The rise of low-cost sensing for managing air pollution in cities

Ever growing populations in cities are associated with a major increase in road vehicles and air pollution. The overall high levels of urban air pollution have been shown to be of a significant risk to city dwellers. However, the impacts of very high but temporally and spatially restricted pollution, and thus exposure, are still poorly understood. Conventional approaches to air quality monitoring are based on networks of static and sparse measurement stations. However, these are prohibitively expensive to capture tempo-spatial heterogeneity and identify pollution hotspots, which is required for the development of robust real-time strategies for exposure control. Current progress in developing low-cost micro-scale sensing technology is radically changing the conventional approach to allow real-time information in a capillary form. But the question remains whether there is value in the less accurate data they generate. This article illustrates the drivers behind current rises in the use of low-cost sensors for air pollution management in cities, whilst addressing the major challenges for their effective implementation.

Exploring variation in measurement as a foundation for statistical thinking in the elementary school

This study was based on the premise that variation is the foundation of statistics and statistical investigations. The study followed the development of fourth-grade students' understanding of variation through participation in a sequence of two lessons based on measurement. In the first lesson all students measured the arm span of one student, revealing pathways students follow in developing understanding of variation and linear measurement (related to research question 1). In the second lesson each student's arm span was measured once, introducing a different aspect of variation for students to observe and contrast. From this second lesson, students' development of the ability to compare their representations for the two scenarios and explain differences in terms of variation was explored (research question 2). Students' documentation, in both workbook and software formats, enabled us to monitor their engagement and identify their increasing appreciation of the need to observe, represent, and contrast the variation in the data. Following the lessons, a written student assessment was used for judging retention of understanding of variation developed through the lessons and the degree of transfer of understanding to a different scenario (research question 3).

Mechanistic details of the membrane perforation and passive translocation of TAT peptides

The trans-activator of transcription (TAT) peptide is regarded as the “gold standard” for cell-penetrating peptides, capable of traversing a mammalian membrane passively into the cytosolic space. This characteristic has been exploited through conjugation of TAT for applications such as drug delivery. However, the process by which TAT achieves membrane penetration remains ambiguous and unresolved. Mechanistic details of TAT peptide action are revealed herein by using three complementary methods: quartz crystal microbalance with dissipation (QCM-D), scanning electrochemical microscopy (SECM) and atomic force microscopy (AFM). When combined, these three scales of measurement define that the membrane uptake of the TAT peptide is by trans-membrane insertion using a “worm-hole” pore that leads to ion permeability across the membrane layer. AFM data provided nanometre-scale visualisation of TAT punctuation using a mammalian-mimetic membrane bilayer. The TAT peptide does not show the same specificity towards a bacterial mimetic membrane and QCM-D and SECM showed that the TAT peptide demonstrates a disruptive action towards these membranes. This investigation supports the energy-independent uptake of the cationic TAT peptide and provides empirical data that clarify the mechanism by which the TAT peptide achieves its membrane activity. The novel use of these three biophysical techniques provides valuable insight into the mechanism for TAT peptide translocation, which is essential for improvements in the cellular delivery of TAT-conjugated cargoes including therapeutic agents required to target specific intracellular locations.

Cross-scale biophysics modelling of F-actin cytoskeleton in cell

This thesis is a comparative study of the modelling of mechanical behaviours of F-actin cytoskeleton which is an important structural component in living cells. A new granular model was developed for F-actin cytoskeleton based on the concept of multiscale modelling. This framework overcomes difficulties encountered in physical modelling of cytoskeleton in conventional continuum mechanics modelling, and the computational challenges in all-atom molecular dynamics simulation. The thermostat algorithm was further modified to better predict the thermodynamic properties of F-actin cytoskeleton in modelling. This multiscale modelling framework was applied in explaining the physical mechanisms of cytoskeleton responses to external mechanical loads.

The validity of personal disturbance scale (DSSI/sAD) in people with diabetes mellitus, using longitudinal data

Despite being used since 1976, Delusions-Symptoms-States-Inventory/states of Anxiety and Depression (DSSI/sAD) has not yet been validated for use among people with diabetes. The aim of this study was to examine the validity of the personal disturbance scale (DSSI/sAD) among women with diabetes using Mater-University of Queensland Study of Pregnancy (MUSP) cohort data. The DSSI subscales were compared against DSM-IV disorders, the Mental Component Score of the Short Form 36 (SF-36 MCS), and Center for Epidemiologic Studies Depression Scale (CES-D). Factor analyses, odds ratios, receiver operating characteristic (ROC) analyses and diagnostic efficiency tests were used to report findings. Exploratory factor analysis and fit indices confirmed the hypothesized two-factor model of DSSI/sAD. We found significant variations in the DSSI/sAD domain scores that could be explained by CES-D (DSSI-Anxiety: 55%, DSSI-Depression: 46%) and SF-36 MCS (DSSI-Anxiety: 66%, DSSI-Depression: 56%). The DSSI subscales predicted DSM-IV diagnosed depression and anxiety disorders. The ROC analyses show that although the DSSI symptoms and DSM-IV disorders were measured concurrently the estimates of concordance remained only moderate. The findings demonstrate that the DSSI/sAD items have similar relationships to one another in both the diabetes and non-diabetes data sets which therefore suggest that they have similar interpretations.

Dynamic agent composition for large-scale agent-based models

PURPOSE: This paper describes dynamic agent composition, used to support the development of flexible and extensible large-scale agent-based models (ABMs). This approach was motivated by a need to extend and modify, with ease, an ABM with an underlying networked structure as more information becomes available. Flexibility was also sought after so that simulations are set up with ease, without the need to program. METHODS: The dynamic agent composition approach consists in having agents, whose implementation has been broken into atomic units, come together at runtime to form the complex system representation on which simulations are run. These components capture information at a fine level of detail and provide a vast range of combinations and options for a modeller to create ABMs. RESULTS: A description of the dynamic agent composition is given in this paper, as well as details about its implementation within MODAM (MODular Agent-based Model), a software framework which is applied to the planning of the electricity distribution network. Illustrations of the implementation of the dynamic agent composition are consequently given for that domain throughout the paper. It is however expected that this approach will be beneficial to other problem domains, especially those with a networked structure, such as water or gas networks. CONCLUSIONS: Dynamic agent composition has many advantages over the way agent-based models are traditionally built for the users, the developers, as well as for agent-based modelling as a scientific approach. Developers can extend the model without the need to access or modify previously written code; they can develop groups of entities independently and add them to those already defined to extend the model. Users can mix-and-match already implemented components to form large-scales ABMs, allowing them to quickly setup simulations and easily compare scenarios without the need to program. The dynamic agent composition provides a natural simulation space over which ABMs of networked structures are represented, facilitating their implementation; and verification and validation of models is facilitated by quickly setting up alternative simulations.

Building cross-scale models of epigenetic mechanisms

Epigenetic changes correspond to heritable modifications of the chromosome structure, which do not involve alteration of the DNA sequence but do affect gene expression. These mechanisms play an important role in normal cell differentiation, but aberration is associated also with several diseases, including cancer and neural disorders. In consequence, despite intensive studies in recent years, the contribution of modifications remains largely unquantified due to overall system complexity and insufficient data. Computational models can provide powerful auxiliary tools to experimentation, not least as scales from the sub-cellular through cell populations (or to networks of genes) can be spanned. In this paper, the challenges to development, of realistic cross-scale models, are discussed and illustrated with respect to current work.

Structural damage alarming and localization of cable-supported bridges using multi-novelty indices: A feasibility study

This paper presents a feasibility study on structural damage alarming and localization of long-span cable-supported bridges using multi-novelty indices formulated by monitoring-derived modal parameters. The proposed method which requires neither structural model nor damage model is applicable to structures of arbitrary complexity. With the intention to enhance the tolerance to measurement noise/uncertainty and the sensitivity to structural damage, an improved novelty index is formulated in terms of auto-associative neural networks (ANNs) where the output vector is designated to differ from the input vector while the training of the ANNs needs only the measured modal properties of the intact structure under in-service conditions. After validating the enhanced capability of the improved novelty index for structural damage alarming over the commonly configured novelty index, the performance of the improved novelty index for damage occurrence detection of large-scale bridges is examined through numerical simulation studies of the suspension Tsing Ma Bridge (TMB) and the cable-stayed Ting Kau Bridge (TKB) incurred with different types of structural damage. Then the improved novelty index is extended to formulate multi-novelty indices in terms of the measured modal frequencies and incomplete modeshape components for damage region identification. The capability of the formulated multi-novelty indices for damage region identification is also examined through numerical simulations of the TMB and TKB.

Large-scale interlaboratory study to develop, analytically validate and apply highly multiplexed, quantitative peptide assays to measure cancer-relevant proteins in plasma

There is an increasing need in biology and clinical medicine to robustly and reliably measure tens-to-hundreds of peptides and proteins in clinical and biological samples with high sensitivity, specificity, reproducibility and repeatability. Previously, we demonstrated that LC-MRM-MS with isotope dilution has suitable performance for quantitative measurements of small numbers of relatively abundant proteins in human plasma, and that the resulting assays can be transferred across laboratories while maintaining high reproducibility and quantitative precision. Here we significantly extend that earlier work, demonstrating that 11 laboratories using 14 LC-MS systems can develop, determine analytical figures of merit, and apply highly multiplexed MRM-MS assays targeting 125 peptides derived from 27 cancer-relevant proteins and 7 control proteins to precisely and reproducibly measure the analytes in human plasma. To ensure consistent generation of high quality data we incorporated a system suitability protocol (SSP) into our experimental design. The SSP enabled real-time monitoring of LC-MRM-MS performance during assay development and implementation, facilitating early detection and correction of chromatographic and instrumental problems. Low to sub-nanogram/mL sensitivity for proteins in plasma was achieved by one-step immunoaffinity depletion of 14 abundant plasma proteins prior to analysis. Median intra- and inter-laboratory reproducibility was <20%, sufficient for most biological studies and candidate protein biomarker verification. Digestion recovery of peptides was assessed and quantitative accuracy improved using heavy isotope labeled versions of the proteins as internal standards. Using the highly multiplexed assay, participating laboratories were able to precisely and reproducibly determine the levels of a series of analytes in blinded samples used to simulate an inter-laboratory clinical study of patient samples. Our study further establishes that LC-MRM-MS using stable isotope dilution, with appropriate attention to analytical validation and appropriate quality c`ontrol measures, enables sensitive, specific, reproducible and quantitative measurements of proteins and peptides in complex biological matrices such as plasma.

Direct measurement as a tool for assessing the accuracy of inverse dynamics

The understanding of the loads generated within the prosthetic leg can aid engineers in the design of components and clinicians in the process of rehabilitation. Traditional methods to assess these loads have relied on inverse dynamics. This indirect method estimates the applied load using video recordings and force-plates located at a distance from the region of interest, such as the base of the residuum. The well-known limitations of this method are related to the accuracy of this recursive model and the experimental conditions required (Frossard et al., 2003). Recent developments in sensors (Frossard et al., 2003) and prosthetic fixation (Brånemark et al., 2000) permit the direct measurement of the loads applied on the residuum of transfemoral amputees. In principle, direct measurement should be an appropriate tool for assessing the accuracy of inverse dynamics. The purpose of this paper is to determine the validity of this assumption. The comparative variable used in this study is the velocity of the relative body center of mass (VCOM(t)). The relativity is used to align the static (w.r.t. position) force plate measurement with the dynamic load cell measurement.

Review of direct measurement of inner prosthesis loading in transfemoral amputation: Potential benefits for evidence-based practice

The understanding of the load applied on the residuum through the prosthesis of individuals with transfemoral amputation (TFA) is essential to address a number of concerns that could strongly reduce their quality of life (e.g., residuum skin lesion, prosthesis fitting, alignment). This inner prosthesis loading could be estimated using a typical gait laboratory relying on inverse dynamics equations. Alternative, technological advances proposed over the last decade enabled direct measurement of this kinetic information in a broad variety of situations that could potentially be more relevant in clinical settings. The purposes of this presentation are (A) to review the literature about recent developments in measure and analyses of inner prosthesis loading of TFA, and (B) to extract information that could potentially contribute to a better evidence-based practice.

Limitations of a laboratory scale model in predicting optimal pilot scale conditions for dilute acid pretreatment of sugarcane bagasse

Pilot and industrial scale dilute acid pretreatment data can be difficult to obtain due to the significant infrastructure investment required. Consequently, models of dilute acid pretreatment by necessity use laboratory scale data to determine kinetic parameters and make predictions about optimal pretreatment conditions at larger scales. In order for these recommendations to be meaningful, the ability of laboratory scale models to predict pilot and industrial scale yields must be investigated. A mathematical model of the dilute acid pretreatment of sugarcane bagasse has previously been developed by the authors. This model was able to successfully reproduce the experimental yields of xylose and short chain xylooligomers obtained at the laboratory scale. In this paper, the ability of the model to reproduce pilot scale yield and composition data is examined. It was found that in general the model over predicted the pilot scale reactor yields by a significant margin. Models that appear very promising at the laboratory scale may have limitations when predicting yields on a pilot or industrial scale. It is difficult to comment whether there are any consistent trends in optimal operating conditions between reactor scale and laboratory scale hydrolysis due to the limited reactor datasets available. Further investigation is needed to determine whether the model has some efficacy when the kinetic parameters are re-evaluated by parameter fitting to reactor scale data, however, this requires the compilation of larger datasets. Alternatively, laboratory scale mathematical models may have enhanced utility for predicting larger scale reactor performance if bulk mass transport and fluid flow considerations are incorporated into the fibre scale equations. This work reinforces the need for appropriate attention to be paid to pilot scale experimental development when moving from laboratory to pilot and industrial scales for new technologies.

Direct measurement of prosthetic loading for evidence-based practice

The demand for an evidence-based clinical practice involving lower limb amputees is increasing. Some of the critical care decisions are related to the loading applied on the residuum partially responsible for comfort and functional outcome. This loading can be assessed using inverse dynamics equations. Typically, this method requires a gait laboratory (e.g., 3D motion analysis system, force-plates). It is mainly suited for the analysis only few steps of walking while being expensive and labour intensive. However, recent scientific and industrial developments demonstrated that discrete and light portable sensors can be placed within the prosthesis to measure accurately the loading during an unlimited number of steps and activities of daily living. Several studies indicated that method based on direct measurements might provide more realistic results. Furthermore, it is a user-friendly method more accessible to clinicians, such as prosthetists. The purpose of this symposium will be to give an overview of these additional opportunities for clinicians to obtain relevant data for evidence-based practice. The three main aims will be: • To present some of the equipment used for direct measurements, • To propose ways to analyse some key data sets, • To give some practical example of data sets for transtibial and transfemoral amputees.

Parallel streaming signature EM-tree: A clustering algorithm for web scale applications

The proliferation of the web presents an unsolved problem of automatically analyzing billions of pages of natural language. We introduce a scalable algorithm that clusters hundreds of millions of web pages into hundreds of thousands of clusters. It does this on a single mid-range machine using efficient algorithms and compressed document representations. It is applied to two web-scale crawls covering tens of terabytes. ClueWeb09 and ClueWeb12 contain 500 and 733 million web pages and were clustered into 500,000 to 700,000 clusters. To the best of our knowledge, such fine grained clustering has not been previously demonstrated. Previous approaches clustered a sample that limits the maximum number of discoverable clusters. The proposed EM-tree algorithm uses the entire collection in clustering and produces several orders of magnitude more clusters than the existing algorithms. Fine grained clustering is necessary for meaningful clustering in massive collections where the number of distinct topics grows linearly with collection size. These fine-grained clusters show an improved cluster quality when assessed with two novel evaluations using ad hoc search relevance judgments and spam classifications for external validation. These evaluations solve the problem of assessing the quality of clusters where categorical labeling is unavailable and unfeasible.

Size-resolved particle distribution and gaseous concentrations by real-world road tunnel measurement

Measurements of aerosol particle number size distributions (15-700 nm), CO and NOx were performed in a bus tunnel, Australia. Daily mean particle size distributions of mixed diesel/CNG (Compressed Natural Gas) buses traffic flow were determined in 4 consecutive measurement days. EFs (Emission Factors) of Particle size distribution of diesel buses and CNG buses were obtained by MLR (Multiple Linear Regression) methods, particle distributions of diesel buses and CNG buses were observed as single accumulation mode and nuclei-mode separately. Particle size distributions of mixed traffic flow were decomposed by two log-normal fitting curves for each 30 minutes interval mean scans, all the mix fleet PSD emission can be well fitted by the summation of two log-normal distribution curves, and these were composed of nuclei mode curve and accumulation curve, which were affirmed as the CNG buses and diesel buses PN emission curves respectively. Finally, particle size distributions of diesel buses and CNG buses were quantified by statistical whisker-box charts. For log-normal particle size distribution of diesel buses, accumulation mode diameters were 74.5～87.5nm, geometric standard deviations were 1.89～1.98. As to log-normal particle size distribution of CNG buses, nuclei-mode diameters were 21～24 nm, geometric standard deviations were 1.27～1.31.