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•Panel mixed-logit mode choice model captures flexible transit potential in adverse weather.•Baby boomers have high propensity for traditional transit, but shift to auto in bad weather.•Bike commuters like flexible transit, though in bad weather shift to the car mode.•Millennials have higher propensity to choose flexible transit in winter.•Millennials have higher propensity for flexible transit and lower propensity for car in the winter, relative to the summer.•Transit agencies should target resources to create weather-protective transit facilities.

ABSTRACTLocation-based social networking data provide an important new dimension in understanding travel choice behaviour, providing high levels of location and time accuracy over long time frames in conjunction with explicit friendship network information. Such data allow examination of location choice dynamics and social networking aspects explicitly. This paper presents an exploration of social network based dynamics of choice set generation in the context of activity and travel choice behaviour, especially destination choice. Using data from an online location-based social network, the paper explores the spatiality of destinations and social network influence on travellers’ destination choice in the Chicago metropolitan area. The results show that social relationships play a role in travellers’ destination choices and that distance plays a strong role in social networks as in location choice. Connectivity through social network structure is examined jointly with individuals’ spatial activity engagement; the number of virtual friends is found to significantly influence actual physical travel behaviour. Finally, caveats in using social networking data for behaviour analysis and planning are discussed.

The article discusses the vibrating sound of grey-winged trumpeter and their habitat Weltvogelpark Walsrode which is a bird park located in North Germany.

To forecast the impact of congestion pricing schemes, it is essential to capture user responses to these schemes and the resulting dynamics of traffic flow on the network. The responses of users must include route, departure time, and mode choices. To capture the effects of these decisions, this paper lays out a framework for the integration of the relevant elements of an activity-based model (ABM) with a dynamic traffic assignment (DTA) model and a simulation framework to support the analysis and evaluation of various pricing schemes. In this paper, a multicriterion dynamic user equilibrium traffic assignment model is used; the model explicitly considers heterogeneous users who seek to minimize travel time, out-of-pocket cost, and travel time reliability in the underlying route choice framework. In addition to the methodological developments, various demand and supply parameters are estimated and calibrated for the selected application network (the Greater Chicago, Illinois, network). This paper showcases the integration of ABM components and a DTA in one coherent modeling framework for the implementation and evaluation of congestion pricing in an actual large-scale network.

Whether crime or the perception of it has any direct and significant influence on travelers’ mode choice is a topic for which the evidence remains inconclusive. Studies have revealed various, and in some cases counterintuitive, roles that safety concerns can play in individuals’ travel behavior. In addition, characteristics of the physical environment such as land use and walkability are also influential factors in travelers’ decisions. This study explored these questions through the study of individual travel behavior by using discrete choice models applied to the reported home-based work trips in the Chicago household travel survey. Mode choice was modeled as functions of variables such as sociodemographics, neighborhood crime density (as a safety measure), and walk score (as a measure of walkability). Different crime types were examined, and a crime index was introduced. Results suggest that both walk score and the crime index at the destination can be considered meaningful predictors of individuals’ mode usage. The crime index at origin, however, does not show a significant and meaningful effect.

Travelers’ mode choice behavior with the presence of high-quality smartphone-delivered multimodal information (SMMI) has rarely been addressed. This study investigated commuters’ en route decisions about switching from automobile to park-and-ride; high-quality SMMI about current level of service was provided. A stated preference survey was conducted in Shanghai, China, and the data from that survey were analyzed through a panel mixed logit model. The model accounted for the variations in individuals’ preferences regarding travel time and correlations between repeated choices of the same individual. Modeling results showed that SMMI had significant effects on commuters’ mode choice behavior and that the effects depended on gender, age, income, and education. The results revealed a high but plausible value of time (VOT). SMMI was evaluated by the users and compared with their previous experiences. This result was particularly obvious for respondents who were least likely to switch and were experienced drivers, accessed dynamic traffic information regularly, and would have been more likely to switch if an auto delay is nonrecurrent. There was also a strong inertia impact; people who were not familiar with park-and-ride would have been less likely to switch from driving to park-and-ride. Travel time was highly valued for commute trips, as revealed by the high VOT and high percentage of respondents whose major criterion for mode choice is travel time. There was a high willingness to pay for an improved service of rail transit; this willingness was reflected by the significant explanatory variable “comfort level of rail transit.”

A model of a social network-based attitude diffusion system in the context of activity and travel choice behavior is presented. The principal mechanisms contributing to attitude formation were identified, and mathematical models to capture these processes were developed. The primary contributions of this research are (a) the modeling of attitude diffusion according to social and learning mechanisms and (b) the evolution of these attitudes over time in a lattice neighborhood social network. The agent-based framework presented is sufficiently general and flexible to allow the building of a more complete representation of information diffusion and attitude formation within activity and travel behavior choice dimensions, for example, mode choice or departure time choice. The framework allows the extension of the presented approach with additional social network structures, information sources, and social interaction mechanisms in the physical and virtual realms or the extension and modification of the presented approach to simulate the impact of information-based management strategies.

The main goal of the study was to integrate demand models into weather-responsive network traffic estimation and prediction system methodologies. The study examined the behavioral responses of travelers along several dimensions in response to weather-related transportation management strategies in conjunction with active travel demand management strategies before and during severe weather events. Specific management interventions included pretrip, information-based mode, and departure time choice adjustments, as well as policy-based rescheduling of school hours. The paper presents a case study of the Chicago, Illinois, area network under snow conditions to assess the effect of a combination of demand management strategies to maintain the same level of network performance as under clear weather conditions. A combination of earlier dissemination of information and school-opening policy resulted in a similar level of network performance maintained under a median snow day as compared with a clear weather day. The paper presents integrated supply and demand models for simulation and an assessment of demand management strategies in conjunction with weather-related congestion.

Pricing shipments and sourcing capacity for a third-party logistics (3PL) provider operating in a spot market requires real-time decision making that is ripe for computer-based support driven by analytics. A decision support system outlined here leverages the 3PL provider's historical shipment data along with its knowledge of both sides of the shipping process to increase profits and to better perform the pricing and sourcing tasks. At the core of the system are discrete choice models for shippers and carriers along with a profit maximization model. The discrete choice models predict the acceptance or rejection of an offer for a shipment to shippers and a bid for capacity to carriers. The profit maximization model determines the shipper price that maximizes the 3PL provider's expected profit. In addition to those models are procedures for determining a list of potential carriers for an incoming shipment and also for ranking those carriers. As its main outputs, the system produces a shipper price and a ranked carrier list. The system is applied to real-world data provided by a 3PL company, with excellent results. The system is able to produce competitive yet profitable prices and to select potential carriers that would increase the 3PL provider's profits.

The aim of a new survey project is to collect data on the link between leisure contacts and leisure activities. The paper introduces briefly into former studies that applied the methods of social network analysis in transport planning. Using these projects as starting points the methodology and background of the new project are presented in detail. This is followed by first descriptive analyses checking how representative the data are for the Swiss population. The paper finishes by giving an outlook on further work and next steps to analyze the data.

Empty capsids from adenovirus, that is, virus particles lacking DNA, are well documented in the published literature. They can be separated from complete virus by CsCl density gradient centrifugation. Here we characterize the presence of empty capsids in recombinant adenovirus preparations purified by column chromatography. The initial purified recombinant adenovirus containing the p53 tumor suppressor gene was produced from 293 cells grown on microcarriers and purified by passage through DEAE-Fractogel and gel-filtration chromatography. Further sequential purification of the column-purified virus by CsCl and glycerol density gradient centrifugations yielded isolated complete virus and empty capsids. The empty capsids were essentially noninfectious and free of DNA. Analysis of empty capsids by SDS-PAGE or RP-HPLC showed the presence of only three major components: hexon, IIIa, and a 31K band. This last protein was identified as the precursor to protein VIII (pVIII) by mass spectrometric analysis. No pVIII was detected from the purified complete virus. Analysis by electron microscopy of the empty capsids showed particles with small defects. The amount of pVIII was used to determine the level of empty capsid contamination. First, the purified empty capsids were used to quantify the relation of pVIII to empty capsid particle concentration (as estimated by either light scattering or hexon content). They were then used as a standard to establish the empty capsid concentration of various recombinant adenovirus preparations. Preliminary research showed changes in empty capsid concentration with variations in the infection conditions. While virus purification on anion-exchange or gel-filtration chromatography has little effect on empty capsid contamination, other chromatographic steps can substantially reduce the final concentration of empty capsids in column-purified adenovirus preparations.

The objectives of the study were to calculate the costs of postoperative complications and to evaluate whether the use of perioperative enteral immunonutrition, may lead to a saving in health care resources consumed. The economic analysis was based on data from a randomized doubleblind trial that include 206 cancer patients who received perioperatively either enteral immunonutrition treatment group, n 102 or a standard enteral diet control group, n 104. Estimates of costs were based on resource use for treatment of complications, which were valued according to the National List of Sanitary Costs of the Italian Ministry of Health and on the medical DiagnosisRelatedGroup DRG reimbursement rates. Costs of nutrition were also calculated. Cost comparison and cost effectiveness analyses were then carried out. Intenttotreat analysis showed that the total costs of 52 postoperative complications were 322,218 euros, with a consumption of the DRG reimbursement rate of 15.4. The costs of nutrition were 35,437 euros in the treatment group versus 10,768 euros in the control group. The total costs nutrition plus treating complications amounted to 113,778 euros in the treatment group versus 254,450 euros in the control group. The mean total costs per patient were 1,115 euros in the treatment group versus 2,447 euros in the control group P0.04. Effectiveness was 83.3 in the treatment group versus 68.3 in the control group P0.009. Cost effectiveness analysis showed a net saving of 2,386 euros per complicationfree patient in favor of the treatment group. In conclusion, the perioperative use of immunonutrition appears cost effective due to a substantial saving of resources used to treat postoperative complications.

Current standard second-line regimens for the treatment of non-Hodgkin's lymphoma (NHL) are administered over a period of 3–6 months, generating substantial treatment costs. In Switzerland, Yttrium-90 (90Y)-ibritumomab tiuxetan was introduced in 2004 as the first-in-class radioimmunotherapy for the treatment of relapsed or refractory indolent NHL. It is delivered in an outpatient setting over a period of 8 days. In Switzerland, just as in the United States, assessment of the biodistribution of the antibody is required one week prior to the actual treatment (this step is not required in the European Union). This analysis compared the costs of 90Y-ibritumomab tiuxetan with 8 cycles of rituximab (R), 6 or 8 cycles of R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, prednisolone), and 6 or 8 cycles of R-CVP (rituximab, cyclophosphamide, vincristine, prednisolone), respectively. Direct medical treatment costs and costs of absence from work (indirect costs) were included. For each treatment option, the number of cycles per treatment and the total medical resources used to care for the patient throughout the treatment were assessed for a theoretical standard patient, defined as 60 years old with therapy refractory, grade 1–2, stage III-IV NHL. The resources used were valued with unit costs or prices gained from the Swiss national fee schedule for medical services, lists of administered prices for laboratory tests and pharmaceuticals, and purchasing prices for all other relevant items. Total lost productivity due to absence from work was estimated by multiplying the days absent from work with average income per day. Results are summarized in Table 1. Direct treatment costs for 90Y-ibritumomab tiuxetan were lower than 8 x R, 8 x R-CHOP, and 8 x R-CVP but higher than 6 x R-CHOP or 6 x R-CVP. When indirect costs were taken into account, total 90Y-ibritumomab tiuxetan cost was lower than for all other regimens except 6 x R-CVP. The only sensitivity analysis that changed the ranking of the treatment options was omitting the biodistribution study and thus adopting the EU regimen for 90Y-ibritumomab tiuxetan. This reduced the costs of radioimmunotherapy to CHF 27,766. In conclusion, 90Y-ibritumomab tiuxetan is not more expensive than other established treatments for relapsed or refractory indolent NHL. Table 1. Per-patient costs by treatment in Switzerland.

Hair samples of psychiatric patients were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS-MS) for the neuroleptics clozapine, flupentixol, haloperidol, penfluridol, thioridazine, and zuclopenthixol. In the study, these neuroleptics were administered to the patients regularly for a minimum of six months. Sample preparation was performed by washing, powdering with a ball mill, extraction of drugs from hair by ultrasonication with methanol, cleanup by solid-phase extraction and subsequent LC-MS-MS analysis using multiple reaction monitoring (MRM). Calibration was performed for all drugs in the range of 0.05 to 10 ng/mg using spiked hair powder and doxepin-d3 as internal standard. Twenty to 50 mg of hair powder was used and the detection limits of LC-MS-MS were below 0.05 ng/mg for all drugs tested. Therapeutic dosage, number of subjects, hair color, and detected amounts of drugs were as follows: dozapine (150–400 mg/day; n = 3, light brown, medium brown, black; 0.47–0.92 ng/mg), haloperidol (150 mg/3 weeks; n = 1, black/gray; 12.2 ng/mg), penfluridol (20–30 mg/week; n = 2, medium brown, black; 0.08 ng/mg; not detected in one case), thioridazine (100–400 mg/day; n = 4, light brown, medium brown, black; 0.33–9.91 ng/mg, not detected in one case). Besides the active drugs also the desmethyl-metabolites of clozapine and thioridazine were detected by LC-MS-MS. However, flupentixol (5 mg/day; light brown hair) and zuclopenthixol (350 mg/3 weeks; light brown hair) were not detected by these methods in one case each, although the drugs were administered regularly to these patients. The comparison of dosage and hair color in two cases with thioridazine and penfluridol suggests that other interindividual factors may have an influence on drug concentration in hair.