Incidence and costs of bicycle-related traumatic brain injuries in the Netherlands

The main cause of death and serious disability in bicycle accidents is traumatic brain injury (TBI). The aim of this population-based study was to assess the incidence and costs of bicycle-related TBI across various age groups, and in comparison to all bicycle-related injuries, to identify main risk groups for the development of preventive strategies.Data from the National Injury Surveillance System and National Medical Registration were used for all patients with bicycle-related injuries and TBI who visited a Dutch emergency department (ED) between 1998 and 2012. Demographics and national, weighted estimates of injury mechanism, injury severity and costs were analysed per age group. Direct healthcare costs and indirect costs were determined using the incidence-based Dutch Burden of Injury Model.Between 1998 and 2012, the incidence of ED treatments due to bicycle-related TBI strongly increased with 54%, to 43 per 100,000 persons in 2012. However, the incidence of all bicycle-related injuries remained stable, from 444 in 1998 to 456/100,000 in 2012. Incidence of hospital admission increased in both TBI (92%) and all injuries from cycling (71%). Highest increase in incidence of both ED treatments and hospital admissions was seen in adults aged 55+. The injury rate of TBI per kilometre travelled increased (44%) except in children, but decreased (−4%) for all injuries, showing a strong decrease in children (−36%) but an increase in men aged 25+, and women aged 15+. Total costs of bicycle-related TBI were €74.5 million annually. Although bicycle-related TBI accounted for 9% of the incidence of all ED treatments due to cycling, it accounted for 18% of the total costs due to all bicycle-related injuries (€410.7 million). Children and adolescents (aged 0–24) had highest incidence of ED treatments due to bicycle-related injuries. Men in the working population (aged 15–64) had highest indirect costs following injuries from cycling, including TBI. Older cyclists (aged 55+) were identified as main risk group for TBI, as they had highest ED attendance, injury rate, injury severity, admission to hospital or intensive care unit, and costs.Incidence of ED treatments due to cycling are high and often involve TBI, imposing a high burden on individuals and society. Older cyclists aged 55+ were identified as main risk group for TBI to be targeted in preventive strategies, due to their high risk for (serious) injuries and ever-increasing share of ED visits and hospital admissions.     

Mathematical modeling of growth of Salmonella spp. and spoilage microorganisms in raw oysters

The main objective of this study was to develop the primary and secondary models to describe the growth kinetics of Salmonella as well as background microorganisms in raw, shucked oysters. Samples, inoculated with a cocktail of two Salmonella serotypes, S. Typhimurium (CICC22956) and S. Enteritidis (CICC21482), were incubated at 4, 8, 12, 16, 20, 25, 30, 33, 37, 40, and 43 °C. Growth of Salmonella was observed at all temperatures, except at 4 °C. The background microorganisms grew at all temperatures. All growth curves clearly exhibited lag, exponential and stationary phases, and were analyzed using the Huang growth model. Three secondary models (Ratkowsky square-root, Huang square-root, and Cardinal parameter models) were compared for evaluating the effect of temperature on bacterial growth rates. Data analysis was performed using IPMP 2013, a free predictive microbiology software tool developed by the USDA ARS.The Cardinal parameters model underestimated the specific rates of the microorganisms at low temperatures. The Huang square-root model was more suitable than the Ratkowsky square-root model for describing the effect of temperature on growth of Salmonella, while the Ratkowsky square-root model, on the other hand, was more suitable for background microorganisms. For both Salmonella and background microorganisms, the logarithms of the lag phase were expressed as linear functions of the logarithms of specific growth rates. The results of this study can be used by the food retailers and regulatory agencies to estimate the microbial shelf-life of raw, shucked oysters.     

Low shear rheological behaviour of two-phase mesophase pitch

The low shear rate rheology of two phase mesophase pitches derived from coal tar pitch has been investigated. Particulate quinoline insolubles (QI) stabilised the mesophase spheres against coalescence. Viscosity measurements over the range 10–10⁶ Pa s were made at appropriate temperature ranges. Increasing shear thinning behaviour was evident with increasing mesophase content. At low mesophase contents the dominant effect on the near Newtonian viscosity was temperature but at higher contents it was the shear rate; temperature dependence declined to near zero. The data indicated that agglomeration could be occurring at intermediate mesophase volume fractions, 0.2–0.3. The Krieger–Dougherty function and its emulsion analogue indicated that in this region the mesophase pitch emulsions actually behaved like ‘hard’ sphere systems and the effective volume fraction was estimated as a function of shear rate illustrating the change in extent of agglomeration. At the higher volume fractions approaching the maximum packing fraction, which could only be measured at higher temperatures, the shear thinning behaviour changed in character and it is considered that this is possibly due to shear induced deformation and breakup of dispersed drops in the shear field.     

A robust method for axis identification

The present paper proposes a new method for axis identification in discrete axially symmetrical geometric models. This method is based on-a-never-used-before property of the axially symmetrical surfaces for which the symmetry line of any section curve of the surface (or of a portion of it in the case of an incomplete axially symmetrical surface) always intersects the axis of symmetry of the surface. Thus the working principle of the method makes it very robust to local defectiveness, measurement noise and outliers.In order to compare it with the most cited methods presented in literature, several types of tests have been designed and performed. The robustness of those methods, on the one hand, has been evaluated by defining the Statistical Confidence Boundary at 1σ confidence level. The trueness of the method, on the other hand, has been evaluated on geometric models obtained by measuring real objects. The high robustness, which characterizes the proposed method, makes it particularly suitable for product geometric inspection where high accuracy is required.     

Reactive pulsed laser deposited N–C codoped TiO2 thin films

TiO₂ is a large bandgap chemically stable oxide useful for several applications that involve photo-activated processes, including photocatalysis, photovoltaics, photoelectrolysis, etc. However, the large band gap renders this material not a very efficient absorber of the solar spectrum. Various schemes of cation and anion doping have been utilized that reduce this deficiency to a certain extent. In this paper we present the results of N–C codoping of TiO₂ thin films deposited by a reactive pulsed laser deposition technique. These films were compared for their optical and structural properties with undoped, N doped and C doped TiO₂ films prepared by the same technique. While all samples contained polycrystalline anatase phase, varying N₂ and CH₄ partial pressures resulted in change in TiO₂ lattice parameters due to codoping. X-ray diffraction high-resolution scans show the evidence of C incorporation into TiO₂ lattice by 2θ shift in (101) reflections due to large ionic radius of C. N doping was confirmed by XPS analyses. Direct relationship between oxygen vacancies and doping concentration was established by the deconvolution of XPS peaks. Considerable bandgap reduction occurred that was measured by using UV–vis diffuse reflectance spectroscopy. Results show that reactive pulsed laser deposition is indeed a useful method for the synthesis of codoped TiO₂ thin films as bandgap reduction of ~1.00 eV via N–C codoping was successfully achieved.     

Soft sensor for real-time cement fineness estimation

This paper describes the design and implementation of soft sensors to estimate cement fineness. Soft sensors are mathematical models that use available data to provide real-time information on process variables when the information, for whatever reason, is not available by direct measurement. In this application, soft sensors are used to provide information on process variable normally provided by off-line laboratory tests performed at large time intervals. Cement fineness is one of the crucial parameters that define the quality of produced cement. Providing real-time information on cement fineness using soft sensors can overcome limitations and problems that originate from a lack of information between two laboratory tests. The model inputs were selected from candidate process variables using an information theoretic approach. Models based on multi-layer perceptrons were developed, and their ability to estimate cement fineness of laboratory samples was analyzed. Models that had the best performance, and capacity to adopt changes in the cement grinding circuit were selected to implement soft sensors. Soft sensors were tested using data from a continuous cement production to demonstrate their use in real-time fineness estimation. Their performance was highly satisfactory, and the sensors proved to be capable of providing valuable information on cement grinding circuit performance. After successful off-line tests, soft sensors were implemented and installed in the control room of a cement factory. Results on the site confirm results obtained by tests conducted during soft sensor development.     

Physical characteristics of AFEX-pretreated and densified switchgrass,prairie cord grass,and corn stover

The goal of the study was to evaluate and compare the physical properties of control, pretreated and densified corn stover, switchgrass, and prairie cord grass samples. Ammonia Fiber Expansion (AFEX) pretreated switchgrass, corn stover, and prairie cord grass samples were densified by using the comPAKco device developed by Federal Machine Company of Fargo, ND. The densified biomass were referred as “PAKs” in this study. All feedstocks were ground into three different grind size of 2, 4 and 8 mm prior to AFEX pretreatment and the impact of grinding on pellet properties was studied. The results showed that the physical properties of AFEX-PAKed material were not influenced by the initial grind size of the feedstocks. The bulk density of the AFEX-PAKed biomass increased by 1.2–6 fold as compared to untreated and AFEX-pretreated materials. The durability of the AFEX-PAKed materials were between 78.25 and 95.2%, indicating that the AFEX-PAKed biomass can be transported easily. To understand the effect of storage on the physical properties of these materials, samples were stored in the ambient condition (20 ± 2 °C and 70 ± 5% relative humidity) for six months. After storage, thermal properties of the biomass did not change but glass transition temperature decreased. The water absorption index and water solubility index of AFEX-treated and AFEX-PAKed biomass showed mixed trends after storage. Moisture content decreased and durability increased upon storage.     

Strategic planning optimization for natural gas to liquid transportation fuel (GTL) systems

A strategic planning optimization model is proposed for a network of natural gas to liquids (GTL) systems, and it is solved using a rolling horizon strategy. The model formulation determines the strategic and tactical decisions of the GTL supply chain over a long time horizon. The decisions to build new GTL refineries may be made over the span of 30 years and their operations cover the span of 60 years. Multiple capacities of GTL refineries (i.e., 1, 5, 10, 50, and 200 thousand barrels per day) that produce gasoline, diesel, and kerosene commensurate to the United States demand ratio may exist in the network. The parameter inputs include the locations, availabilities, and prices of natural gas in the United States discretized by county, the delivery locations of fuel products, and the transportation costs of every input and output of the refinery, defined for each time period. Formulated as a large-scale mixed-integer linear optimization (MILP) model, the problem is solved using a rolling horizon strategy for tractability. Case studies on the state of Pennsylvania are presented for different planning schemes and their impact on the economic performance of the GTL network is discussed.     

A mineralogical approach to evaluating laboratory scale acid rock drainage characterisation tests

Effective management of the risks associated with acid rock drainage (ARD) requires the ability to identify material with a potential to generate ARD reliably. With the increasing prevalence of quantitative mineralogy (Quantitative XRD, auto-SEM), opportunity exists to use mineralogy at all stages in ARD characterisation and prediction. This study uses a mineralogical approach across the head grade samples and the residues obtained under leach conditions of several common ARD characterisation tests (Acid Neutralising Capacity, Net Acid Generation), as well as the University of Cape Town (UCT) biokinetic test to evaluate the extent to which acid-neutralising minerals react. The results show the contribution of the carbonates to the acid neutralising capacity, as well as the partial dissolution of intermediate weathering silicate minerals such as chlorite and mica.     

Questioning numerical integration methods for microsphere (and microplane) constitutive equations

In the last few years, more and more complex microsphere models have been proposed to predict the mechanical response of various polymers. Similarly than for microplane models, they consist in deriving a one-dimensional force vs. stretch equation and to integrate it over the unit sphere to obtain a three-dimensional constitutive equation. In this context, the focus of authors is laid on the physics of the one-dimensional relationship, but in most of the case the influence of the integration method on the prediction is not investigated.Here we compare three numerical integration schemes: a classical Gaussian scheme, a method based on a regular geometric meshing of the sphere, and an approach based on spherical harmonics. Depending on the method, the number of integration points may vary from 4 to 983,040! Considering simple quantities, i.e. principal (large) strain invariants, it is shown that the integration method must be carefully chosen. Depending on the quantities retained to described the one-dimensional equation and the required error, the performances of the three methods are discussed. Consequences on stress–strain prediction are illustrated with a directional version of the classical Mooney–Rivlin hyperelastic model. Finally, the paper closes with some advices for the development of new microsphere constitutive equations.