring that both lateral and longitudinal disturbances are attenuated through vehicular strings. [ABSTRACT FROM AUTHOR]

The interactions of motorised vehicles with pedestrians have always been a concern in traffic safety. The major threat to pedestrians comes from the high level of interactions imposed in uncontrolled traffic environments, where road users have to compete over the right of way. In the absence of traffic management and control systems in such traffic environments, road users have to negotiate the right of way while avoiding conflict. Furthermore, the high level of movement freedom and agility of pedestrians, as one of the interactive parties, can lead to exposing unpredictable behaviour on the road. Traffic interactions in uncontrolled mixed traffic environments will become more challenging by fully/partially automated driving systems' deployment, where the intentions and decisions of interacting agents must be predicted/detected to avoid conflict and improve traffic safety and efficiency. This study aims to formulate a game-theoretic approach to model pedestrian interactions with passenger cars and light vehicles (two-wheel and three-wheel vehicles) in uncontrolled traffic settings. The proposed models employ the most influencing factors in the road user's decision and choice of strategy to predict their movements and conflict resolution strategies in traffic interactions. The models are applied to two data sets of video recordings collected in a shared space in Hamburg and a mid-block crossing area in Surat, India, including the interactions of pedestrians with passenger cars and light vehicles, respectively. The models are calibrated using the identified conflicts between users and their conflict resolution strategies in the data sets. The proposed models indicate satisfactory performances considering the stochastic behaviour of road users – particularly in the mid-block crossing area in India – and have the potential to be used as a behavioural model for automated driving systems. • Video analysis of interactions between pedestrians and different vehicle types. • Formulating a methodology to predict road users' strategies to avoid conflicts. • Considering various factors affecting users' decisions in traffic interactions. • Implications for designers of automated driving systems are discussed. [ABSTRACT FROM AUTHOR]

[Display omitted] • First concept for the sustainable remediation of nanoplastics from the environment. • Use of superparamagnetic iron oxide nanoparticles for nanoplastics remediation. • Remediation of different polymers relates to type of SPION. • Applicability was confirmed in DI water as well as in contaminated and river water. • Toxicological assessment confirmed harmlessness. Nano-/microplastics (NP) is a human-made emerging contaminant with worldwide occurrence. The small size (below one micrometer), the different chemical nature and the persistence make NP to potential hazards with suspect probability of tissue penetration and inflammation or as accumulator for toxins. A strategy to stop the spill of novel NP is the remediation from waste water or rivers as prominent distributors. We have developed core–shell superparamagnetic iron oxide nanoparticles (SPIONs) that attract NP and glue them to larger agglomerates which then can be removed from water by applying an external magnetic field. The shell molecules provide two interaction motifs towards NP. The tuned surface potential of the functionalized SPIONs attract complementary charged NP efficiently and the n-alkyl chain is dedicated to preferential interaction towards organic NP rather than inorganic particles. Structural analytics and molecular dynamics simulation support the proposed concept. Systematic remediation experiments with different NP (chemical structures, sizes and mixtures), from different waters – including river water – and with different SPION core materials indicate a universal validity of the concept, with best remediation performance for mixed NP. We suggest a method for broadband remediation of various NP with simple materials and processes, which both have the potential to be up-scaled. [ABSTRACT FROM AUTHOR]

Shared space assumes that the elimination of physical segregation and traffic control measures forces road users to become more alert, move at lower speeds, and rely on the environmental context for negotiating movement. Still, pedestrians tend to feel reluctant about sharing the space with motorized traffic triggering a coexistence problem. By investigating trajectories, shared space is informally divided into three zones: circulation, safe, and activity zone. This study attempts to answer the following research questions: can all road users coexist in the same road space? If yes, under which circumstances, this can be achieved? Three German and one Greek case, presenting different design characteristics and traffic flow compositions, are empirically investigated. Relative variables, namely: pedestrian crossing rate, speed compliance rate and speed deviations, are considered. The findings indicate that vehicle speeds are reduced when the flow of both pedestrians and vehicles is above the mean. A high pedestrian crossing rate is related to higher speed deviations and consequently to heterogeneous driving behavior. By extending the activity or safe zones, the speed compliance rate is significantly reduced, while pedestrians cross more the circulation zone. By providing a wider circulation zone, average vehicle speeds exceed the speed limit. • This study investigates the coexistence problem in four shared space cases. • Shared space is informally divided into zones: circulation, safe, and activity zone. • Pedestrian crossing rate increases in shared spaces with wide activity zones. • A high pedestrian crossing rate leads to high traffic speed deviations. • Wide circulation zones result in vehicle speeds above the speed limit. [ABSTRACT FROM AUTHOR]