20 research outputs found
Small-scale evaporation tests on clay: influence of drying rate on clayey soil layer
No full textCracks in drying soils have detrimental effects on the integrity of geotechnical structures. The evaporation rate is recognized to play an important role in fracture generation, having a direct impact on the amount of cracks produced. This investigation examined the drying behaviour of a clay with different initial water contents and under different evaporative conditions. Small-scale evaporation experiments were carried out using a river clay and commercially available suction-measuring equipment. The results showed that the initial conditions have great influence on the drying performance of a soil, which can be partly attributed to the influence of the surface texture and the pore structure. It was observed that under certain circumstances, the evaporation of a soil surface can be higher than that of open water. The different evaporation rates had a marked effect on the water distributions with depth within the soil. The evaporation rate also produced a dynamic response of the soil-water retention curve
Modelling desiccation cracking in a homogenous soil clay layer: comparison between different hypotheses on constitutive behaviour
No full textDesiccation cracks are usually thought to start from the surface of an evaporating soil layer, and the available simplified models for crack initiation and propagation are based on this hypothesis. On the contrary, experimental results on a Dutch river clay showed that cracks in an evaporating soil layer may start and propagate below the surface, confirming earlier findings by other researchers. A simple one-dimensional model was set up to analyse the consequences of different hypotheses about the material behaviour on the crack onset in a homogenous soil layer undergoing surface drying. The results of the model show that dependence of the material behaviour on the rate of water content change is a necessary requirement for cracks to initiate below the surface. The conclusion suggests that, to properly understand cracking in an evaporating soil layer, an intrinsic time scale for the mechanical response must be accounted for, among all the other factors which were previously highlighted by other researchers. The key factor to predict crack onset below the surface is the dependence of the drying branch of the water retention curve of the compressible soil on the rate of drying, which would be justified by a rate dependent fabric evolution
Modelling desiccation cracking in a homogenous soil clay layer: comparison between different hypotheses on constitutive behaviour
No full textDesiccation cracks are usually thought to start from the surface of an evaporating soil layer, and the available simplified models for crack initiation and propagation are based on this hypothesis. On the contrary, experimental results on a Dutch river clay showed that cracks in an evaporating soil layer may start and propagate below the surface, confirming earlier findings by other researchers. A simple one-dimensional model was set up to analyse the consequences of different hypotheses about the material behaviour on the crack onset in a homogenous soil layer undergoing surface drying. The results of the model show that dependence of the material behaviour on the rate of water content change is a necessary requirement for cracks to initiate below the surface. The conclusion suggests that, to properly understand cracking in an evaporating soil layer, an intrinsic time scale for the mechanical response must be accounted for, among all the other factors which were previously highlighted by other researchers. The key factor to predict crack onset below the surface is the dependence of the drying branch of the water retention curve of the compressible soil on the rate of drying, which would be justified by a rate dependent fabric evolution
Specific genomic aberrations in primary colorectal cancer are associated with liver metastases
No full textBackground: Accurate staging of colorectal cancer (CRC) with clinicopathological parameters is important for predicting prognosis and guiding treatment but provides no information about organ site of metastases. Patterns of genomic aberrations in primary colorectal tumors may reveal a chromosomal signature for organ specific metastases. Methods: Array Comparative Genomic Hybridization (aCGH) was employed to asses DNA copy number changes in primary colorectal tumors of three distinctive patient groups. This included formalin-fixed, paraffin-embedded tissue of patients who developed liver metastases (LM; n = 36), metastases (PM; n = 37) and a group that remained metastases-free (M0; n = 25). A novel statistical method for identifying recurrent copy number changes, KC-SMART, was used to find specific locations of genomic aberrations specific for various groups. We created a classifier for organ specific metastases based on the aCGH data using Prediction Analysis for Microarrays (PAM). Results: Specifically in the tumors of primary CRC patients who subsequently developed liver metastasis, KC-SMART analysis identified genomic aberrations on chromosome 20q. LM-PAM, a shrunken centroids classifier for liver metastases occurrence, was able to distinguish the LM group from the other groups (M0&PM) with 80% accuracy (78% sensitivity and 86% specificity). The classification is predominantly based on chromosome 20q aberrations. Conclusion: Liver specific CRC metastases may be predicted with a high accuracy based on specific genomic aberrations in the primary CRC tumor. The ability to predict the site of metastases is important for improvement of personalized patient management.MediamaticsElectrical Engineering, Mathematics and Computer Scienc
RivierEnLand
No full textHet gangbare veiligheidsconcept, van dijken en waterkerende kunstwerken in Rivierenland, biedt ons op langere termijn geen “gegarandeerde” veiligheid. In dit rapport wordt een beeld geschetst van het Rivierenland zoals dat zich als “natuurlijk systeem” zal ontwikkelen in de komende 500 jaar. Het rapport is onderverdeeld in drie stukken; dit zijn inleiding, onderzoeken en conclusies. In de onderzoeken kan verder onderscheid gemaakt worden tussen verschijnselen die te maken hebben met rivieren in het algemeen, het modelleren van het Rivierenland en de problematieken die zich in het gebied voor kunnen gaan doen. Om een voorspelling te doen over een tijdsbestek van 500 jaar is het nodig te kijken naar een verleden zonder ingrepen. Er moet dus worden beschouwd, wat er voor het jaar 1000 n Chr. is gebeurd met de rivieren. Uit gegevens volgt dat rivieren zich in 1.000 jaar 20 tot 25 kilometer hebben verlegd. De rivieren gaan bij voorkeur daarbij morfologisch gezien hun loop verleggen in zuidelijke richting. Om praktische redenen is er voor gekozen om de waterstanden in het rivierengebied te benaderen in het KENQUA-model. Dit is gebaseerd op het “knikker-model”. Dit houdt in dat een bepaalde massa zich naar beneden beweegt. Met het model kan gesimuleerd worden welke delen van een gebied vollopen wanneer een bepaalde waterstand als beginvoorwaarde wordt aangenomen. Met de resultaten van het model zijn inundatiekaarten bepaald voor debieten met frequenties van 1/10, 1/100, 1/1.000, 1/10.000 per jaar. Bij het inrichten of herinrichten van het Rivierenland tracht men tot een zodanige kartering te komen van de bodem dat met behulp van de nieuwe bodemkaarten uitspraken kunnen worden gedaan betreffende het toekomstige landgebruik. Er zijn eisen gedefinieerd die in de toekomst worden gesteld aan het nieuwe rivierengebied, dan kan men mede aan de hand van een geschikte bodemkaart nagaan waar een bepaald landgebruik met succes is toe te passen. De verwachte veranderingen in het klimaat van Nederland en de stroomgebieden van de grote rivieren zullen leiden tot een grotere dynamiek in de riviersystemen dan tot nu toe gebruikelijk. Dit impliceert het veelvuldiger optreden van lage rivierafvoeren in de zomerperiode en het frequenter voorkomen van hoogwaters gedurende het winterhalfjaar. Ook zullen deze extremen langer duren. Het risico van (zeer) hoge grond- en oppervlaktewaterstanden bij extreme weersomstandigheden kan worden vergroot door verminderde afvoermogelijkheden ten gevolge van hoge buitenwaterstanden. Deze situatie kan zich zowel voordoen bij vrije lozing op zee als bij bemaling op buitenwater (rivieren, IJsselmeer). In verzilting van de bodem moet een onderscheid gemaakt worden tussen indringing van zeewater in de bodem en het omhoog komen van zout grondwater uit zeer oude bodemlagen. Bij de eerste zou mogelijk sprake kunnen zijn van een grote afhankelijkheid m.b.t. zeespiegelstijging, de tweede wordt vooral een probleem bij het oppompen van grondwater. In een langdurig extreme situatie zal zout water van een lage concentratie de Alblasserwaard bereiken. Het omhoog komen van zout grondwater in het meer oostelijk deel van Nederland zal alleen lokaal voorkomen, bij het onttrekken van forse debieten zoet grondwater. Over de exacte oorzaak van de zeespiegelstijging zijn de geleerden het nog niet geheel eens. Dit wil zeggen dat de oorzaak gezocht moet worden in een samenspel tussen verschillende factoren. Hoe zwaar iedere factor individueel meeweegt in het veroorzaken van de zeespiegelstijging is een lastige kwestie. Er is echter één oorzaak waarover iedereen het unaniem eens is, tevens de grootste oorzaak: het broeikaseffect. Doordat de bodem ook nog eens daalt is de zeespiegelstijging ten opzichte van het land groot. De gemiddelde schatting van deze relatieve stijging bedraagt ongeveer 2,5 meter in de komende 500 jaar. In vijfhonderd jaar zal de zeespiegel stijgen en het extreme minimumdebiet van de grote rivieren Rijn en Maas dalen. Met behulp van een ZoutSim model in het programma STELLA is onderzocht welke gevolgen deze veranderingen hebben op de zoutindringing. Er is uitgerekend dat de indringing van de zouttong in de orde van 10 kilometer op de Oude Maas bedraagt. Op de Nieuwe Maas zal dit ongeveer 20 kilometer zijn. Voor de drinkwaterinlaten in de Biesbos zal de voortschrijding van de zouttong geen probleem zijn. Op de Oude Maas bereikt de zouttong nooit de 60 kilometer verder liggende drinkwaterinlatenHydraulic EngineeringCivil Engineering and Geoscience
Investigating the impact of NHS based ovarian cancer screening
No full textthe UK ovarian cancer is the fifth most common cancer in females and after uterine cancer, the second most common gynaecological cancer. There were 6,596 new cases diagnosed in the UK in 2006. The majority of women who develop ovarian cancer have few symptoms until the cancer has spread. A systematic review of published literature was performed to include randomised control trials, case control or cohort studies. It is apparent from the literature on ovarian cancer screening that internationally extensive research is performed however, there is lack of consensus on who to offer screening to, and the most efficacious way of offering it. Annual screening was found to be inadequate for early cancer detection as several studies report advanced stage disease or found that women were developing symptoms in the interim period of screening visits.
The retrospective studies performed at Milton Keynes Hospital demonstrated that ovarian cancer affects a wide age range with many women having no family history of ovarian or breast cancer. Many cases were found to have early stage ovarian cancer however, the largest group of women were found to have extensive metastatic disease at time of diagnosis. 80% of cases reviewed experienced abdominal or pelvic pains often with distension. Five patients were found to have a CA125 value in the normal range, one of which had advanced disease, indicating the limitations of this biomarker. The impact and costs associated with screening in the NHS setting vary considerably with inclusion criteria used. The UK National Screening Committee will have to decide once the findings of UKCTOCS are published in 2010/11 as to the cost benefit of offering NHS based ovarian cancer screening. An annual cost of at least £1.3 million should be expected per NHS trust, in addition to individual trusts needs for equipment, staff and additional facilities required to offer such screening
MDM2 Promoter SNP344T>A (rs1196333) Status Does Not Affect Cancer Risk
No full textThe MDM2 proto-oncogene plays a key role in central cellular processes like growth control and apoptosis, and the gene locus is frequently amplified in sarcomas. Two polymorphisms located in the MDM2 promoter P2 have been shown to affect cancer risk. One of these polymorphisms (SNP309T>G; rs2279744) facilitates Sp1 transcription factor binding to the promoter and is associated with increased cancer risk. In contrast, SNP285G>C (rs117039649), located 24 bp upstream of rs2279744, and in complete linkage disequilibrium with the SNP309G allele, reduces Sp1 recruitment and lowers cancer risk. Thus, fine tuning of MDM2 expression has proven to be of significant importance with respect to tumorigenesis. We assessed the potential functional effects of a third MDM2 promoter P2 polymorphism (SNP344T>A; rs1196333) located on the SNP309T allele. While in silico analyses indicated SNP344A to modulate TFAP2A, SPIB and AP1 transcription factor binding, we found no effect of SNP344 status on MDM2 expression levels. Assessing the frequency of SNP344A in healthy Caucasians (n = 2,954) and patients suffering from ovarian (n = 1,927), breast (n = 1,271), endometrial (n = 895) or prostatic cancer (n = 641), we detected no significant difference in the distribution of this polymorphism between any of these cancer forms and healthy controls (6.1% in healthy controls, and 4.9%, 5.0%, 5.4% and 7.2% in the cancer groups, respectively). In conclusion, our findings provide no evidence indicating that SNP344A may affect MDM2 transcription or cancer risk.© 2012 Knappskog et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Scatterplot representation of marker discovery process and ROC curves.
No full text<p>A (top figure: HM27, bottom figure: HM450), scatterplots of the highest PBL β-value (β-PBL<sub>H</sub>) of 10 (HM27) and 2 (HM450) healthy control samples (X-axis) against the associated 10th percentile of CRC tumor β-values (β-CRC<sub>10</sub>) on the Y-axis. The blue dots represent the eliminated probes (HM27: n = 23,049; HM450: n = 367,833) and the red dots (HM27: n = 695; HM450: n = 30,207) represent the retained probes with a β-CRC<sub>10</sub>>β-PBL<sub>H</sub> or a β-PBL<sub>H</sub><0.2. B, scatterplots of the mean normal colon tissue β-value (β-NC<sub>M</sub>) for the retained probes from Panel A (X-axis) against the associated β-CRC<sub>10</sub> (Y-axis). The red dots (HM27: n = 512; HM450: n = 28,428) represent the eliminated probes, the green dots represent the retained probes (HM27: n = 183; HM450: n = 1779) with a β-CRC<sub>10</sub>>β-NC<sub>M</sub> or a β-NC<sub>M</sub><0.2. C, scatterplots of the retained probes from Panel B (green) displayed by the difference between β-CRC<sub>10</sub> and β-PBL<sub>H</sub> (X-axis) against the associated β-CRC<sub>10</sub> (Y-axis). The dots within the yellow square are the probes selected for additional filtering against other types of cancer. The white arrows point out the probes of the two candidate markers. D, ROC curves for the probes used in the multiplex reaction based on methylation β-values of 335 independent colorectal cancer samples and 23 independent matched normal colorectal tissue samples (the DNA methylation data of these samples were not used in the marker discovery pipeline). The dark grey color is the area under the curve.</p
Deep learning based tumor–stroma ratio scoring in colon cancer correlates with microscopic assessment
No full textBackground: The amount of stroma within the primary tumor is a prognostic parameter for colon cancer patients. This phenomenon can be assessed using the tumor–stroma ratio (TSR), which classifies tumors in stroma-low (≤50% stroma) and stroma-high (>50% stroma). Although the reproducibility for TSR determination is good, improvement might be expected from automation. The aim of this study was to investigate whether the scoring of the TSR in a semi- and fully automated method using deep learning algorithms is feasible. Methods: A series of 75 colon cancer slides were selected from a trial series of the UNITED study. For the standard determination of the TSR, 3 observers scored the histological slides. Next, the slides were digitized, color normalized, and the stroma percentages were scored using semi- and fully automated deep learning algorithms. Correlations were determined using intraclass correlation coefficients (ICCs) and Spearman rank correlations. Results: 37 (49%) cases were classified as stroma-low and 38 (51%) as stroma-high by visual estimation. A high level of concordance between the 3 observers was reached, with ICCs of 0.91, 0.89, and 0.94 (all P < .001). Between visual and semi-automated assessment the ICC was 0.78 (95% CI 0.23–0.91, P-value 0.005), with a Spearman correlation of 0.88 (P < .001). Spearman correlation coefficients above 0.70 (N=3) were observed for visual estimation versus the fully automated scoring procedures. Conclusion: Good correlations were observed between standard visual TSR determination and semi- and fully automated TSR scores. At this point, visual examination has the highest observer agreement, but semi-automated scoring could be helpful to support pathologists. © 2023 The Author
Goodness-Of-Fit Tests for Doubly Truncated Data
No full textPurpose – The paper regards the goodness-of-fit (GOF) tests for doubly truncated continuous data with known truncation points. The first goal of the paper is to derive computing formulas of several test statistics for doubly truncated data, when the number of truncated data is unknown. The second goal is to develop statistical inference procedure based on the derived formulas, which includes information regarding the number of truncated data, when it is available. Research method – The formulas and the inference procedure are developed with the use of the methods proposed by Chernobai, Rachev and Fabozzi [2015], who already
developed GOF tests for the left truncated data, when the number of truncated data is unknown. Results – Several tests are developed in case of double truncation. Depending on the chosen truncation points, the tests for left, right or doubly truncated samples might be obtained. When no truncation occurs, the tests are reduced to the complete sample tests. The quality of the tests is assessed on the basis of the FTSE100 return distributions. Originality / value / implications / recommendations – To the best knowledge of the author, computing formulas of the GOF test statistics for doubly truncated distributions with known truncation points, when the number of truncated data is unknown, have not been presented in the literature [email protected]ń University of Economics and BusinessAhmad M. I., Sinclair C.D., Spurr B.D., 1988, Assessment of Flood Frequency Models Using Empirical Distribution Function Statistics, “Water Resources Research”, Vol. 24(8), pp. 1323–1328, DOI: 10.1029/WR024i008p01323.Ayebo A., Kozubowski T.J., 2003, An Asymmetric Generalization of Gaussian and Laplace Laws, “Journal of Probability and Statistical Science”, Vol. 1(2), pp. 187–210.Barr D.R., Davidson T., 1973, A Kolmogorov-Smirnov Test for Censored Samples, “Technometrics”, Vol. 15(4), pp. 739–757.Chernobai A., Rachev S., Fabozzi F., 2015, Composite Goodness-Of-Fit Tests for Left Truncated Loss Samples, [in:] Handbook of Financial Econometrics and Statistics, Lee C., Lee J. (eds), Springer, New York.Cont R., 2001, Empirical Properties of Asset Returns: Stylized Facts and Statistical Issues, “Quantitative Finance”, Vol. 1, pp. 223–236, DOI: 10.1080/713665670.Dufour R., Maag U.R., 1978, Distribution Results for Modified Kolmogorov–Smirnov Statistics for Truncated or Censored Samples, “Technometrics”, Vol. 20(1), pp. 29–32, DOI: 10.1080/00401706.1978.10489613.Echaust K., Lach A., 2017, Goodness-Of-Fit Tests for Truncated Distributions, “35th International Conference on Mathematical Methods in Economics: Conference Proceedings”.Lach A., Smaga Ł., 2018, Comparison of the Goodness-Of-Fit Tests for Truncated Distributions, “Przegląd Statystyczny”, Vol. 65(3), pp. 296–313, DOI: 10.5604/01.3001.0014.0541.Martinez W.L., Martinez A.R., 2008, Computational Statistics Handbook with MATLAB, Chapman and Hall/CRC, New York.Pewsey A., 2018, Parametric Bootstrap Edf-based Goodness-Of-Fit Testing for Sinh-Arcsinh Distributions, “Test”, Vol. 27(1), pp. 147–172, DOI: 10.1007/s11749-017-0538-2.Pettitt A.N., Stephens M.A., 1976, Modified Cramér-von Mises Statistics for Censored Data, “Biometrika”, Vol. 63(2), pp. 291–298, DOI: 10.1093/biomet/63.2.291.Prause K., 1999, The Generalized Hyperbolic Model: Estimation, Financial Derivatives, and Risk Measures (unpublished doctoral dissertation), Universität Freiburg, Freiburg.Sinclair C.D., Spurr B.D., Ahmad M.I., 1987, Modified Anderson-Darling Test, “Communications in Statistics – Theory and Methods”, Vol. 19(10), pp. 3677–3686, DOI:
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