Traffic incident clearance time and arrival time prediction based on hazard models

Accurate prediction of incident duration is not only important information of Traffic Incident Management System, but also an ffective input for travel time prediction. In this paper, the hazard based prediction odels are developed for both incident clearance time and arrival time. The data are obtained from the Queensland Department of Transport and Main Roads’ STREAMS Incident Management System (SIMS) for one year ending in November 2010. The best fitting distributions are drawn for both clearance and arrival time for 3 types of incident: crash, stationary vehicle, and hazard. The results show that Gamma, Log-logistic, and Weibull are the best fit for crash, stationary vehicle, and hazard incident, respectively. The obvious impact factors are given for crash clearance time and arrival time. The quantitative influences for crash and hazard incident are presented for both clearance and arrival. The model accuracy is analyzed at the end.

A tag-based personalized item recommendation system using tensor modeling and topic model approaches

This research falls in the area of enhancing the quality of tag-based item recommendation systems. It aims to achieve this by employing a multi-dimensional user profile approach and by analyzing the semantic aspects of tags. Tag-based recommender systems have two characteristics that need to be carefully studied in order to build a reliable system. Firstly, the multi-dimensional correlation, called as tag assignment , should be appropriately modelled in order to create the user profiles [1]. Secondly, the semantics behind the tags should be considered properly as the flexibility with their design can cause semantic problems such as synonymy and polysemy [2]. This research proposes to address these two challenges for building a tag-based item recommendation system by employing tensor modeling as the multi-dimensional user profile approach, and the topic model as the semantic analysis approach. The first objective is to optimize the tensor model reconstruction and to improve the model performance in generating quality rec-ommendation. A novel Tensor-based Recommendation using Probabilistic Ranking (TRPR) method [3] has been developed. Results show this method to be scalable for large datasets and outperforming the benchmarking methods in terms of accuracy. The memory efficient loop implements the n-mode block-striped (matrix) product for tensor reconstruction as an approximation of the initial tensor. The probabilistic ranking calculates the probabil-ity of users to select candidate items using their tag preference list based on the entries generated from the reconstructed tensor. The second objective is to analyse the tag semantics and utilize the outcome in building the tensor model. This research proposes to investigate the problem using topic model approach to keep the tags nature as the “social vocabulary” [4]. For the tag assignment data, topics can be generated from the occurrences of tags given for an item. However there is only limited amount of tags availa-ble to represent items as collection of topics, since an item might have only been tagged by using several tags. Consequently, the generated topics might not able to represent the items appropriately. Furthermore, given that each tag can belong to any topics with various probability scores, the occurrence of tags cannot simply be mapped by the topics to build the tensor model. A standard weighting technique will not appropriately calculate the value of tagging activity since it will define the context of an item using a tag instead of a topic.

Levels and trends of PBDEs and HBCDs in the global environment : status at the end of 2012

In this paper, we have compiled and reviewed the most recent literature, published from January2010 to December 2012, relating to the human exposure, environmental distribution, behaviour, fate and concentration time trends of polybrominated diphenyl ether (PBDE) and hexabromocyclododecane (HBCD) flame retardants, in order to establish their current trends and priorities for future study. Due to the large volume of literature included, we have provided full detail of the reviewed studies as Electronic Supplementary Information and here summarise the most relevant findings. Decreasing time trends for penta-mix PBDE congeners were seen for soils in northern Europe, sewage sludge in Sweden and the USA, carp from a US river, trout from three of the Great Lakes and in Arctic and UK marine mammals and many birds, but increasing time trends continue in Arctic polar bears and some birds at high trophic levels in northern Europe. This is a result of the time delay inherent in long-range atmospheric transport processes. In general, concentrations of BDE209 (the major component of the deca-mix PBDE product) are continuing to increase. Of major concern is the possible/likely debromination of the large reservoir of BDE209 in soils and sediments worldwide, to yield lower brominated congeners which are both more mobile and more toxic, and we have compiled the most recent evidence for the occurrence of this degradation process. Numerous studies reported here reinforce the importance o f this future concern. Time trends for HBCDs are mixed, with both increases and decreases evident in different matrices and locations and, notably, with increasing occurrence in birds of prey.

Investigating the interplay between transport, land use and the environment : a review of the literature

Integration of land use and transport decisions to achieve sustainable travel behavior has been considered an integral element for sustainable urban development. However, before the popularity of urban sustainability concept, land use and transport interaction had been scrutinized as strictly separate entities in the urban planning and development domains. Fortunately today the concept of sustainability has been pushed to the forefront of policy-making and politics as the world wakes up to the impacts of climate change and the effects of the rapid urbanization and modern urban lifestyles. The paper therefore aims to highlight the importance of the interplay between transport, land use and the environment. This review paper provides evidence from the literature including the Transport, Land Use and the Environment Special Issue contributions and global best practice cases to showcase new empirical approaches and investigations from different parts of the world that contribute to the wealth of knowledge in exploring the interplay between transport, land use and the environment thoroughly.

Analyzing busway station potential capacity under mixed stopping and non-stopping operation

Busway stations are the interface between passengers and services. The station is crucial to line operation as it is typically the only location where buses can pass each other. Congestion may occur here when buses manoeuvring into and out of the platform lane interfere with bus flow, or when a queue of buses forms upstream of the platform lane blocking the passing lane. Further, some systems include operation where express buses do not observe the station, resulting in a proportion of non-stopping buses. It is important to understand the operation of the station under this type of operation and its effect on busway capacity. This study uses microscopic simulation to treat the busway station operation and to analyse the relationship between station potential capacity where all buses stop, and Mixed Potential Capacity where there is a mixture of stopping and non-stopping buses. First, the micro simulation technique is used to analyze the All Stopping Buses (ASB) scenario and then statistical model is tuned and calibrated for a specified range of controlled scenarios of dwell time characteristics Subsequently, a mathematical model is developed for Mixed Stopping Buses (MSB) Potential Capacity by introducing different proportions of express (or non-stopping) buses. The proposed models for a busway station bus capacity provide a better understanding of operation and are useful to transit agencies in busway planning, design and operation.

Model-based analysis and optimization of bioreactor for hematopoietic stem cell cultivation

One of the problems to be solved in attaining the full potentials of hematopoietic stem cell (HSC) applications is the limited availability of the cells. Growing HSCs in a bioreactor offers an alternative solution to this problem. Besides, it also offers the advantages of eliminating labour intensive process as well as the possible contamination involved in the periodic nutrient replenishments in the traditional T-flask stem cell cultivation. In spite of this, the optimization of HSC cultivation in a bioreactor has been barely explored. This manuscript discusses the development of a mathematical model to describe the dynamics in nutrient distribution and cell concentration of an ex vivo HSC cultivation in a microchannel perfusion bioreactor. The model was further used to optimize the cultivation by proposing three alternative feeding strategies in order to prevent the occurrence of nutrient limitation in the bioreactor. The evaluation of these strategies, the periodic step change increase in the inlet oxygen concentration, the periodic step change increase in the media inflow, and the feedback control of media inflow, shows that these strategies can successfully improve the cell yield of the bioreactor. In general, the developed model is useful for the design and optimization of bioreactor operation.

Testing times for the implementation of curriculum change: Analysis and extension of a curriculum change model

School curriculum change processes have traditionally been managed internally. However, in Queensland, Australia, as a response to the current high-stakes accountability regime, more and more principals are outsourcing this work to external change agents (ECAs). In 2009, one of the authors (a university lecturer and ECA) developed a curriculum change model (the Controlled Rapid Approach to Curriculum Change (CRACC)), specifically outlining the involvement of an ECA in the initiation phase of a school’s curriculum change process. The purpose of this paper is to extend the CRACC model by unpacking the implementation phase, drawing on data from a pilot study of a single school. Interview responses revealed that during the implementation phase, teachers wanted to be kept informed of the wider educational context; use data to constantly track students; relate pedagogical practices to testing practices; share information between departments and professional levels; and, own whole school performance. It is suggested that the findings would be transferable to other school settings and internal leadership of curriculum change. The paper also strikes a chord of concern – Do the responses from teachers operating in such an accountability regime live their professional lives within this corporate and globalised ideology whether they want to or not?

Predictive motion planning for AUVs subject to strong time-varying currents and forecasting uncertainties

This paper presents a novel path planning method for minimizing the energy consumption of an autonomous underwater vehicle subjected to time varying ocean disturbances and forecast model uncertainty. The algorithm determines 4-Dimensional path candidates using Nonlinear Robust Model Predictive Control (NRMPC) and solutions optimised using A*-like algorithms. Vehicle performance limits are incorporated into the algorithm with disturbances represented as spatial and temporally varying ocean currents with a bounded uncertainty in their predictions. The proposed algorithm is demonstrated through simulations using a 4-Dimensional, spatially distributed time-series predictive ocean current model. Results show the combined NRMPC and A* approach is capable of generating energy-efficient paths which are resistant to both dynamic disturbances and ocean model uncertainty.

The Arctic Summer Cloud Ocean Study (ASCOS): overview and experimental design

The climate in the Arctic is changing faster than anywhere else on earth. Poorly understood feedback processes relating to Arctic clouds and aerosol–cloud interactions contribute to a poor understanding of the present changes in the Arctic climate system, and also to a large spread in projections of future climate in the Arctic. The problem is exacerbated by the paucity of research-quality observations in the central Arctic. Improved formulations in climate models require such observations, which can only come from measurements in situ in this difficult-to-reach region with logistically demanding environmental conditions. The Arctic Summer Cloud Ocean Study (ASCOS) was the most extensive central Arctic Ocean expedition with an atmospheric focus during the International Polar Year (IPY) 2007–2008. ASCOS focused on the study of the formation and life cycle of low-level Arctic clouds. ASCOS departed from Longyearbyen on Svalbard on 2 August and returned on 9 September 2008. In transit into and out of the pack ice, four short research stations were undertaken in the Fram Strait: two in open water and two in the marginal ice zone. After traversing the pack ice northward, an ice camp was set up on 12 August at 87°21' N, 01°29' W and remained in operation through 1 September, drifting with the ice. During this time, extensive measurements were taken of atmospheric gas and particle chemistry and physics, mesoscale and boundary-layer meteorology, marine biology and chemistry, and upper ocean physics. ASCOS provides a unique interdisciplinary data set for development and testing of new hypotheses on cloud processes, their interactions with the sea ice and ocean and associated physical, chemical, and biological processes and interactions. For example, the first-ever quantitative observation of bubbles in Arctic leads, combined with the unique discovery of marine organic material, polymer gels with an origin in the ocean, inside cloud droplets suggests the possibility of primary marine organically derived cloud condensation nuclei in Arctic stratocumulus clouds. Direct observations of surface fluxes of aerosols could, however, not explain observed variability in aerosol concentrations, and the balance between local and remote aerosols sources remains open. Lack of cloud condensation nuclei (CCN) was at times a controlling factor in low-level cloud formation, and hence for the impact of clouds on the surface energy budget. ASCOS provided detailed measurements of the surface energy balance from late summer melt into the initial autumn freeze-up, and documented the effects of clouds and storms on the surface energy balance during this transition. In addition to such process-level studies, the unique, independent ASCOS data set can and is being used for validation of satellite retrievals, operational models, and reanalysis data sets.

Realizing the 'hindered charge ordered phase' in nanoscale charge ordered manganites: magnetization, magneto-transport and EPR investigations

We report three prominent observations made on the nanoscale charge ordered ( CO) manganites RE(1-x)AE(x)MnO(3) (RE = Nd, Pr; AE = Ca; x = 0.5) probed by temperature dependent magnetization and magneto-transport, coupled with electron magnetic/paramagnetic resonance spectroscopy (EMR/EPR). First, evidence is presented to show that the predominant ground state magnetic phase in nanoscale CO manganites is ferromagnetic and it coexists with a residual anti-ferromagnetic phase. Secondly, the shallow minimum in the temperature dependence of the EPR linewidth shows the presence of a charge ordered phase in nanoscale manganites which was shown to be absent from the DC static magnetization and transport measurements. Thirdly, the EPR linewidth, reflective of spin dynamics, increases significantly with a decrease of particle size in CO manganites. We discuss the interesting observations made on various samples of different particle sizes and give possible explanations. We have shown that EMR spectroscopy is a highly useful technique to probe the 'hindered charge ordered phase' in nanoscale CO manganites, which is not possible by static DC magnetization and transport measurements.

Side Chain Structure Determines Unique Physiologic and Therapeutic Properties of norUrsodeoxycholic Acid in Mdr2(-/-) Mice

24-norursodeoxycholic acid (norUDCA), a side chain-modified ursodeoxycholic acid derivative, has dramatic therapeutic effects in experimental cholestasis and may be a promising agent for the treatment of cholestatic liver diseases. We aimed to better understand the physiologic and therapeutic properties of norUDCA and to test if they are related to its side chain length and/or relative resistance to amidation. For this purpose, Mdr2-/- mice, a model for sclerosing cholangitis, received either a standard diet or a norUDCA-, tauro norursodeoxycholic acid (tauro- norUDCA)-, or di norursodeoxycholic acid (di norUDCA)-enriched diet. Bile composition, serum biochemistry, liver histology, fibrosis, and expression of key detoxification and transport systems were investigated. Direct choleretic effects were addressed in isolated bile duct units. The role of Cftr for norUDCA-induced choleresis was explored in Cftr-/- mice. norUDCA had pharmacologic features that were not shared by its derivatives, including the increase in hepatic and serum bile acid levels and a strong stimulation of biliary HCO3- -output. norUDCA directly stimulated fluid secretion in isolated bile duct units in a HCO3- -dependent fashion to a higher extent than the other bile acids. Notably, the norUDCA significantly stimulated HCO 3- -output also in Cftr-/- mice. In Mdr2-/- mice, cholangitis and fibrosis strongly improved with norUDCA, remained unchanged with tauro- norUDCA, and worsened with di norUDCA. Expression of Mrp4, Cyp2b10, and Sult2a1 was increased by norUDCA and di norUDCA, but was unaffected by tauro- norUDCA. Conclusion:The relative resistance of norUDCA to amidation may explain its unique physiologic and pharmacologic properties. These include the ability to undergo cholehepatic shunting and to directly stimulate cholangiocyte secretion, both resulting in a HCO3- -rich hypercholeresis that protects the liver from cholestatic injury.

NIR model development and robustness in prediction of melon fruit total soluble solids

Near infrared spectroscopy (NIRS) can be used for the on-line, non-invasive assessment of fruit for eating quality attributes such as total soluble solids (TSS). The robustness of multivariate calibration models, based on NIRS in a partial transmittance optical geometry, for the assessment of TSS of intact rockmelons (Cucumis melo) was assessed. The mesocarp TSS was highest around the fruit equator and increased towards the seed cavity. Inner mesocarp TSS levels decreased towards both the proximal and distal ends of the fruit, but more so towards the proximal end. The equatorial region of the fruit was chosen as representative of the fruit for near infrared assessment of TSS. The spectral window for model development was optimised at 695-1045 nm, and the data pre-treatment procedure was optimised to second-derivative absorbance without scatter correction. The 'global' modified partial least squares (MPLS) regression modelling procedure of WINISI (ver. 1.04) was found to be superior with respect to root mean squared error of prediction (RMSEP) and bias for model predictions of TSS across seasons, compared with the 'local' MPLS regression procedure. Updating of the model with samples selected randomly from the independent validation population demonstrated improvement in both RMSEP and bias with addition of approximately 15 samples.

Long-term trends in fertility of soils under continuous cultivation and cereal cropping in southern Queensland. IX. Simulation of soil carbon and nitrogen pools using CENTURY model

Cultivation and cropping of soils results in a decline in soil organic carbon and soil nitrogen, and can lead to reduced crop yields. The CENTURY model was used to simulate the effects of continuous cultivation and cereal cropping on total soil organic matter (C and N), carbon pools, nitrogen mineralisation, and crop yield from 6 locations in southern Queensland. The model was calibrated for each replicate from the original datasets, allowing comparisons for each replicate rather than site averages. The CENTURY model was able to satisfactorily predict the impact of long-term cultivation and cereal cropping on total organic carbon, but was less successful in simulating the different fractions and nitrogen mineralisation. The model firstly over-predicted the initial (pre-cropping) soil carbon and nitrogen concentration of the sites. To account for the unique shrinking and swelling characteristics of the Vertosol soils, the default annual decomposition rates of the slow and passive carbon pools were doubled, and then the model accurately predicted initial conditions. The ability of the model to predict carbon pool fractions varied, demonstrating the difficulty inherent in predicting the size of these conceptual pools. The strength of the model lies in the ability to closely predict the starting soil organic matter conditions, and the ability to predict the impact of clearing, cultivation, fertiliser application, and continuous cropping on total soil carbon and nitrogen.

Simple software processes and tests improve the reliability and usefulness of a model.

Models are abstractions of reality that have predetermined limits (often not consciously thought through) on what problem domains the models can be used to explore. These limits are determined by the range of observed data used to construct and validate the model. However, it is important to remember that operating the model beyond these limits, one of the reasons for building the model in the first place, potentially brings unwanted behaviour and thus reduces the usefulness of the model. Our experience with the Agricultural Production Systems Simulator (APSIM), a farming systems model, has led us to adapt techniques from the disciplines of modelling and software development to create a model development process. This process is simple, easy to follow, and brings a much higher level of stability to the development effort, which then delivers a much more useful model. A major part of the process relies on having a range of detailed model tests (unit, simulation, sensibility, validation) that exercise a model at various levels (sub-model, model and simulation). To underline the usefulness of testing, we examine several case studies where simulated output can be compared with simple relationships. For example, output is compared with crop water use efficiency relationships gleaned from the literature to check that the model reproduces the expected function. Similarly, another case study attempts to reproduce generalised hydrological relationships found in the literature. This paper then describes a simple model development process (using version control, automated testing and differencing tools), that will enhance the reliability and usefulness of a model.