Image analysis for detecting the transverse profile of worn-out rails

Over its useful life a railway track is subject tomany mechanical and environmental stresses which graduallylead to its deterioration. Monitoring the wear condition of therailway superstructure is one of the key points to guarantee anadequate safety level of the railway transport system; in thisfield, the use of high-efficiency laser techniques has becomeconsolidated and implemented in diagnostic trains (e.g. the“Archimede train” and the “Talete train” ) which allow to detectthe track geometric parameters (gauge, alignment, longitudinallevel, cross level, superelevation defect, etc.) and the state of railwear (vertical, horizontal, 45-degree etc.) with very highaccuracy. The objective of this paper is to describe a new nonconventionalprocedure for detecting the transverse profile ofworn-out rails by means of image-processing technique. Thismethodological approach is based on the analysis of theinformation contained in high-resolution photographic images ofrails and on specific algorithms which allow to obtain the exactgeometric profile and the measurement of the relevant deviationscompared to new rails of the same typology.The analyses and the first results, obtained from laboratoryresearches, concern rails cross sections taken from railway linesunder upgrading. The procedure has shown high precision in thewear evaluation as well as great rapidity in being performed

Resting-State Functional Connectome in Patients with Brain Tumors Before and After Surgical Resection

Purpose: High-grade glioma surgery has evolved around the principal belief that a safe maximal tumor resection improves symptoms, quality of life, and survival. Mapping brain function has been recently improved by resting-state functional magnetic resonance imaging (rest-fMRI), a novel imaging technique that explores networks connectivity at “rest.” Methods: This prospective study analyzed 10 patients with high-grade glioma in whom rest-fMRI connectivity was assessed both in single-subject and in group analysis before and after surgery. Seed-based functional connectivity analysis was performed with CONN toolbox. Network identification focused on 8 major functional connectivity networks. A voxel-wise region of interest (ROI) to ROI correlation map to assess functional connectivity throughout the whole brain was computed from a priori seeds ROI in specific resting-state networks before and after surgical resection in each patient. Results: Reliable topography of all 8 resting-state networks was successfully identified in each participant before surgical resection. Single-subject functional connectivity analysis showed functional disconnection for dorsal attention and salience networks, whereas the language network demonstrated functional connection either in the case of left temporal glioblastoma. Functional connectivity in group analysis showed wide variations of functional connectivity in the default mode, salience, and sensorimotor networks. However, salience and language networks, salience and default mode networks, and salience and sensorimotor networks showed a significant correlation (P uncorrected <0.0025; P false discovery rate <0.077) in comparison before and after surgery confirming non-disconnection of these networks. Conclusions: Resting-state fMRI can reliably detect common functional connectivity networks in patients with glioma and has the potential to anticipate network alterations after surgical resection

Determination of intact parabens in the human plasma of cancer and non-cancer patients using a validated fabric phase sorptive extraction reversed-phase liquid chromatography method with uv detection

Parabens have been widely employed as preservatives since the 1920s for extending the shelf life of foodstuffs, medicines, and daily care products. Given the fact that there are some legitimate concerns related to their potential multiple endocrine-disrupting properties, the development of novel bioanalytical methods for their biomonitoring is crucial. In this study, a fabric phase sorptive extraction reversed-phase liquid chromatography method coupled with UV detection (FPSE-HPLC-UV) was developed and validated for the quantitation of seven parabens in human plasma samples. Chromatographic separation of the seven parabens and p-hydroxybenzoic acid was achieved on a semi-micro Spherisorb ODS1 analytical column under isocratic elution using a mobile phase containing 0.1% (v/v) formic acid and 66% 49 mM ammonium formate aqueous solution in acetonitrile at flow rate 0.25 mL min−1 with a 24-min run time for each sample. The method was linear at a concentration range of 20 to 500 ng mL−1 for the seven parabens under study in human plasma samples. The efficiency of the method was proven with the analysis of 20 human plasma samples collected from women subjected to breast cancer surgery and to reconstructive and aesthetic breast surgery. The highest quantitation rates in human plasma samples from cancerous cases were found for methylparaben and isobutylparaben with average plasma concentrations at 77 and 112.5 ng mL−1 . The high concentration levels detected agree with previous findings for some of the parabens and emphasize the need for further epidemiological research on the possible health effects of the use of these compounds

The Changing Waves of Migration from the Balkans to Turkey: A Historical Account

Ahmet İçduygu and Deniz Sert tell the history of migration from the Balkans to Turkey from the end of the nineteenth century to the present. They relate this history to nation-building, but also to economic conditions and specific Turkish concerns, such as the perceived need for immigration to compensate for a declining population at that time. They also demonstrate that after 1990, ethnic migration decreased and irregular labour migration became more important

708 Common and 2010 rare DISC1 locus variants identified in 1542 subjects:analysis for association with psychiatric disorder and cognitive traits

A balanced t(1;11) translocation that transects the Disrupted in schizophrenia 1 (DISC1) gene shows genome-wide significant linkage for schizophrenia and recurrent major depressive disorder (rMDD) in a single large Scottish family, but genome-wide and exome sequencing-based association studies have not supported a role for DISC1 in psychiatric illness. To explore DISC1 in more detail, we sequenced 528 kb of the DISC1 locus in 653 cases and 889 controls. We report 2718 validated single-nucleotide polymorphisms (SNPs) of which 2010 have a minor allele frequency of <1%. Only 38% of these variants are reported in the 1000 Genomes Project European subset. This suggests that many DISC1 SNPs remain undiscovered and are essentially private. Rare coding variants identified exclusively in patients were found in likely functional protein domains. Significant region-wide association was observed between rs16856199 and rMDD (P=0.026, unadjusted P=6.3 × 10-5, OR=3.48). This was not replicated in additional recurrent major depression samples (replication P=0.11). Combined analysis of both the original and replication set supported the original association (P=0.0058, OR=1.46). Evidence for segregation of this variant with disease in families was limited to those of rMDD individuals referred from primary care. Burden analysis for coding and non-coding variants gave nominal associations with diagnosis and measures of mood and cognition. Together, these observations are likely to generalise to other candidate genes for major mental illness and may thus provide guidelines for the design of future studies. © 2014 Macmillan Publishers Limited

A New High-Efficiency Procedure for Aggregate Gradation Determination of the Railway Ballast by Means Image Recognition Method

The mechanical characteristics of the railway superstructure are related to the properties of the ballast, and especially to the particle size distribution of its grains. Under the constant stress-strain of carriages, the ballast can deteriorate over time, and consequently it should properly be monitored for safety reasons. The equipment which currently monitors the railway superstructure (like the Italian diagnostic train Archimede) do not make any “quantitative” evaluation of the ballast. The aim of this paper is therefore to propose a new methodology for extracting railway ballast particle size distribution by means of the image processing technique. The procedure has been tested on a regularly operating Italian railway line and the results have been compared with those obtained from laboratory experiments, thus assessing how effective is the methodology which could potentially be implemented also in diagnostic trains in the near future

A new high-efficiency procedure for aggregate gradation determination of the railway ballast by means image recognition method

The mechanical characteristics of the railway superstructure are related to the properties of the ballast, and especially to the particle size distribution of its grains. Under the constant stress-strain of carriages, the ballast can deteriorate over time, and consequently it should properly be monitored for safety reasons. The equipment which currently monitors the railway superstructure (like the Italian diagnostic train Archimede) do not make any “quantitative” evaluation of the ballast. The aim of this paper is therefore to propose a new methodology for extracting railway ballast particle size distribution by means of the image processing technique. The procedure has been tested on a regularly operating Italian railway line and the results have been compared with those obtained from laboratory experiments, thus assessing how effective is the methodology which could potentially be implemented also in diagnostic trains in the near future