Spatial interaction modeling of interregional commodity flows

Drawing from both the spatial price equilibrium theoretical framework and the empirical literature on spatial interaction modeling, this paper expands models of interregional commodity flows (CFs) by incorporating new variables and using a flexible Box-Cox functional form. The 1993 US commodity flows survey provides the empirical basis for estimating state-to-state flow models for 16 commodity groups over the 48 continental US states. The optimized Box-Cox specification proves to be superior to the multiplicative one in all cases, while selected variables provide new insights into the determinants of state-to-state CFs

An Analysis of Vehicular Traffic Flow Using Langevin Equation

Traffic flow data are stochastic in nature, and an abundance of literature exists thereof. One way to express stochastic data is the Langevin equation. Langevin equation consists of two parts. The first part is known as the deterministic drift term, the other as the stochastic diffusion term. Langevin equation does not only help derive the deterministic and random terms of the selected portion of the city of Istanbul traffic empirically, but also sheds light on the underlying dynamics of the flow. Drift diagrams have shown that slow lane tends to get congested faster when vehicle speeds attain a value of 25 km/h, and it is 20 km/h for the fast lane. Three or four distinct regimes may be discriminated again from the drift diagrams; congested, intermediate, and free-flow regimes. At places, even the intermediate regime may be divided in two, often with readiness to congestion. This has revealed the fact that for the selected portion of the highway, there are two main states of flow, namely, congestion and free-flow, with an intermediate state where the noise-driven traffic flow forces the flow into either of the distinct regimes

Detection of Novel NF1 Variants with Next-Generation DNA Sequencing Technology and Genotype-Phenotype Characteristics of Neurofibromatosis

MakaleWOS:000925992500001Objective: Neurofibromatosis type 1 (NF1, #162200) is a common neurological disorder with de novo or inherited germline mutations of the Neurofibromin (NF1, *613113). The purpose of this study is to increase the limited knowledge of NF1 in a small population-based dataset. Materials and Methods: This study enrolled patients with clinically suspected NF1 referred to the Kayseri Training and Research Hospital, Medical Genetics Department, between 2015 and 2017. The local ethics committee approved this study. Next-generation sequencing was performed for the genetic analysis. The genetic, demographic, and clinical features of the participants were characterized. Results: A total of 79 cases of NF1 were included. Of these cases, 40 were male, and 39 were female. The mean age was 11.9 years, and most were younger than 18 years. The most common complaint was cafe au lait macules. The 61 (77.3%) patients had pathogenic variants, and 16 (26.2%) were novel. Mostly affected mutation sites were exonic regions (n=54, 88.5%). The most common mutated exon was exon 38 (n=7, 11.5%), and most of the detected mutations were nonsense mutations (31%). Conclusion: It is one of Turkiye's largest NF1 study groups, where all exons of the NF1 gene were analyzed. This study contributes novel variants to the literature. There was no mutational hotspot region, and no significant relationship between genotype and phenotype was observed. Further studies and large sample sizes are required to better understand the relationship between NF and genetic changes

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Sample size needed for calibrating trip distribution and behavior of the gravity model

Conventional calibration algorithms of trip distribution models assume that the analyst has a whole base year trip matrix. To attain a whole trip matrix, the sample size for travel surveys needed to be as large as possible. However, this could be very expensive especially in large cities. Some studies in the past showed a small sized sample would be enough to estimate functional parameters of observed trip length frequency distribution. But the performance of a gravity model with small sized samples has never been addressed. This empirical study has shown that sample sizes as small as 1000 (even smaller for quick response studies) could be as dependable as large sample surveys using a line search calibration algorithm. © 2009 Elsevier Ltd. All rights reserved

Modeling freight distribution using artificial neural networks

Studies about freight distribution modeling are limited due to the limitations in data availability. Existing studies in this subject, generally either use the conventional gravity models or the regression based models as modeling techniques. The present study, using the 1993 US Commodity Flow Survey Data, models inter-regional commodity flows for 48 continental states of the US with three different artificial neural networks (ANN). The results are compared with those of Celik and Guldmann's (2002) Box-Cox Regression Model. The ANN using conventional gravity model variables provides a slight improvement with respect to this Box-Cox model. However, the ANNs using theoretically relevant variables provide surprising improvements in comparison to the Box-Cox model. It is concluded that ANN architecture is a very promising technique for predicting short-term inter-regional commodity flows

Forecasting interregional commodity flows using artificial neural networks: An evaluation

Previous studies have concluded that the use of artificial neural networks (ANNs) is a promising new technique for modelling freight distribution, supporting, the findings of other studies in the area of spatial interaction modelling. However, the forecasting performance of ANNs is still under investigation. This study tests the predictive performance of the ANN Model with respect to a Box-Cox spatial interaction model. It is concluded that the Box-Cox model outperforms ANN in forecasting interregional commodity flows even if ANN had proven calibration superiority in comparison to conventional gravity type models

Determination of optimum environmental conservation: Using multi-criteria decision-making techniques

The type and degree of conservation areas in Turkey legally dictate the kind of land uses that can and cannot take place in a conservation area. Thus, the conservation scheme is one of the most important criteria in designing an urban land-use plan. The aim of this study is to analyse the effects of various conservation decisions on land-use allocation holding everything else constant. This study uses a land-allocation mathematical programme formulated by Hanink and Cromley [(1998) Land-use allocation in the absence of complete market values, Journal of Regional Science, 38, pp. 465-480] that integrates the geographical information systems with a generalized assignment problem to determine an optimum level of conservation scheme in Cesme/Izmir, a coastal resort in Turkey. The findings state that the proposed technique is indeed very useful and promising to answer diversified practical issues on a more rational basis

The impact of rail transit investment on the residential property values in developing countries: The case of Izmir Subway, Turkey

Purpose The purpose of this paper is to test whether the rail transit investment in Izmir, Turkey has had positive valuation impacts on the surrounding residential properties, and to estimate the value of travel time using relevant parameters. Design/methodology/approach The necessary data were collected via a survey including all real-estate agents in the area. To test the research question, the Hedonic Price Model (HPM) is used as the research technique. The obtained parameters are also used to estimate the value of travel time. Findings The findings of the models has indicated that the proximity to rail stations was valued at $250-300 per meters, and the value of travel per hour was$1.47-1.83 on average. Research limitations/implications These findings should be checked with more consistent database using transaction process, and the mortgage loan rate which was not legislated at the time of study. Practical implications Until a mortgage loan rate is registered in turkey, the estimated parameters can be used in the cost-benefit analysis of rail transit investments in Turkey. Originality/value The theoretical premise that “any improvement in accessibility will be capitalized into the land values” is tested one more time in a developing country case whose urban environment is substantially different from those of the developed world, especially the North American cities. Furthermore, a new methodology using the HPM parameters is also suggested to estimate the value of travel time

Modelling trip distribution with fuzzy and genetic fuzzy systems

This paper explores the potential capabilities of fuzzy and genetic fuzzy system approaches in urban trip distribution modelling with some new features. First, a simple fuzzy rule-based system (FRBS) and a novel genetic fuzzy rule-based system [GFRBS: a fuzzy system improved by a knowledge base learning process with genetic algorithms (GAs)] are designed to model intra-city passenger flows for Istanbul. Subsequently, their accuracy, applicability and generalizability characteristics are evaluated against the well-known gravity- and neural network (NN)-based trip distribution models. The overall results show that: traditional doubly constrained gravity models are still simple and efficient; NNs may not show expected performance when they are forced to satisfy trip constraints; simply-designed FRBSs, learning from observations and expertise, are both efficient and interpretable even if the data are large and noisy; and use of GAs in fuzzy rule-based learning considerably increases modelling performance, although it brings additional computation cost