Pre-crash and non-crash traffic flow trends analysis on motorways

Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence, reducing the frequency of crashes assists in addressing congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a short time window around the time of a crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists. We will compare them with normal traffic trends and show this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding to traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash. Using the K-Means clustering method with Euclidean distance function allowed the crashes to be clustered. Then, normal situation data was extracted based on the time distribution of crashes and were clustered to compare with the “high risk” clusters. Five major trends have been found in the clustering results for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Based on these findings, crash likelihood estimation models can be fine-tuned based on the monitored traffic conditions with a sliding window of 30 minutes to increase accuracy of the results and minimize false alarms.

Acquiring search expertise : learning experiences and threshold concepts

Expert searchers engage with information as information brokers, researchers, reference librarians, information architects, faculty who teach advanced search, and in a variety of other information-intensive professions. Their experiences are characterized by a profound understanding of information concepts and skills and they have an agile ability to apply this knowledge to interacting with and having an impact on the information environment. This study explored the learning experiences of searchers to understand the acquisition of search expertise. The research question was: What can be learned about becoming an expert searcher from the learning experiences of proficient novice searchers and highly experienced searchers? The key objectives were: (1) to explore the existence of threshold concepts in search expertise; (2) to improve our understanding of how search expertise is acquired and how novice searchers, intent on becoming experts, can learn to search in more expertlike ways. The participant sample drew from two population groups: (1) highly experienced searchers with a minimum of 20 years of relevant professional experience, including LIS faculty who teach advanced search, information brokers, and search engine developers (11 subjects); and (2) MLIS students who had completed coursework in information retrieval and online searching and demonstrated exceptional ability (9 subjects). Using these two groups allowed a nuanced understanding of the experience of learning to search in expertlike ways, with data from those who search at a very high level as well as those who may be actively developing expertise. The study used semi-structured interviews, search tasks with think-aloud narratives, and talk-after protocols. Searches were screen-captured with simultaneous audio-recording of the think-aloud narrative. Data were coded and analyzed using NVivo9 and manually. Grounded theory allowed categories and themes to emerge from the data. Categories represented conceptual knowledge and attributes of expert searchers. In accord with grounded theory method, once theoretical saturation was achieved, during the final stage of analysis the data were viewed through lenses of existing theoretical frameworks. For this study, threshold concept theory (Meyer & Land, 2003) was used to explore which concepts might be threshold concepts. Threshold concepts have been used to explore transformative learning portals in subjects ranging from economics to mathematics. A threshold concept has five defining characteristics: transformative (causing a shift in perception), irreversible (unlikely to be forgotten), integrative (unifying separate concepts), troublesome (initially counter-intuitive), and may be bounded. Themes that emerged provided evidence of four concepts which had the characteristics of threshold concepts. These were: information environment: the total information environment is perceived and understood; information structures: content, index structures, and retrieval algorithms are understood; information vocabularies: fluency in search behaviors related to language, including natural language, controlled vocabulary, and finesse using proximity, truncation, and other language-based tools. The fourth threshold concept was concept fusion, the integration of the other three threshold concepts and further defined by three properties: visioning (anticipating next moves), being light on one's 'search feet' (dancing property), and profound ontological shift (identity as searcher). In addition to the threshold concepts, findings were reported that were not concept-based, including praxes and traits of expert searchers. A model of search expertise is proposed with the four threshold concepts at its core that also integrates the traits and praxes elicited from the study, attributes which are likewise long recognized in LIS research as present in professional searchers. The research provides a deeper understanding of the transformative learning experiences involved in the acquisition of search expertise. It adds to our understanding of search expertise in the context of today's information environment and has implications for teaching advanced search, for research more broadly within library and information science, and for methodologies used to explore threshold concepts.

Ethanol exposure alters monoamine oxidase gene-expression in neuronal SH-SY5Y cells

Abstract: Monoamine Oxidase (MAO) enzymes catabolise, and thus modulate abundance of, neurotransmitters in the brain. Variation in MAO enzyme activity has been linked to alcohol abuse behaviour, although the molecular mechanisms underlying this association are not understood. The present study evaluated relative gene-transcript abundance of MAO-A and MAO-B in the SH-SY5Y human neuroblastoma cell-line in response to ethanol exposure and following ethanol withdrawal. We found that each isoform of MAO was significantly transcriptionally up-regulated 55-80% in response to 100mM ethanol exposure. This trend was maintained following prolonged exposures (24 h-72 h) and with short exposures (24 h) followed by a period of ethanol withdrawal, suggesting that the transcriptional regulation is the result of a cellular change occurring within the first 24 hours of ethanol exposure. These results suggest a role for MAO transcriptional regulation in the complex neurobiochemical changes underlying alcohol addiction.

Bi-2223 precursor billets for pit wire production

High temperature superconductor precursor billets (feed rods) have been developed for loading into silver tubes. The billets are loaded prior to rolling or drawing operations in PIT wire manufacture. Investigations have shown that wires and tapes prepared from feed rod loaded tubes show enhanced uniformity of electrical transport properties when compared with conventional powder packing, especially in wires drawn to long lengths. Analysis on production feed rods have shown carbon content to be as low as 110 ppm. © 1999 IEEE.

AFM study of morphological changes associated with electrochemical solid--solid transformation of three-dimensional crystals of TCNQ to metal derivatives (metal= Cu, Co, Ni; TCNQ= tetracyanoquinodimethane)

In situ atomic force microscopy (AFM) allows images from the upper face and sides of TCNQ crystals to be monitored during the course of the electrochemical solid–solid state conversion of 50 × 50 μm2 three-dimensional drop cast crystals of TCNQ to CuTCNQ or M[TCNQ]2(H2O)2 (M = Co, Ni). Ex situ images obtained by scanning electron microscopy (SEM) also allow the bottom face of the TCNQ crystals, in contact with the indium tin oxide or gold electrode surface and aqueous metal electrolyte solution, to be examined. Results show that by carefully controlling the reaction conditions, nearly mono-dispersed, rod-like phase I CuTCNQ or M[TCNQ]2(H2O)2 can be achieved on all faces. However, CuTCNQ has two different phases, and the transformation of rod-like phase 1 to rhombic-like phase 2 achieved under conditions of cyclic voltammetry was monitored in situ by AFM. The similarity of in situ AFM results with ex situ SEM studies accomplished previously implies that the morphology of the samples remains unchanged when the solvent environment is removed. In the process of crystal transformation, the triple phase solid∣electrode∣electrolyte junction is confirmed to be the initial nucleation site. Raman spectra and AFM images suggest that 100% interconversion is not always achieved, even after extended electrolysis of large 50 × 50 μm2 TCNQ crystals.

Electrochemically-induced TCNQ/Mn TCNQ 2 (H2O) 2 (TCNQ= 7, 7, 8, 8-Tetracyanoquinodimethane) solid-solid interconversion : two voltammetrically distinct processes that allow selective generation of nanofiber or nanorod network morphologies

Unlike the case with other divalent transition metal M\[TCNQ](2)(H(2)O)(2) (M = Fe, Co, Ni) analogues, the electrochemically induced solid-solid phase interconversion of TCNQ microcrystals (TCNQ = 7,7,8,8-tetracyanoquinodimethane) to Mn\[TCNQ](2)(H(2)O)(2) occurs via two voltammetrically distinct, time dependent processes that generate the coordination polymer in nanofiber or rod-like morphologies. Careful manipulation of the voltammetric scan rate, electrolysis time, Mn(2+)((aq)) concentration, and the method of electrode modification with solid TCNQ allows selective generation of either morphology. Detailed ex situ spectroscopic (IR, Raman), scanning electron microscopy (SEM), and X-ray powder diffraction (XRD) characterization clearly establish that differences in the electrochemically synthesized Mn-TCNQ material are confined to morphology. Generation of the nanofiber form is proposed to take place rapidly via formation and reduction of a Mn-stabilized anionic dimer intermediate, \[(Mn(2+))(TCNQ-TCNQ)(2)(*-)], formed as a result of radical-substrate coupling between TCNQ(*-) and neutral TCNQ, accompanied by ingress of Mn(2+) ions from the aqueous solution at the triple phase TCNQ/electrode/electrolyte boundary. In contrast, formation of the nanorod form is much slower and is postulated to arise from disproportionation of the \[(Mn(2+))(TCNQ-TCNQ)(*-)(2)] intermediate. Thus, identification of the time dependent pathways via the solid-solid state electrochemical approach allows the crystal size of the Mn\[TCNQ](2)(H(2)O)(2) material to be tuned and provides new mechanistic insights into the formation of different morphologies.

Traffic safety risks trends and patterns analysis on motorways

Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestion. Hence, reducing the frequency of crashes assist in addressing congestion issues (Meyer, 2008). Analysing traffic conditions and discovering risky traffic trends and patterns are essential basics in crash likelihood estimations studies and still require more attention and investigation. In this paper we will show, through data mining techniques, that there is a relationship between pre-crash traffic flow patterns and crash occurrence on motorways, compare them with normal traffic trends, and that this knowledge has the potentiality to improve the accuracy of existing crash likelihood estimation models, and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash occurrence. K-Means clustering algorithm applied to determine dominant pre-crash traffic patterns. In the first phase of this research, traffic regimes identified by analysing crashes and normal traffic situations using half an hour speed in upstream locations of crashes. Then, the second phase investigated the different combination of speed risk indicators to distinguish crashes from normal traffic situations more precisely. Five major trends have been found in the first phase of this paper for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Moreover, the second phase explains that spatiotemporal difference of speed is a better risk indicator among different combinations of speed related risk indicators. Based on these findings, crash likelihood estimation models can be fine-tuned to increase accuracy of estimations and minimize false alarms.

From words to integers and beyond in corporate life

Poets have a licence to couch great truths in succinct, emotionally powerful, and perhaps slightly mysterious and ambiguous ways. On the other hand, it is the task of academics to explore such truths intellectually, in depth and detail, identifying the key constructs and their underlying relations and structures, hopefully without impairing the essential truth. So it could be said that in January 2013, around 60 academics gathered at the University of Texas, Austin under the benign and encouraging eye of their own muse, Professor Rod Hart, to play their role in exploring and explaining the underlying truth of Yan Zhen’s words. The goals of this chapter are quite broad. Rod was explicit and yet also somewhat Delphic in his expectations and aspirations for the chapter. Even though DICTION was a key analytic tool in most chapters, this chapter was not to be about DICTION per se, or simply a critique of the individual chapters forming this section of the book. Rather DICTION and these studies, as well as some others that got our attention, were to be more a launching pad for observations on what they revealed about the current state of understanding and research into the language of institutions, as well as some ‘adventurous’, but not too outlandish reflections on future challenges and opportunities.

Trialling low-cost level crossing warning devices in Australia

This paper discusses the methodology and design of the Cooperative Research Centre for Rail Innovation’s national low-cost level crossing trial programme currently being conducted in Australia. Three suppliers of innovative low-cost level crossing warning devices were chosen through a tendering and evaluation process. The paper outlines the acceptance criteria that were used to select the suppliers and describes the different types of train detection technologies and innovative cost- reduction solutions that are being tested as part of the trial. The trial is being hosted by three major railways in three different regions in Australia, where systems from the three suppliers have been installed parallel to a baseline conventional track-circuit based level crossing at each site. The paper discusses our experience to date, the trialling process and the challenges that the project has confronted in order to develop a nationally consistent trialling programme.

Synthesis and spectroscopic characterization of magnesium oxalate nano-crystals

Synthesis of MgC2O4⋅2H2O nano particles was carried out by thermal double decomposition of solutions of oxalic acid dihydrate (C2H2O4⋅2H2O) and Mg(OAc)2⋅4H2O employing CATA-2R microwave reactor. Structural elucidation was carried out by employing X-ray diffraction (XRD), particle size and shape were studied by transmission electron microscopy (TEM) and nature of bonding was investigated by optical absorption and near-infrared (NIR) spectral studies. The powder resulting from this method is pure and possesses distorted rhombic octahedral structure. The synthesized nano rod is 80 nm in diameter and 549 nm in length.

Silver deposits in cutaneous burn scar tissue is a common phenomenon following application of a silver dressing

BACKGROUND Silver dressings have been widely and successfully used to prevent cutaneous wounds, including burns, chronic ulcers, dermatitis and other cutaneous conditions, from infection. However, in a few cases, skin discolouration or argyria-like appearances have been reported. This study investigated the level of silver in scar tissue post-burn injury following application of Acticoat, a silver dressing. METHODS A porcine deep dermal partial thickness burn model was used. Burn wounds were treated with this silver dressing until completion of re-epithelialization, and silver levels were measured in a total of 160 scars and normal tissues. RESULTS The mean level of silver in scar tissue covered with silver dressings was 136 microg/g, while the silver level in normal skin was less than 0.747 microg/g. A number of wounds had a slate-grey appearance, and dissection of the scars revealed brown-black pigment mostly in the middle and deep dermis within the scar. The level of silver and the severity of the slate-grey discolouration were correlated with the length of time of the silver dressing application. CONCLUSIONS These results show that silver deposition in cutaneous scar tissue is a common phenomenon, and higher levels of silver deposits and severe skin discolouration are correlated with an increase in the duration of this silver dressing application.

Silver absorption on burns after the application of Acticoat : data from pediatric patients and a porcine burn model

Silver dressings have been widely used to successfully prevent burn wound infection and sepsis. However, a few case studies have reported the functional abnormality and failure of vital organs, possibly caused by silver deposits. The aim of this study was to investigate the serum silver level in the pediatric burn population and also in several internal organs in a porcine burn model after the application of Acticoat. A total of 125 blood samples were collected from 46 pediatric burn patients. Thirty-six patients with a mean of 13.4% TBSA burns had a mean peak serum silver level of 114 microg/L, whereas 10 patients with a mean of 1.85% TBSA burns had an undetectable level of silver (<5.4 microg/L). Overall, serum silver levels were closely related to burn sizes. However, the highest serum silver was 735 microg/L in a 15-month-old toddler with 10% TBSA burns and the second highest was 367 microg/L in a 3-year old with 28% TBSA burns. In a porcine model with 2% TBSA burns, the mean peak silver level was 38 microg/L at 2 to 3 weeks after application of Acticoat and was then significantly reduced to an almost undetectable level at 6 weeks. Of a total of four pigs, silver was detected in all four livers (1.413 microg/g) and all four hearts (0.342 microg/g), three of four kidneys (1.113 microg/g), and two of four brains (0.402 microg/g). This result demonstrated that although variable, the level of serum silver was positively associated with the size of burns, and significant amounts of silver were deposited in internal organs in pigs with only 2% TBSA burns, after application of Acticoat.

ZnO nanocones with high-index {101̅1} facets for enhanced energy conversion efficiency of dye-sensitized solar cells

ZnO is a promising photoanode material for dye-sensitized solar cells (DSCs) due to its high bulk electron mobility and because different geometrical structures can easily be tailored. Although various strategies have been taken to improve ZnO-based DSC efficiencies, their performances are still far lower than TiO2 counterparts, mainly because low conductivity Zn2+–dye complexes form on the ZnO surfaces. Here, cone-shaped ZnO nanocrystals with exposed reactive O-terminated {101̅1} facets were synthesized and applied in DSC devices. The devices were compared with DSCs made from more commonly used rod-shaped ZnO nanocrystals where {101̅0} facets are predominantly exposed. When cone-shaped ZnO nanocrystals were used, DSCs sensitized with C218, N719, and D205 dyes universally displayed better power conversion efficiency, with the highest photoconversion efficiency of 4.36% observed with the C218 dye. First-principles calculations indicated that the enhanced DSCs performance with ZnO nanocone photoanodes could be attributed to the strength of binding between the dye molecules and reactive O-terminated {101̅1} ZnO facets and that more effective use of dye molecules occurred due to a significantly less dye aggregation on these ZnO surfaces compared to other ZnO facets.