A rapid and label-free dual detection of Hg (II) and cysteine with the use of fluorescence switching of graphene quantum dots

A simple and rapid method of analysis for mercury ions (Hg2+) and cysteine (Cys) was developed with the use of graphene quantum dots (GQDs) as a fluorescent probe. In the presence of GQDs, Hg2+ cations are absorbed on their negatively charged surface by means of electrostatic interactions. Thus, the fluorescence (FL) of the GQDs would be significantly quenched as a result of the FL charge transfer, e.g. 92% quenching at 450 nm occurs for a 5 μmol L−1 Hg2+ solution. However, when Cys was added, a significant FL enhancement was observed (510% at 450 nm for a 8.0 μmol L−1 Cys solution), and Hg2+ combined with Cys rather than with the GQDs in an aqueous solution. This occurred because a strong metalsingle bondthiol bond formed, displacing the weak electrostatic interactions, and this resulted in an FL enhancement of the GQDs. The limits of detection (LOD) for Hg2+ and Cys were 0.439 nmol L−1 and 4.5 nmol L−1, respectively. Also, this method was used successfully to analyze Hg2+ and Cys in spiked water samples.

The root locus method: application to linear stability analysis and design of cooperative car-following models

A global framework for linear stability analyses of traffic models, based on the dispersion relation root locus method, is presented and is applied taking the example of a broad class of car-following (CF) models. This approach is able to analyse all aspects of the dynamics: long waves and short wave behaviours, phase velocities and stability features. The methodology is applied to investigate the potential benefits of connected vehicles, i.e. V2V communication enabling a vehicle to send and receive information to and from surrounding vehicles. We choose to focus on the design of the coefficients of cooperation which weights the information from downstream vehicles. The coefficients tuning is performed and different ways of implementing an efficient cooperative strategy are discussed. Hence, this paper brings design methods in order to obtain robust stability of traffic models, with application on cooperative CF models

Flow evaluation and hemolysis analysis of BVAD centrifugal blood pump by computational fluids dynamics

Computational fluid dynamics (CFD) and particle image velocimetry (PIV) are commonly used techniques to evaluate the flow characteristics in the development stage of blood pumps. CFD technique allows rapid change to pump parameters to optimize the pump performance without having to construct a costly prototype model. These techniques are used in the construction of a bi-ventricular assist device (BVAD) which combines the functions of LVAD and RVAD in a compact unit. The BVAD construction consists of two separate chambers with similar impellers, volutes, inlet and output sections. To achieve the required flow characteristics of an average flow rate of 5 l/min and different pressure heads (left – 100mmHg and right – 20mmHg), the impellers were set at different rotating speeds. From the CFD results, a six-blade impeller design was adopted for the development of the BVAD. It was also observed that the fluid can flow smoothly through the pump with minimum shear stress and area of stagnation which are related to haemolysis and thrombosis. Based on the compatible Reynolds number the flow through the model was calculated for the left and the right pumps. As it was not possible to have both the left and right chambers in the experimental model, the left and right pumps were tested separately.

VIP Barcoding: Composition vector-based software for rapid species identification based on DNA barcoding

Species identification based on short sequences of DNA markers, that is, DNA barcoding, has emerged as an integral part of modern taxonomy. However, software for the analysis of large and multilocus barcoding data sets is scarce. The Basic Local Alignment Search Tool (BLAST) is currently the fastest tool capable of handling large databases (e.g. >5000 sequences), but its accuracy is a concern and has been criticized for its local optimization. However, current more accurate software requires sequence alignment or complex calculations, which are time-consuming when dealing with large data sets during data preprocessing or during the search stage. Therefore, it is imperative to develop a practical program for both accurate and scalable species identification for DNA barcoding. In this context, we present VIP Barcoding: a user-friendly software in graphical user interface for rapid DNA barcoding. It adopts a hybrid, two-stage algorithm. First, an alignment-free composition vector (CV) method is utilized to reduce searching space by screening a reference database. The alignment-based K2P distance nearest-neighbour method is then employed to analyse the smaller data set generated in the first stage. In comparison with other software, we demonstrate that VIP Barcoding has (i) higher accuracy than Blastn and several alignment-free methods and (ii) higher scalability than alignment-based distance methods and character-based methods. These results suggest that this platform is able to deal with both large-scale and multilocus barcoding data with accuracy and can contribute to DNA barcoding for modern taxonomy. VIP Barcoding is free and available at http://msl.sls.cuhk.edu.hk/vipbarcoding/.

A CCG virtual system for big data application communication costs analysis

Network topology and routing are two important factors in determining the communication costs of big data applications at large scale. As for a given Cluster, Cloud, or Grid system, the network topology is fixed and static or dynamic routing protocols are preinstalled to direct the network traffic. Users cannot change them once the system is deployed. Hence, it is hard for application developers to identify the optimal network topology and routing algorithm for their applications with distinct communication patterns. In this study, we design a CCG virtual system (CCGVS), which first uses container-based virtualization to allow users to create a farm of lightweight virtual machines on a single host. Then, it uses software-defined networking (SDN) technique to control the network traffic among these virtual machines. Users can change the network topology and control the network traffic programmingly, thereby enabling application developers to evaluate their applications on the same system with different network topologies and routing algorithms. The preliminary experimental results through both synthetic big data programs and NPB benchmarks have shown that CCGVS can represent application performance variations caused by network topology and routing algorithm.

A novel near-infrared spectroscopy and chemometrics method for rapid analysis of several chemical components and antioxidant activity of mint (mentha haplocalyx briq.) samples

A novel near-infrared spectroscopy (NIRS) method has been researched and developed for the simultaneous analyses of the chemical components and associated properties of mint (Mentha haplocalyx Briq.) tea samples. The common analytes were: total polysaccharide content, total flavonoid content, total phenolic content, and total antioxidant activity. To resolve the NIRS data matrix for such analyses, least squares support vector machines was found to be the best chemometrics method for prediction, although it was closely followed by the radial basis function/partial least squares model. Interestingly, the commonly used partial least squares was unsatisfactory in this case. Additionally, principal component analysis and hierarchical cluster analysis were able to distinguish the mint samples according to their four geographical provinces of origin, and this was further facilitated with the use of the chemometrics classification methods-K-nearest neighbors, linear discriminant analysis, and partial least squares discriminant analysis. In general, given the potential savings with sampling and analysis time as well as with the costs of special analytical reagents required for the standard individual methods, NIRS offered a very attractive alternative for the simultaneous analysis of mint samples.

Customised osteotomy guides and endoprosthetic reconstruction for periacetabular tumours

Purpose We sought to analyse clinical and oncological outcomes of patients after guided resection of periacetabular tumours and endoprosthetic reconstruction of the remaining defect. Methods From 1988 to 2008, we treated 56 consecutive patients (mean age 52.5 years, 41.1 % women). Patients were followed up either until death or February 2011 (mean follow up 5.5 years, range 0.1–22.5, standard deviation ± 5.3). Kaplan–Meier analysis was used to estimate survival rates. Results Disease-specific survival was 59.9 % at five years and 49.7 % at ten and 20 years, respectively. Wide resection margins were achieved in 38 patients, whereas 11 patients underwent marginal and seven intralesional resection. Survival was significantly better in patients with wide or marginal resection than in patients with intralesional resection (p = 0.022). Survival for patients with secondary tumours was significantly worse than for patients with primary tumours (p = 0.003). In 29 patients (51.8 %), at least one reoperation was necessary, resulting in a revision-free survival of 50.5 % at five years, 41.1 % at ten years and 30.6 % at 20 years. Implant survival was 77.0 % at five years, 68.6 % at ten years and 51.8 % at 20 years. A total of 35 patients (62.5 %) experienced one or more complications after surgery. Ten of 56 patients (17.9 %) experienced local recurrence after a mean of 8.9 months. The mean postoperative Musculoskeletal Tumor Society (MSTS) score was 18.1 (60.1 %). Conclusion The surgical approach assessed in this study simplifies the process of tumour resection and prosthesis implantation and leads to acceptable clinical and oncological outcomes.

Linear and weakly nonlinear stability analyses of cooperative car-following models

Stability analyses have been widely used to better understand the mechanism of traffic jam formation. In this paper, we consider the impact of cooperative systems (a.k.a. connected vehicles) on traffic dynamics and, more precisely, on flow stability. Cooperative systems are emerging technologies enabling communication between vehicles and/or with the infrastructure. In a distributed communication framework, equipped vehicles are able to send and receive information to/from other equipped vehicles. Here, the effects of cooperative traffic are modeled through a general bilateral multianticipative car-following law that improves cooperative drivers' perception of their surrounding traffic conditions within a given communication range. Linear stability analyses are performed for a broad class of car-following models. They point out different stability conditions in both multianticipative and nonmultianticipative situations. To better understand what happens in unstable conditions, information on the shock wave structure is studied in the weakly nonlinear regime by the mean of the reductive perturbation method. The shock wave equation is obtained for generic car-following models by deriving the Korteweg de Vries equations. We then derive traffic-state-dependent conditions for the sign of the solitary wave (soliton) amplitude. This analytical result is verified through simulations. Simulation results confirm the validity of the speed estimate. The variation of the soliton amplitude as a function of the communication range is provided. The performed linear and weakly nonlinear analyses help justify the potential benefits of vehicle-integrated communication systems and provide new insights supporting the future implementation of cooperative systems.

Zombies on the road: A holistic design approach to balancing gamification and safe driving [poster]

This paper explores novel driving experiences that make use of gamification and augmented reality in the car. We discuss our design considerations, which are grounded in road safety psychology and video game design theory. We aim to address the tension between safe driving practices and player engagement. Specifically, we propose a holistic, iterative thinking process inspired by game design cognition and share our insights generated through the application of this process. We present preliminary game concepts that blend digital components with physical elements from the driving environment. We further highlight how this design process helped us to iteratively evolve these concepts towards being safer while maintaining fun. These insights and game design cognition itself will be useful to the AutomotiveUI community investigating similar novel driving experiences.

Towards development of a rapid and effective non-destructive testing strategy to identify brominated flame retardants in the plastics of consumer products

Polybrominated diphenyl ethers (PBDEs) are a class of brominated flame retardants (BFRs) once extensively used in the plastics of a wide range of consumer products. The listing of certain congeners that are constituents of commercial PBDE mixtures (including c-octaBDE) in the Stockholm Convention and tightening regulation of many other BFRs in recent years have created the need for a rapid and effective method of identifying BFR-containing plastics. A three-tiered testing strategy comparing results from non-destructive testing (X-ray fluorescence (XRF)) (n = 1714), a surface wipe test (n = 137) and destructive chemical analysis (n = 48) was undertaken to systematically identify BFRs in a wide range of consumer products. XRF rapidly identified bromine in 92% of products later confirmed to contain BFRs. Surface wipes of products identified tetrabromobisphenol A (TBBPA), c-octaBDE congeners and BDE-209 with relatively high accuracy (> 75%) when confirmed by destructive chemical analysis. A relationship between the amounts of BFRs detected in surface wipes and subsequent destructive testing shows promise in predicting not only the types of BFRs present but also estimating the concentrations present. Information about the types of products that may contain persistent BFRs will assist regulators in implementing policies to further reduce the occurrence of these chemicals in consumer products.

Collaborative learning from distributed places and spaces: Exploring the use of virtual collaborative tools for local and global student teamwork projects

Educating responsive graduates. Graduate competencies include reliability, communication skills and ability to work in teams. Students using Collaborative technologies adapt to a new working environment, working in teams and using collaborative technologies for learning. Collaborative Technologies were used not simply for delivery of learning but innovatively to supplement and enrich research-based learning, providing a space for active engagement and interaction with resources and team. This promotes the development of responsive ‘intellectual producers’, able to effectively communicate, collaborate and negotiate in complex work environments. Exploiting technologies. Students use ‘new’ technologies to work collaboratively, allowing them to experience the reality of distributed workplaces incorporating both flexibility and ‘real’ time responsiveness. Students are responsible and accountable for individual and group work contributions in a highly transparent and readily accessible workspace. This experience provides a model of an effective learning tool. Navigating uncertainty and complexity. Collaborative technologies allows students to develop critical thinking and reflective skills as they develop a group product. In this forum students build resilience by taking ownership and managing group work, and navigating the uncertainties and complexities of group dynamics as they constructively and professionally engage in team dialogue and learn to focus on the goal of the team task.

Acceptability of Bus Rapid Transit (BRT) to commuters in Dhaka

This research has made substantial and novel contributions to the body of knowledge by combining mixed, quantitative and qualitative analyses to understand the potential uptake of a proposed Bus Rapid Transit (BRT) system by commuters in a developing country's megacity, using Dhaka, Bangladesh as the case study. The quantitative analysis took a unique approach by dividing the analysis into an exploratory analysis of Revealed Preference (RP) survey data, modelling with RP data and modelling with Preferred Mode Selection (PMS) survey data. The qualitative analysis also made a novel contribution by taking a "lesson drawing" approach from model cities in analysing Dhaka's transport environment.

Molecular self-assembly on graphene

The formation of ordered arrays of molecules via self-assembly is a rapid, scalable route towards the realization of nanoscale architectures with tailored properties. In recent years, graphene has emerged as an appealing substrate for molecular self-assembly in two dimensions. Here, the first five years of progress in supramolecular organization on graphene are reviewed. The self-assembly process can vary depending on the type of graphene employed: epitaxial graphene, grown in situ on a metal surface, and non-epitaxial graphene, transferred onto an arbitrary substrate, can have different effects on the final structure. On epitaxial graphene, the process is sensitive to the interaction between the graphene and the substrate on which it is grown. In the case of graphene that strongly interacts with its substrate, such as graphene/Ru(0001), the inhomogeneous adsorption landscape of the graphene moiré superlattice provides a unique opportunity for guiding molecular organization, since molecules experience spatially constrained diffusion and adsorption. On weaker-interacting epitaxial graphene films, and on non-epitaxial graphene transferred onto a host substrate, self-assembly leads to films similar to those obtained on graphite surfaces. The efficacy of a graphene layer for facilitating planar adsorption of aromatic molecules has been repeatedly demonstrated, indicating that it can be used to direct molecular adsorption, and therefore carrier transport, in a certain orientation, and suggesting that the use of transferred graphene may allow for predictible molecular self-assembly on a wide range of surfaces.

Workers’ attitude towards bus rapid transit: Considering Dhaka, Bangladesh

The Government of Bangladesh is planning to develop and implement Bus Rapid Transit (BRT) in Dhaka city. This paper presents a stated choice survey conducted to understand workers’ attitudes toward BRT in Dhaka. The survey data are analysed using a multinomial logit (MNL) model to scrutinize social and economic factors’ impact on participant’s mode choices. Analysis results reveal that males, workers of higher age, education qualification, and income have a greater tendency towards choosing BRT.

Functional activation during the Rapid Visual Information Processing task in a middle aged cohort: An fMRI study

The Rapid Visual Information Processing (RVIP) task, a serial discrimination task where task performance believed to reflect sustained attention capabilities, is widely used in behavioural research and increasingly in neuroimaging studies. To date, functional neuroimaging research into the RVIP has been undertaken using block analyses, reflecting the sustained processing involved in the task, but not necessarily the transient processes associated with individual trial performance. Furthermore, this research has been limited to young cohorts. This study assessed the behavioural and functional magnetic resonance imaging (fMRI) outcomes of the RVIP task using both block and event-related analyses in a healthy middle aged cohort (mean age = 53.56 years, n = 16). The results show that the version of the RVIP used here is sensitive to changes in attentional demand processes with participants achieving a 43% accuracy hit rate in the experimental task compared with 96% accuracy in the control task. As shown by previous research, the block analysis revealed an increase in activation in a network of frontal, parietal, occipital and cerebellar regions. The event related analysis showed a similar network of activation, seemingly omitting regions involved in the processing of the task (as shown in the block analysis), such as occipital areas and the thalamus, providing an indication of a network of regions involved in correct trial performance. Frontal (superior and inferior frontal gryi), parietal (precuenus, inferior parietal lobe) and cerebellar regions were shown to be active in both the block and event-related analyses, suggesting their importance in sustained attention/vigilance. These networks and the differences between them are discussed in detail, as well as implications for future research in middle aged cohorts.