856 resultados para Population set-based methods
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The primary goal of this dissertation is to develop point-based rigid and non-rigid image registration methods that have better accuracy than existing methods. We first present point-based PoIRe, which provides the framework for point-based global rigid registrations. It allows a choice of different search strategies including (a) branch-and-bound, (b) probabilistic hill-climbing, and (c) a novel hybrid method that takes advantage of the best characteristics of the other two methods. We use a robust similarity measure that is insensitive to noise, which is often introduced during feature extraction. We show the robustness of PoIRe using it to register images obtained with an electronic portal imaging device (EPID), which have large amounts of scatter and low contrast. To evaluate PoIRe we used (a) simulated images and (b) images with fiducial markers; PoIRe was extensively tested with 2D EPID images and images generated by 3D Computer Tomography (CT) and Magnetic Resonance (MR) images. PoIRe was also evaluated using benchmark data sets from the blind retrospective evaluation project (RIRE). We show that PoIRe is better than existing methods such as Iterative Closest Point (ICP) and methods based on mutual information. We also present a novel point-based local non-rigid shape registration algorithm. We extend the robust similarity measure used in PoIRe to non-rigid registrations adapting it to a free form deformation (FFD) model and making it robust to local minima, which is a drawback common to existing non-rigid point-based methods. For non-rigid registrations we show that it performs better than existing methods and that is less sensitive to starting conditions. We test our non-rigid registration method using available benchmark data sets for shape registration. Finally, we also explore the extraction of features invariant to changes in perspective and illumination, and explore how they can help improve the accuracy of multi-modal registration. For multimodal registration of EPID-DRR images we present a method based on a local descriptor defined by a vector of complex responses to a circular Gabor filter.
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In the last decade, large numbers of social media services have emerged and been widely used in people's daily life as important information sharing and acquisition tools. With a substantial amount of user-contributed text data on social media, it becomes a necessity to develop methods and tools for text analysis for this emerging data, in order to better utilize it to deliver meaningful information to users. Previous work on text analytics in last several decades is mainly focused on traditional types of text like emails, news and academic literatures, and several critical issues to text data on social media have not been well explored: 1) how to detect sentiment from text on social media; 2) how to make use of social media's real-time nature; 3) how to address information overload for flexible information needs. In this dissertation, we focus on these three problems. First, to detect sentiment of text on social media, we propose a non-negative matrix tri-factorization (tri-NMF) based dual active supervision method to minimize human labeling efforts for the new type of data. Second, to make use of social media's real-time nature, we propose approaches to detect events from text streams on social media. Third, to address information overload for flexible information needs, we propose two summarization framework, dominating set based summarization framework and learning-to-rank based summarization framework. The dominating set based summarization framework can be applied for different types of summarization problems, while the learning-to-rank based summarization framework helps utilize the existing training data to guild the new summarization tasks. In addition, we integrate these techneques in an application study of event summarization for sports games as an example of how to better utilize social media data.
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INTRODUCTION: Severe maternal morbidity , also known as maternal near miss , has been used as an alternative to the study of maternal mortality , since being more frequent shares the same determinants and enables the implementati on of epidem iological surveillance of cases . Since then, hospital audits ha ve been carried out to determine the rates of maternal near miss, its mai n causes and associated factors . More recently, population surveys based on self - reported morbidity have als o been presented as vi able in identifying these cases . OBJECTIVE: The aim of this study was to determine the prevalence and associated factors of maternal near miss and complications during pregnancy and puerperal period in Natal/RN. METHODS: A cross - secti onal population - based study was conducted in Natal /RN , Brazil, which has as its target population women aged 15 to 49 years who were pregnant in the last five years. It was carried out a probabilistic sam pling design based on a multi - stage complex sample , in which 60 census tracts were selected from three strata (north , south - east and west). Afterwards, domiciles were visited in order to obtain a sample of the 908 eligible women in whom a questionnaire was applied. The descriptive analyzes and bivariate ass ociations were performed using the Chi - square test and the estimate of the prevalence ratio (PR ) with 95% confidence interval (CI) and considering the weights and design effects . The Poisson regression analysis , also with 5% significance and 95% CI, was us ed for analyzes of associated factors. RESULTS: 848 women were identified and interviewed after visits in 8.227 households corresponding to a response rate of 93 . 4 %. The prevalence of maternal near miss was 41 . 1 /1 000NV, being the Intensive Care Unity stay i ng (19 . 1 /1 000 LB ) and eclampsia (13 . 5/1000LB) the most important marker s . The prevalence of complications in the puerperal peri od was 21 . 2 %, and hemorrhage (10 . 7%) and urinary tract infection (10 . 7%) the most frequently reported clinical conditions and rema in ing in the hospital for over a week after delivery the mo st frequent intervention (5.4%) . Regarding associated factors , the bivariate analysis showed an association between the increased number of complications in women of black/brown race ( PR= 1 . 23; CI95 % : 1 . 04 - 1 . 46) and lower socioeconomic status ( PR= 1 . 33; CI95%: 1 . 12 - 1 . 58) in women who had pre natal care in public service ( PR= 1 . 42; CI95%: 1 . 16 to 1 . 72 ) and that were not advised during prenatal about where they should do the d elivery (PR= 1 . 24; CI95%: 1 . 05 - 1 . 46), made the del ivery in the public service (PR= 1 . 63; CI95%: 1 . 30 - 2 . 03), had to search for more than one hospital for delivery (PR=1 . 22; CI95%: 1 . 03 - 1 . 45) and had no companion during childbirth ( PR =1 . 19; CI95%: 1 . 01 - 1 . 41) or at all times of childbirth c are - before, during and after childbirth - ( PR= 1 . 25, CI95%: 1 . 05 - 1 . 48) . Moreover, the number of days postpartum hospitalization was higher in women who had more complications (P R= 1 . 59 ; CI95%: 1 . 36 - 1 . 86). In the final regression model for both birth place (P R= 1 . 21 ; CI 95% : 1 . 02 to 1 . 44 ) and socioeconomic status (PR = 1.54 ; CI95%: 1 . 25 - 1 . 90 ) the association remained. CONCLUSION : Conducting population surveys using the pragmatic definition of near miss is feasible and may add importa nt information about this ev ent . It was possible to find the expression of health inequalities related to maternal health in the analysis of both socioeconomic conditions and on the utilization of health services.
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Produced water is a by-product of offshore oil and gas production, and is released in large volumes when platforms are actively processing crude oil. Some pollutants are not typically removed by conventional oil/water separation methods and are discharged with produced water. Oil and grease can be found dispersed in produced water in the form of tiny droplets, and polycyclic aromatic hydrocarbons (PAHs) are commonly found dissolved in produced water. Both can have acute and chronic toxic effects in marine environments even at low exposure levels. The analysis of the dissolved and dispersed phases are a priority, but effort is required to meet the necessary detection limits. There are several methods for the analysis of produced water for dispersed oil and dissolved PAHs, all of which have advantages and disadvantages. In this work, EPA Method 1664 and APHA Method 5520 C for the determination of oil and grease will be examined and compared. For the detection of PAHs, EPA Method 525 and PAH MIPs will be compared, and results evaluated. APHA Method 5520 C Partition-Infrared Method is a liquid-liquid extraction procedure with IR determination of oil and grease. For analysis on spiked samples of artificial seawater, extraction efficiency ranged from 85 – 97%. Linearity was achieved in the range of 5 – 500 mg/L. This is a single-wavelength method and is unsuitable for quantification of aromatics and other compounds that lack sp³-hybridized carbon atoms. EPA Method 1664 is the liquid-liquid extraction of oil and grease from water samples followed by gravimetric determination. When distilled water spiked with reference oil was extracted by this procedure, extraction efficiency ranged from 28.4 – 86.2%, and %RSD ranged from 7.68 – 38.0%. EPA Method 525 uses solid phase extraction with analysis by GC-MS, and was performed on distilled water and water from St. John’s Harbour, all spiked with naphthalene, fluorene, phenanthrene, and pyrene. The limits of detection in harbour water were 0.144, 3.82, 0.119, and 0.153 g/L respectively. Linearity was obtained in the range of 0.5-10 g/L, and %RSD ranged from 0.36% (fluorene) to 46% (pyrene). Molecularly imprinted polymers (MIPs) are sorbent materials made selective by polymerizing functional monomers and crosslinkers in the presence of a template molecule, usually the analytes of interest or related compounds. They can adsorb and concentrate PAHs from aqueous environments and are combined with methods of analysis including GC-MS, LC-UV-Vis, and desorption electrospray ionization (DESI)- MS. This work examines MIP-based methods as well as those methods previously mentioned which are currently used by the oil and gas industry and government environmental agencies. MIPs are shown to give results consistent with other methods, and are a low-cost alternative improving ease, throughput, and sensitivity. PAH MIPs were used to determine naphthalene spiked into ASTM artificial seawater, as well as produced water from an offshore oil and gas operation. Linearity was achieved in the range studied (0.5 – 5 mg/L) for both matrices, with R² = 0.936 for seawater and R² = 0.819 for produced water. The %RSD for seawater ranged from 6.58 – 50.5% and for produced water, from 8.19 – 79.6%.
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lmage super-resolution is defined as a class of techniques that enhance the spatial resolution of images. Super-resolution methods can be subdivided in single and multi image methods. This thesis focuses on developing algorithms based on mathematical theories for single image super resolution problems. lndeed, in arder to estimate an output image, we adopta mixed approach: i.e., we use both a dictionary of patches with sparsity constraints (typical of learning-based methods) and regularization terms (typical of reconstruction-based methods). Although the existing methods already per- form well, they do not take into account the geometry of the data to: regularize the solution, cluster data samples (samples are often clustered using algorithms with the Euclidean distance as a dissimilarity metric), learn dictionaries (they are often learned using PCA or K-SVD). Thus, state-of-the-art methods still suffer from shortcomings. In this work, we proposed three new methods to overcome these deficiencies. First, we developed SE-ASDS (a structure tensor based regularization term) in arder to improve the sharpness of edges. SE-ASDS achieves much better results than many state-of-the- art algorithms. Then, we proposed AGNN and GOC algorithms for determining a local subset of training samples from which a good local model can be computed for recon- structing a given input test sample, where we take into account the underlying geometry of the data. AGNN and GOC methods outperform spectral clustering, soft clustering, and geodesic distance based subset selection in most settings. Next, we proposed aSOB strategy which takes into account the geometry of the data and the dictionary size. The aSOB strategy outperforms both PCA and PGA methods. Finally, we combine all our methods in a unique algorithm, named G2SR. Our proposed G2SR algorithm shows better visual and quantitative results when compared to the results of state-of-the-art methods.
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In this work, we introduce the periodic nonlinear Fourier transform (PNFT) method as an alternative and efficacious tool for compensation of the nonlinear transmission effects in optical fiber links. In the Part I, we introduce the algorithmic platform of the technique, describing in details the direct and inverse PNFT operations, also known as the inverse scattering transform for periodic (in time variable) nonlinear Schrödinger equation (NLSE). We pay a special attention to explaining the potential advantages of the PNFT-based processing over the previously studied nonlinear Fourier transform (NFT) based methods. Further, we elucidate the issue of the numerical PNFT computation: we compare the performance of four known numerical methods applicable for the calculation of nonlinear spectral data (the direct PNFT), in particular, taking the main spectrum (utilized further in Part II for the modulation and transmission) associated with some simple example waveforms as the quality indicator for each method. We show that the Ablowitz-Ladik discretization approach for the direct PNFT provides the best performance in terms of the accuracy and computational time consumption.
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Because of the role that DNA damage and depletion play in human disease, it is important to develop and improve tools to assess these endpoints. This unit describes PCR-based methods to measure nuclear and mitochondrial DNA damage and copy number. Long amplicon quantitative polymerase chain reaction (LA-QPCR) is used to detect DNA damage by measuring the number of polymerase-inhibiting lesions present based on the amount of PCR amplification; real-time PCR (RT-PCR) is used to calculate genome content. In this unit, we provide step-by-step instructions to perform these assays in Homo sapiens, Mus musculus, Rattus norvegicus, Caenorhabditis elegans, Drosophila melanogaster, Danio rerio, Oryzias latipes, Fundulus grandis, and Fundulus heteroclitus, and discuss the advantages and disadvantages of these assays.
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Marine mammals exploit the efficiency of sound propagation in the marine environment for essential activities like communication and navigation. For this reason, passive acoustics has particularly high potential for marine mammal studies, especially those aimed at population management and conservation. Despite the rapid realization of this potential through a growing number of studies, much crucial information remains unknown or poorly understood. This research attempts to address two key knowledge gaps, using the well-studied bottlenose dolphin (Tursiops truncatus) as a model species, and underwater acoustic recordings collected on four fixed autonomous sensors deployed at multiple locations in Sarasota Bay, Florida, between September 2012 and August 2013. Underwater noise can hinder dolphin communication. The ability of these animals to overcome this obstacle was examined using recorded noise and dolphin whistles. I found that bottlenose dolphins are able to compensate for increased noise in their environment using a wide range of strategies employed in a singular fashion or in various combinations, depending on the frequency content of the noise, noise source, and time of day. These strategies include modifying whistle frequency characteristics, increasing whistle duration, and increasing whistle redundancy. Recordings were also used to evaluate the performance of six recently developed passive acoustic abundance estimation methods, by comparing their results to the true abundance of animals, obtained via a census conducted within the same area and time period. The methods employed were broadly divided into two categories – those involving direct counts of animals, and those involving counts of cues (signature whistles). The animal-based methods were traditional capture-recapture, spatially explicit capture-recapture (SECR), and an approach that blends the “snapshot” method and mark-recapture distance sampling, referred to here as (SMRDS). The cue-based methods were conventional distance sampling (CDS), an acoustic modeling approach involving the use of the passive sonar equation, and SECR. In the latter approach, detection probability was modelled as a function of sound transmission loss, rather than the Euclidean distance typically used. Of these methods, while SMRDS produced the most accurate estimate, SECR demonstrated the greatest potential for broad applicability to other species and locations, with minimal to no auxiliary data, such as distance from sound source to detector(s), which is often difficult to obtain. This was especially true when this method was compared to traditional capture-recapture results, which greatly underestimated abundance, despite attempts to account for major unmodelled heterogeneity. Furthermore, the incorporation of non-Euclidean distance significantly improved model accuracy. The acoustic modelling approach performed similarly to CDS, but both methods also strongly underestimated abundance. In particular, CDS proved to be inefficient. This approach requires at least 3 sensors for localization at a single point. It was also difficult to obtain accurate distances, and the sample size was greatly reduced by the failure to detect some whistles on all three recorders. As a result, this approach is not recommended for marine mammal abundance estimation when few recorders are available, or in high sound attenuation environments with relatively low sample sizes. It is hoped that these results lead to more informed management decisions, and therefore, more effective species conservation.
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X-ray computed tomography (CT) is a non-invasive medical imaging technique that generates cross-sectional images by acquiring attenuation-based projection measurements at multiple angles. Since its first introduction in the 1970s, substantial technical improvements have led to the expanding use of CT in clinical examinations. CT has become an indispensable imaging modality for the diagnosis of a wide array of diseases in both pediatric and adult populations [1, 2]. Currently, approximately 272 million CT examinations are performed annually worldwide, with nearly 85 million of these in the United States alone [3]. Although this trend has decelerated in recent years, CT usage is still expected to increase mainly due to advanced technologies such as multi-energy [4], photon counting [5], and cone-beam CT [6].
Despite the significant clinical benefits, concerns have been raised regarding the population-based radiation dose associated with CT examinations [7]. From 1980 to 2006, the effective dose from medical diagnostic procedures rose six-fold, with CT contributing to almost half of the total dose from medical exposure [8]. For each patient, the risk associated with a single CT examination is likely to be minimal. However, the relatively large population-based radiation level has led to enormous efforts among the community to manage and optimize the CT dose.
As promoted by the international campaigns Image Gently and Image Wisely, exposure to CT radiation should be appropriate and safe [9, 10]. It is thus a responsibility to optimize the amount of radiation dose for CT examinations. The key for dose optimization is to determine the minimum amount of radiation dose that achieves the targeted image quality [11]. Based on such principle, dose optimization would significantly benefit from effective metrics to characterize radiation dose and image quality for a CT exam. Moreover, if accurate predictions of the radiation dose and image quality were possible before the initiation of the exam, it would be feasible to personalize it by adjusting the scanning parameters to achieve a desired level of image quality. The purpose of this thesis is to design and validate models to quantify patient-specific radiation dose prospectively and task-based image quality. The dual aim of the study is to implement the theoretical models into clinical practice by developing an organ-based dose monitoring system and an image-based noise addition software for protocol optimization.
More specifically, Chapter 3 aims to develop an organ dose-prediction method for CT examinations of the body under constant tube current condition. The study effectively modeled the anatomical diversity and complexity using a large number of patient models with representative age, size, and gender distribution. The dependence of organ dose coefficients on patient size and scanner models was further evaluated. Distinct from prior work, these studies use the largest number of patient models to date with representative age, weight percentile, and body mass index (BMI) range.
With effective quantification of organ dose under constant tube current condition, Chapter 4 aims to extend the organ dose prediction system to tube current modulated (TCM) CT examinations. The prediction, applied to chest and abdominopelvic exams, was achieved by combining a convolution-based estimation technique that quantifies the radiation field, a TCM scheme that emulates modulation profiles from major CT vendors, and a library of computational phantoms with representative sizes, ages, and genders. The prospective quantification model is validated by comparing the predicted organ dose with the dose estimated based on Monte Carlo simulations with TCM function explicitly modeled.
Chapter 5 aims to implement the organ dose-estimation framework in clinical practice to develop an organ dose-monitoring program based on a commercial software (Dose Watch, GE Healthcare, Waukesha, WI). In the first phase of the study we focused on body CT examinations, and so the patient’s major body landmark information was extracted from the patient scout image in order to match clinical patients against a computational phantom in the library. The organ dose coefficients were estimated based on CT protocol and patient size as reported in Chapter 3. The exam CTDIvol, DLP, and TCM profiles were extracted and used to quantify the radiation field using the convolution technique proposed in Chapter 4.
With effective methods to predict and monitor organ dose, Chapters 6 aims to develop and validate improved measurement techniques for image quality assessment. Chapter 6 outlines the method that was developed to assess and predict quantum noise in clinical body CT images. Compared with previous phantom-based studies, this study accurately assessed the quantum noise in clinical images and further validated the correspondence between phantom-based measurements and the expected clinical image quality as a function of patient size and scanner attributes.
Chapter 7 aims to develop a practical strategy to generate hybrid CT images and assess the impact of dose reduction on diagnostic confidence for the diagnosis of acute pancreatitis. The general strategy is (1) to simulate synthetic CT images at multiple reduced-dose levels from clinical datasets using an image-based noise addition technique; (2) to develop quantitative and observer-based methods to validate the realism of simulated low-dose images; (3) to perform multi-reader observer studies on the low-dose image series to assess the impact of dose reduction on the diagnostic confidence for multiple diagnostic tasks; and (4) to determine the dose operating point for clinical CT examinations based on the minimum diagnostic performance to achieve protocol optimization.
Chapter 8 concludes the thesis with a summary of accomplished work and a discussion about future research.
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Polybrominated diphenyl ethers (PBDEs) are a class of brominated flame retardants (BFRs) that have been heavily used in consumer products such as furniture foams, plastics, and textiles since the mid-1970’s. BFRs are added to products in order to meet state flammability standards intended to increase indoor safety in the event of a fire. The three commercial PBDE mixtures, Penta-, Octa-, and DecaBDE, have all been banned in the United States, however, limited use of DecaBDE is still permitted. PBDEs were phased out of production and added to the Stockholm Convention due to concerns over their environmental persistence and toxicity. Human exposure to PBDEs occurs primarily through the inadvertent ingestion of contaminated house dust, as well as though dietary sources. Despite the phase-out and discontinued use of PBDEs, human exposure to this class of chemicals is likely to continue for decades due to the continued use of treated products and existing environmental reservoirs of PBDEs. Extensive research over the years has shown that PBDEs disrupt thyroid hormone (TH) levels and neurodevelopmental endpoints in rodent and fish models. Additionally, there is growing epidemiological evidence linking PBDE exposure in humans to altered TH homeostasis and neurodevelopmental impairments in children. Due to the importance of THs throughout gestation, there is a great need to understand the effects of BFRs on the developing fetus. Specifically, the placenta plays a critical role in the transport, metabolism, and delivery of THs to the fetal compartment during pregnancy and is a likely target for BFR bioaccumulation and endocrine disruption. The central hypothesis of this dissertation research is that BFRs disrupt the activity of TH sulfotransferase (SULT) enzymes, thereby altering TH concentrations in the placenta.
In the first aim of this dissertation research, the concentrations of PBDEs and 2,4,6-TBP were measured in a cohort of 102 placenta tissue samples from an ongoing pregnancy cohort in Durham, NC. Methods were developed for the extraction and analysis of the BFR analytes. It was found that 2,4,6-TBP was significantly correlated with all PBDE analytes, indicating that 2,4,6-TBP may share common product applications with PBDEs or that 2,4,6-TBP is a metabolite of PBDE compounds. Additionally, this was the first study to measure 2,4,6-TBP in human placenta tissues.
In the second aim of this dissertation research, the placenta tissue concentrations of THs, as well as the endogenous activity of deiodinase (DI) and TH SULT enzymes were quantified using the same cohort of 102 placenta tissue samples. Enzyme activity was detected in all samples and this was the first study to measure TH DI and SULT activity in human placenta tissues. Enzyme activities and TH concentrations were compared with BFR concentrations measured in Aim 1. There were few statistically significant associations observed for the combined data, however, upon stratifying the data set based on infant sex, additional significant associations were observed. For example, among males, those with the highest concentrations of BDE-99 in placenta had T3 levels 0.80 times those with the lowest concentration of BDE-99 (95% confidence interval (CI): 0.59, 1.07). Whereas females with the highest concentrations of BDE-99 in placenta had T3 levels 1.50 times those with the lowest concentration of BDE-99 (95% CI: 1.10, 2.04). Additionally, all BFR analyte concentrations were higher in the placenta of males versus females and they were significantly higher for 2,4,6-TBP and BDE-209. 3,3’-T2 SULT activity was significantly higher in female placenta tissues, while type 3 DI activity was significantly higher in male placenta tissues. This research is the first to show sex-specific differences in the bioaccumulation of BFRs in human placenta tissue, as well as differences in TH concentrations and endogenous DI and SULT activity. The underlying mechanisms of these observed sex differences warrant further investigation.
In the third aim of this dissertation research, the effects of BFRs were examined in a human choriocarcinoma placenta cell line, BeWo. Michaelis-Menten parameters and inhibition curves were calculated for 2,4,6-TBP, 3-OH BDE-47, and 6-OH BDE-47. 2,4,6-TBP was shown to be the most potent inhibitor of 3,3’-T2 SULT activity with a calculated IC50 value of 11.6 nM. It was also shown that 2,4,6-TBP and 3-OH BDE-47 exhibit mixed inhibition of 3,3’-T2 sulfation in BeWo cell homogenates. Next, a series of cell culture exposure experiments were performed using 1, 6, 12, and 24 hour exposure durations. Once again, 2,4,6-TBP was shown to be the most potent inhibitor of basal 3,3’-T2 SULT activity by significantly decreasing activity at the high and medium dose (1 M and 0.5 M, respectively) at all measured time points. Interestingly, BDE-99 was also shown to inhibit basal 3,3’-T2 SULT activity in BeWo cells following the 24 hour exposure, despite exhibiting no inhibitory effects in the BeWo cell homogenate experiments. This indicates that BDE-99 must act through a pathway other than direct enzyme inhibition. Following exposures, the TH concentrations in the cell culture growth media and mRNA expression of TH-related genes were also examined. There was no observed effect of BFR treatment on these endpoints. Future work should focus on determining the downstream biological effects of TH SULT disruption in placental cells, as well as the underlying mechanisms of action responsible for reductions in basal TH SULT activity following BFR exposure.
This was one of the first studies to measure BFRs in a cohort of placenta tissue samples from the United States and the first study to measure THs, DI activity, and SULT activity in human placenta tissues. This research provides a novel contribution to our growing understanding of the effects of BFRs on TH homeostasis within the human placenta, and provides further evidence for sex-specific differences within this important organ. Future research should continue to investigate the effects of environmental contaminants on TH homeostasis within the placenta, as this represents the most critical and vulnerable stage of human development.
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Background: Esophageal adenocarcinoma (EA) is one of the fastest rising cancers in western countries. Barrett’s Esophagus (BE) is the premalignant precursor of EA. However, only a subset of BE patients develop EA, which complicates the clinical management in the absence of valid predictors. Genetic risk factors for BE and EA are incompletely understood. This study aimed to identify novel genetic risk factors for BE and EA.Methods: Within an international consortium of groups involved in the genetics of BE/EA, we performed the first meta-analysis of all genome-wide association studies (GWAS) available, involving 6,167 BE patients, 4,112 EA patients, and 17,159 representative controls, all of European ancestry, genotyped on Illumina high-density SNP-arrays, collected from four separate studies within North America, Europe, and Australia. Meta-analysis was conducted using the fixed-effects inverse variance-weighting approach. We used the standard genome-wide significant threshold of 5×10-8 for this study. We also conducted an association analysis following reweighting of loci using an approach that investigates annotation enrichment among the genome-wide significant loci. The entire GWAS-data set was also analyzed using bioinformatics approaches including functional annotation databases as well as gene-based and pathway-based methods in order to identify pathophysiologically relevant cellular pathways.Findings: We identified eight new associated risk loci for BE and EA, within or near the CFTR (rs17451754, P=4·8×10-10), MSRA (rs17749155, P=5·2×10-10), BLK (rs10108511, P=2·1×10-9), KHDRBS2 (rs62423175, P=3·0×10-9), TPPP/CEP72 (rs9918259, P=3·2×10-9), TMOD1 (rs7852462, P=1·5×10-8), SATB2 (rs139606545, P=2·0×10-8), and HTR3C/ABCC5 genes (rs9823696, P=1·6×10-8). A further novel risk locus at LPA (rs12207195, posteriori probability=0·925) was identified after re-weighting using significantly enriched annotations. This study thereby doubled the number of known risk loci. The strongest disease pathways identified (P<10-6) belong to muscle cell differentiation and to mesenchyme development/differentiation, which fit with current pathophysiological BE/EA concepts. To our knowledge, this study identified for the first time an EA-specific association (rs9823696, P=1·6×10-8) near HTR3C/ABCC5 which is independent of BE development (P=0·45).Interpretation: The identified disease loci and pathways reveal new insights into the etiology of BE and EA. Furthermore, the EA-specific association at HTR3C/ABCC5 may constitute a novel genetic marker for the prediction of transition from BE to EA. Mutations in CFTR, one of the new risk loci identified in this study, cause cystic fibrosis (CF), the most common recessive disorder in Europeans. Gastroesophageal reflux (GER) belongs to the phenotypic CF-spectrum and represents the main risk factor for BE/EA. Thus, the CFTR locus may trigger a common GER-mediated pathophysiology.
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This paper describes an implementation of a method capable of integrating parametric, feature based, CAD models based on commercial software (CATIA) with the SU2 software framework. To exploit the adjoint based methods for aerodynamic optimisation within the SU2, a formulation to obtain geometric sensitivities directly from the commercial CAD parameterisation is introduced, enabling the calculation of gradients with respect to CAD based design variables. To assess the accuracy and efficiency of the alternative approach, two aerodynamic optimisation problems are investigated: an inviscid, 3D, problem with multiple constraints, and a 2D high-lift aerofoil, viscous problem without any constraints. Initial results show the new parameterisation obtaining reliable optimums, with similar levels of performance of the software native parameterisations. In the final paper, details of computing CAD sensitivities will be provided, including accuracy as well as linking geometric sensitivities to aerodynamic objective functions and constraints; the impact in the robustness of the overall method will be assessed and alternative parameterisations will be included.
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Estimates of HIV prevalence are important for policy in order to establish the health status of a country's population and to evaluate the effectiveness of population-based interventions and campaigns. However, participation rates in testing for surveillance conducted as part of household surveys, on which many of these estimates are based, can be low. HIV positive individuals may be less likely to participate because they fear disclosure, in which case estimates obtained using conventional approaches to deal with missing data, such as imputation-based methods, will be biased. We develop a Heckman-type simultaneous equation approach which accounts for non-ignorable selection, but unlike previous implementations, allows for spatial dependence and does not impose a homogeneous selection process on all respondents. In addition, our framework addresses the issue of separation, where for instance some factors are severely unbalanced and highly predictive of the response, which would ordinarily prevent model convergence. Estimation is carried out within a penalized likelihood framework where smoothing is achieved using a parametrization of the smoothing criterion which makes estimation more stable and efficient. We provide the software for straightforward implementation of the proposed approach, and apply our methodology to estimating national and sub-national HIV prevalence in Swaziland, Zimbabwe and Zambia.
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[EN]Vision-based applications designed for humanmachine interaction require fast and accurate hand detection. However, previous works on this field assume different constraints, like a limitation in the number of detected gestures, because hands are highly complex objects to locate. This paper presents an approach which changes the detection target without limiting the number of detected gestures. Using a cascade classifier we detect hands based on their wrists. With this approach, we introduce two main contributions: (1) a reliable segmentation, independently of the gesture being made and (2) a training phase faster than previous cascade classifier based methods. The paper includes experimental evaluations with different video streams that illustrate the efficiency and suitability for perceptual interfaces.
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BACKGROUND: Post-abortion contraceptive use in India is low and the use of modern methods of contraception is rare, especially in rural areas. This study primarily compares contraceptive use among women whose abortion outcome was assessed in-clinic with women who assessed their abortion outcome at home, in a low-resource, primary health care setting. Moreover, it investigates how background characteristics and abortion service provision influences contraceptive use post-abortion. METHODS: A randomized controlled, non-inferiority, trial (RCT) compared clinic follow-up with home-assessment of abortion outcome at 2 weeks post-abortion. Additionally, contraceptive-use at 3 months post-abortion was investigated through a cross-sectional follow-up interview with a largely urban sub-sample of women from the RCT. Women seeking abortion with a gestational age of up to 9 weeks and who agreed to a 2-week follow-up were included (n = 731). Women with known contraindications to medical abortions, Hb < 85 mg/l and aged below 18 were excluded. Data were collected between April 2013 and August 2014 in six primary health-care clinics in Rajasthan. A computerised random number generator created the randomisation sequence (1:1) in blocks of six. Contraceptive use was measured at 2 weeks among women successfully followed-up (n = 623) and 3 months in the sub-set of women who were included if they were recruited at one of the urban study sites, owned a phone and agreed to a 3-month follow-up (n = 114). RESULTS: There were no differences between contraceptive use and continuation between study groups at 3 months (76 % clinic follow-up, 77 % home-assessment), however women in the clinic follow-up group were most likely to adopt a contraceptive method at 2 weeks (62 ± 12 %), while women in the home-assessment group were most likely to adopt a method after next menstruation (60 ± 13 %). Fifty-two per cent of women who initiated a method at 2 weeks chose the 3-month injection or the copper intrauterine device. Only 4 % of women preferred sterilization. Caste, educational attainment, or type of residence did not influence contraceptive use. CONCLUSIONS: Simplified follow-up after early medical abortion will not change women's opportunities to access contraception in a low-resource setting, if contraceptive services are provided as intra-abortion services as early as on day one. Women's postabortion contraceptive use at 3 months is unlikely to be affected by mode of followup after medical abortion, also in a low-resource setting. Clinical guidelines need to encourage intra-abortion contraception, offering the full spectrum of evidence-based methods, especially long-acting reversible methods. TRIAL REGISTRATION: Clinicaltrials.gov NCT01827995.