Modelling transport and real-estate values interactions in urban systems

This article presents hedonic Multiple Linear Regression models (MLR), Spatial Auto-Regressive hedonic models (SAR), Spatial autoregressive hedonic in the Error term Models (SEM) and spatial Durbin hedonic Models (SDM) to estimate houses price variations in metropolitan areas as a result of changing environmental and accessibility conditions. The goodness of fit of the different models has been compared along with a series of hypotheses about the performance of the specifications considering spatial relationships between observations. The case study for such analysis was the urban area of Santander (Spain). It has been observed the models which considered spatial dependence between observations offered a greater degree of fit in a scenario showing strong spatial correlation in MLR residuals. The SEM model combined with a Queen-Contiguity matrix provided a good fit to the data and at the same time presented significant parameters with theoretically coherent signs. This model estimated increases of 1.8% for each additional transit line present in the areas of housing, as well as a reduction of 1.1% in their prices for each additional minute in travelling time to the Central Business District. Closeness to the train stations, however, implied reductions in house prices

Modelling the spatial interactions between workplace and residential location

The use of Multinomial Logit (MNL) models specification for the simulation of residential location have been often criticised due to the Independence of Irrelevant Alternatives hypothesis (IIA) which does not allow for the existence of spatial correlation between residential zones. Moreover, it is not clear when and to what extent the influence of the workplace zone and accessibility to employment affect the residential location choices made by households; in other word, whether the residing choice is conditional to the workplace, or vice versa; or if such choices (residence and work place) are joint. In this paper, Nested Logit (NL) and Cross-Nested Logit models of residential location choice are specified and compared to MNL, to investigate the existence of spatial correlation between different locations. Furthermore, different assumptions are tested, considering the choice of residential zone and the joint choice of residential zone and work place zone. The models were estimated for the urban area of Santander (Spain). The results indicate that the inclusion in the model specification, of the spatial correlation between zones fit the data significantly better. Home-work journey times were a statistically significant factor in household location choice, whereas accessibility to employment had the correct sign but it was not statistically significant

Modelling gender perception of quality in interurban bus services

This paper models how women and men perceive the quality of interurban bus services and proposes a new methodology for detecting the highest priority service variables to act on. Service quality perception was modelled using both ordered logit and ordered probit models using data from revealed preference surveys. The methodology for detecting different priority levels uses the graphic representation of the relationships between influence in the model and average evaluation by users. The modification of certain variables increases the knowledge of how woman evaluate quality in bus services to help promote the use of interurban public transport. Statistical analysis of the data provides some conclusions such as: the proportion of users increases as age decreases for both men and women; and women seem to make shorter and more frequent trips than men. The best model for this data set was ordered logit. As expected, the most relevant variable is the relationship between quality and price. Other important variables are the condition of the bus and the frequency of service

On-line tracking of the human gut microbial metabolism: high-throughput screening during colonic in-vitro fermentation

The human gut encloses a large community of bacteria producing a wide range of volatile organic compounds (VOCs) when fermenting undigestible substrates. This study aims to provide a high throughput method to study in real-time the gut microbial volatilome when the microbiota process undigestible dietary substrates. Background: Small metabolites from the human gut microbiota are recognized as the intermediates of the microbiome-host cross-talk [1]. The research on the human gut metabolome is mainly based on discrete sampling representing discontinuous ‘snapshot’ of these complex biological systems [2]. The aim of this research work is to enhance the current understanding of the dynamics of the gut microbiota by integrating non-invasive and continuous analytical methods with in-vitro gut simulators, to monitor in real-time, the progression of small molecules released into the headspace [2,3] Methodology: Automated Head space-Solid Phase Micro Extraction coupled with Gas Chromatography-Mass Spectrometry (HS-SPME-GC-MS) and Static Headspace- Proton Transfer Reaction-Time of Flight-Mass Spectrometry (SHS-PTR-ToF-MS) are used for the purpose of this investigation. The objective is to screen and monitor a specific set of masses of interest, to gain system level mechanistic insights on primary metabolism of the gut microbial consortia. Results: This methodology enabled the continuous monitoring of multiple metabolites in time, including short-chain fatty acids (SCFAs) and medium-chain fatty acids (MCFAs) derived from 24h oat bran fermentation. A mixture of -odd and -even chain acids were co-released into the culture headspace after 4 hours of fermentation and their relative abundance increased in time over 24 hours. The production of multiple MCFAs from the substrate is most likely a community optimization strategy to maximize ATP production from oat degradation by means of reverse beta-oxidation which involves the utilization of fermentation intermediates, such as propanol and acetate. Furthermore, the untargeted screening allowed the detection of low abundant sulfur metabolites, thiophenes, which, to our knowledge, were never investigated before as gut microbial metabolites (GMMs). Conclusion: By integrating non-invasive and continuous analytical methods with an in-vitro gut simulator, it was possible to monitor in real-time the progression of two important class of small molecules released by the microbial consortia into the headspace. The collected information can be jointly integrated to shed light on the dynamics of bacterial foraging of complex undigestible substrates (e.g. bran from cereals). Overall, these results confirm the idea to consider the bacterial headspace as a highly dynamic chemical system that contains information on microbial community behavio

Paying for parking : improving stated-preference surveys

This article describes an experiment which introduced random ranges into the variables used for the design of a stated preference survey and its effects on willingness to pay for parking. User behaviour at the time of parking was modelled to determine their willingness to pay in order to get to their final destination more quickly. Calculating willingness to pay is fundamental during the social and economic assessment of projects. It is important to correctly model how car parks and their users interact in order to get values which represent reality as closely as possible. Willingness to pay is calculated using a stated preference survey and by calibrating multinomial logit models, taking variable tastes into account. It is shown that a value with a low variability can be obtained for willingness to pay by correctly establishing the context of the choice and randomly changing the variables around an average value

Primary diffuse large B-cell lymphoma of the breast: prognostic factors and outcomes of a study by the International Extranodal Lymphoma Study Group

Background: Primary diffuse large B-cell lymphoma (DLBCL) of breast is rare. We aimed to define clinical features, prognostic factors, patterns of failure, and treatment outcomes. Patients and methods: A retrospective international study of 204 eligible patients presenting to the International Extranodal Lymphoma Study Group-affiliated institutions from 1980 to 2003. Results: Median age was 64 years, with 95% of patients presenting with unilateral disease. Median overall survival (OS) was 8.0 years, and median progression-free survival 5.5 years. In multifactor analysis, favourable International Prognostic Index score, anthracycline-containing chemotherapy, and radiotherapy (RT) were significantly associated with longer OS (each P ≤ 0.03). There was no benefit from mastectomy, as opposed to biopsy or lumpectomy only. At a median follow-up time of 5.5 years, 37% of patients had progressed—16% in the same or contralateral breast, 5% in the central nervous system, and 14% in other extranodal sites. Conclusions: The combination of limited surgery, anthracycline-containing chemotherapy, and involved-field RT produced the best outcome in the pre-rituximab era. A prospective trial on the basis of these results should be pursued to confirm these observations and to determine whether the impact of rituximab on the patterns of relapse and outcome parallels that of DLBCL presenting at other site

Synergistic effect of static compliance and d-dimers to predict outcome of patients with covid-19-ards: A prospective multicenter study

The synergic combination of D-dimer (as proxy of thrombotic/vascular injury) and static compliance (as proxy of parenchymal injury) in predicting mortality in COVID-19-ARDS has not been systematically evaluated. The objective is to determine whether the combination of elevated D-dimer and low static compliance can predict mortality in patients with COVID-19-ARDS. A “training sample” (March–June 2020) and a “testing sample” (September 2020–January 2021) of adult patients invasively ventilated for COVID-19-ARDS were collected in nine hospitals. D-dimer and compliance in the first 24 h were recorded. Study outcome was all-cause mortality at 28-days. Cutoffs for D-dimer and compliance were identified by receiver operating characteristic curve analysis. Mutually exclusive groups were selected using classification tree analysis with chi-square automatic interaction detection. Time to death in the resulting groups was estimated with Cox regression adjusted for SOFA, sex, age, PaO2/FiO2 ratio, and sample (training/testing). “Training” and “testing” samples amounted to 347 and 296 patients, respectively. Three groups were identified: D-dimer ≤ 1880 ng/mL (LD); D-dimer > 1880 ng/mL and compliance > 41 mL/cmH2O (LD-HC); D-dimer > 1880 ng/mL and compliance ≤ 41 mL/cmH2O (HD-LC). 28-days mortality progressively increased in the three groups (from 24% to 35% and 57% (training) and from 27% to 39% and 60% (testing), respectively; p < 0.01). Adjusted mortality was significantly higher in HD-LC group compared with LD (HR = 0.479, p < 0.001) and HD-HC (HR = 0.542, p < 0.01); no difference was found between LD and HD-HC. In conclusion, combination of high D-dimer and low static compliance identifies a clinical phenotype with high mortality in COVID-19-ARDS