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In recent years, the wide application of deep neural network models has brought serious risks of intellectual property rights infringement. Embedding a watermark in a network model is an effective solution to protect intellectual property rights. Although researchers have proposed schemes to add watermarks to models, they cannot prevent attackers from adding and overwriting original information, and embedding rates cannot be quantified. Therefore, aiming at these problems, this paper designs a high embedding rate and tamper-proof watermarking scheme. We employ wet paper coding (WPC), in which important parameters are regarded as wet blocks and the remaining unimportant parameters are regarded as dry blocks in the model. To obtain the important parameters more easily, we propose an optimized probabilistic selection strategy (OPSS). OPSS defines the unimportant-level function and sets the importance threshold to select the important parameter positions and to ensure that the original function is not affected after the model parameters are changed. We regard important parameters as an unmodifiable part, and only modify the part that includes the unimportant parameters. We selected the MNIST, CIFAR-10, and ImageNet datasets to test the performance of the model after adding a watermark and to analyze the fidelity, robustness, embedding rate, and comparison schemes of the model. Our experiment shows that the proposed scheme has high fidelity and strong robustness along with a high embedding rate and the ability to prevent malicious tampering.

Paper spray ionization has been used as a fast sampling/ionization method for the direct mass spectrometric analysis of biological samples at ambient conditions. Here, we demonstrated that by utilizing paper spray ionization-mass spectrometry (PSI-MS) coupled with field asymmetric waveform ion mobility spectrometry (FAIMS), predictive metabolic and lipidomic profiles of routine breast core needle biopsies could be obtained effectively. By the combination of machine learning algorithms and pathological examination reports, we developed a classification model, which has an overall accuracy of 87.5% for an instantaneous differentiation between cancerous and noncancerous breast tissues utilizing metabolic and lipidomic profiles. Our results suggested that paper spray ionization-ion mobility spectrometry-mass spectrometry (PSI-IMS-MS) is a powerful approach for rapid breast cancer diagnosis based on altered metabolic and lipidomic profiles.

One of the most widely used measures of scientific impact is the number of citations. However, due to its heavy-tailed distribution, citations are fundamentally difficult to predict but can be improved. This study was aimed at investigating the factors and parts influencing the citation number of a scientific paper in the otology field. Therefore, this work proposes a new solution that utilizes machine learning and natural language processing to process English text and provides a paper citation as the predicted results. Different algorithms are implemented in this solution, such as linear regression, boosted decision tree, decision forest, and neural networks. The application of neural network regression revealed that papers’ abstracts have more influence on the citation numbers of otological articles. This new solution has been developed in visual programming using Microsoft Azure machine learning at the back end and Programming Without Coding Technology at the front end. We recommend using machine learning models to improve the abstracts of research articles to get more citations.

Today, computer graphics and graphic image processing techniques have been widely used in daily life and industrial production. Due to the development of computers, computer graphics has brought more convenience to our daily life. In order to give full play to the value of computers, this paper takes the Hakka paper-cut art with local characteristics as the starting point, first of all its development history, artistic characteristics, compositional forms, expression techniques, cultural connotations, Hakka paper-cut patterns, and the symbolic meaning of folk customs, and then we design a visualization system for the paper-cut works of Gannan Hakka based on computer graphics. In addition, the system provides a solution for the integration of Gannan Hakka paper-cut art and Jiangxi native product packaging design and provides a reference for the theory and practice of modern native product packaging design.

Aiming at the problem of easy tampering and difficult integrity authentication of paper text documents, this paper proposes a robust content authentication method for printed documents based on text watermarking scheme resisting print-and-scan attack. Firstly, an authentication watermark signal sequence related to content of text document is generated based on the Logistic chaotic map model; then, the authentication watermark signal sequence is embedded into printed paper document by using a robust text watermarking scheme; finally, the watermark information is extracted from scanned image of paper document, and compared with the authentication watermark information calculated in real time by the text document content obtained by OCR technology, thereby performing content integrity authentication of the paper text documents. Experimental results show that our method can achieve the robust content integrity authentication of paper text documents, and can also accurately locate the tampering position. In addition, the document after embedding the watermark information has a good visual effect, and the text watermarking scheme has a large information capacity.

The report of the American Association of Physicists in Medicine (AAPM) Task Group No. 132 published in 2017 reviewed rigid image registration and deformable image registration (DIR) approaches and solutions to provide recommendations for quality assurance and quality control of clinical image registration and fusion techniques in radiotherapy. However, that report did not include the use of DIR for advanced applications such as dose warping or warping of other matrices of interest. Considering that DIR warping tools are now readily available, discussions were hosted by the Medical Image Registration Special Interest Group (MIRSIG) of the Australasian College of Physical Scientists & Engineers in Medicine in 2018 to form a consensus on best practice guidelines. This position statement authored by MIRSIG endorses the recommendations of the report of AAPM task group 132 and expands on the best practice advice from the ‘Deforming to Best Practice’ MIRSIG publication to provide guidelines on the use of DIR for advanced applications.

There is increasing focus on applying deep learning methods to electrocardiograms (ECGs), with recent studies showing that neural networks (NNs) can predict future heart failure or atrial fibrillation from the ECG alone. However, large numbers of ECGs are needed to train NNs, and many ECGs are currently only in paper format, which are not suitable for NN training. We developed a fully-automated online ECG digitisation tool to convert scanned paper ECGs into digital signals. Using automated horizontal and vertical anchor point detection, the algorithm automatically segments the ECG image into separate images for the 12 leads and a dynamical morphological algorithm is then applied to extract the signal of interest. We then validated the performance of the algorithm on 515 digital ECGs, of which 45 were printed, scanned and redigitised. The automated digitisation tool achieved 99.0% correlation between the digitised signals and the ground truth ECG (n = 515 standard 3-by-4 ECGs) after excluding ECGs with overlap of lead signals. Without exclusion, the performance of average correlation was from 90 to 97% across the leads on all 3-by-4 ECGs. There was a 97% correlation for 12-by-1 and 3-by-1 ECG formats after excluding ECGs with overlap of lead signals. Without exclusion, the average correlation of some leads in 12-by-1 ECGs was 60–70% and the average correlation of 3-by-1 ECGs achieved 80–90%. ECGs that were printed, scanned, and redigitised, our tool achieved 96% correlation with the original signals. We have developed and validated a fully-automated, user-friendly, online ECG digitisation tool. Unlike other available tools, this does not require any manual segmentation of ECG signals. Our tool can facilitate the rapid and automated digitisation of large repositories of paper ECGs to allow them to be used for deep learning projects.

The purpose of this article is to present algorithms for the diagnostic management of solitary bone lesions incidentally encountered on computed tomography (CT) and magnetic resonance (MRI) in adults. Based on review of the current literature and expert opinion, the Practice Guidelines and Technical Standards Committee of the Society of Skeletal Radiology (SSR) proposes a bone reporting and data system (Bone-RADS) for incidentally encountered solitary bone lesions on CT and MRI with four possible diagnostic management recommendations (Bone-RADS1, leave alone; Bone-RADS2, perform different imaging modality; Bone-RADS3, perform follow-up imaging; Bone-RADS4, biopsy and/or oncologic referral). Two algorithms for CT based on lesion density (lucent or sclerotic/mixed) and two for MRI allow the user to arrive at a specific Bone-RADS management recommendation. Representative cases are provided to illustrate the usability of the algorithms.

The application of big data, radiomics, machine learning, and artificial intelligence (AI) algorithms in radiology requires access to large data sets containing personal health information. Because machine learning projects often require collaboration between different sites or data transfer to a third party, precautions are required to safeguard patient privacy. Safety measures are required to prevent inadvertent access to and transfer of identifiable information. The Canadian Association of Radiologists (CAR) is the national voice of radiology committed to promoting the highest standards in patient-centered imaging, lifelong learning, and research. The CAR has created an AI Ethical and Legal standing committee with the mandate to guide the medical imaging community in terms of best practices in data management, access to health care data, de-identification, and accountability practices. Part 2 of this article will inform CAR members on the practical aspects of medical imaging de-identification, strengths and limitations of de-identification approaches, list of de-identification software and tools available, and perspectives on future directions.

The ACR Committee on Incidental Findings presents recommendations for managing liver lesions that are incidentally detected on CT. These recommendations represent an update from the liver component of the ACR 2010 white paper on managing incidental findings in the pancreas, adrenal glands, kidneys, and liver. The Liver Subcommittee-which included five abdominal radiologists, one hepatologist, and one hepatobiliary surgeon-developed this algorithm. The recommendations draw from published evidence and expert opinion and were finalized by informal iterative consensus. Algorithm branches categorize liver lesions on the basis of patient characteristics and imaging features. They terminate with an assessment of benignity or a specific follow-up recommendation. The algorithm addresses most, but not all, pathologies and clinical scenarios. The goal is to improve the quality of care by providing guidance on how to manage incidentally detected liver lesions.

This letter points out a conceptual error made by the authors of a published paper, which presents a review and evaluation of computational methods in lncRNA identification. The error was made in the execution of the BASiNET method when considering an example file (toy model) made available by the authors with the aim of showing how a classification model could be stored in a file for later use. In this letter, this error is contextualized, the correct use of the BASiNET method is pointed out and the results of its correct execution to one of the datasets used in the review article are presented. The results clearly show the misuse of the method and present its correct use so that it can be fairly compared with other methods in the literature and prevent its misuse from being replicated by new studies.

Letter to the Editor concerning "Describing center of pressure movement in stabilometry by ellipse area approximation" from Agnieszka Gołąb.

International audience; The objective of this article was to evaluate the evidence currently available about the clinical value of artificial intelligence (AI) in breast imaging. Nine experts from the disciplines involved in breast disease management – including physicists and radiologists – convened a meeting on June 3, 2019 to discuss the evidence for the use of this technology in plenary and focused sessions. Prior to the meeting, the group performed a literature review on predefined topics. This paper presents the consensus reached by this working group on recommendations for the future use of AI in breast screening and related research topics.

Highlights • In this position paper, we provide a collection of views on the role of AI in the COVID-19 pandemic, from the clinical needs to the design of AI-based systems, to the translation of the developed tools to the clinic. We highlight key factors in designing system solutions - per specific task; as well as design issues in managing the disease on the national level. We focus on three specific use-cases for which AI systems can be built: from the early disease detection, the management of the disease in a hospital setting, and building patient-specific predictive models that require the combination of imaging with additional clinical features. Infrastructure considerations and population modeling in two European countries will be described. This pandemic has made the practical and scientific challenges of making AI solutions very explicit. A discussion concludes this paper, with a list of challenges facing the community in the AI road ahead., In this position paper, we provide a collection of views on the role of AI in the COVID-19 pandemic, from clinical requirements to the design of AI-based systems, to the translation of the developed tools to the clinic. We highlight key factors in designing system solutions - per specific task; as well as design issues in managing the disease at the national level. We focus on three specific use-cases for which AI systems can be built: early disease detection, management in a hospital setting, and building patient-specific predictive models that require the combination of imaging with additional clinical data. Infrastructure considerations and population modeling in two European countries will be described. This pandemic has made the practical and scientific challenges of making AI solutions very explicit. A discussion concludes this paper, with a list of challenges facing the community in the AI road ahead.

The Canadian Association of Radiologists Incidental Findings Working Group consists of both academic subspecialty and general radiologists and is tasked with adapting and expanding upon the American College of Radiology incidental findings white papers to more closely apply to Canadian practice patterns, particularly more comprehensively dealing with the role of ultrasound and pursuing more cost-effective approaches to the workup of incidental findings without compromising patient care. Presented here are the 2020 Canadian guidelines for the management of hepatobiliary incidental findings. Topics covered include initial assessment of hepatic steatosis and cirrhosis, the workup of incidental liver masses identified on ultrasound and computed tomography (with algorithms presented), incidental gallbladder findings (wall thickening, calcification, and polyps), and management of incidental biliary dilatation.

Objective Most preventable adverse drug events and medication errors occur during medication ordering. Medication order entry and clinical decision support are available on paper or as computerized systems. In this post-hoc analysis we investigated frequency and clinical impact of blood glucose (BG) documentation- and user-related calculation errors as well as workflow deviations in diabetes management. We aimed to compare a paper-based protocol to a computerized medication management system combined with clinical workflow and decision support. Methods Seventy-nine hospitalized patients with type 2 diabetes mellitus were treated with an algorithm driven basal-bolus insulin regimen. BG measurements, which were the basis for insulin dose calculations, were manually entered either into the paper-based workflow protocol (PaperG: 37 patients) or into GlucoTab ® —a mobile tablet PC based system (CompG: 42 patients). We used BG values from the laboratory information system as a reference. A workflow simulator was used to determine user calculation errors as well as workflow deviations and to estimate the effect of errors on insulin doses. The clinical impact of insulin dosing errors and workflow deviations on hypo- and hyperglycemia was investigated. Results The BG documentation error rate was similar for PaperG (4.9%) and CompG group (4.0%). In PaperG group, 11.1% of manual insulin dose calculations were erroneous and the odds ratio (OR) of a hypoglycemic event following an insulin dosing error was 3.1 (95% CI: 1.4–6.8). The number of BG values influenced by insulin dosing errors was eightfold higher than in the CompG group. In the CompG group, workflow deviations occurred in 5.0% of the tasks which led to an increased likelihood of hyperglycemia, OR 2.2 (95% CI: 1.1–4.6). Discussion Manual insulin dose calculations were the major source of error and had a particularly strong influence on hypoglycemia. By using GlucoTab ® , user calculation errors were entirely excluded. The immediate availability and automated handling of BG values from medical devices directly at the point of care has a high potential to reduce errors. Computerized systems facilitate the safe use of more complex insulin dosing algorithms without compromising usability. In CompG group, missed or delayed tasks had a significant effect on hyperglycemia, while in PaperG group insufficient precision of documentation times limited analysis. The use of old BG measurements was clinically less relevant. Conclusion Insulin dosing errors and workflow deviations led to measurable changes in clinical outcome. Diabetes management systems including decision support should address nurses as well as physicians in a computerized way. Our analysis shows that such systems reduce the frequency of errors and therefore decrease the probability of hypo- and hyperglycemia.

The electrocardiogram (ECG) signal describes the heart’s electrical activity, allowing it to detect several health conditions, including cardiac system abnormalities and dysfunctions. Nowadays, most patient medical records are still paper-based, especially those made in past decades. The importance of collecting digitized ECGs is twofold: firstly, all medical applications can be easily implemented with an engineering approach if the ECGs are treated as signals; secondly, paper ECGs can deteriorate over time, therefore a correct evaluation of the patient’s clinical evolution is not always guaranteed. The goal of this paper is the realization of an automatic conversion algorithm from paper-based ECGs (images) to digital ECG signals. The algorithm involves a digitization process tested on an image set of 16 subjects, also with pathologies. The quantitative analysis of the digitization method is carried out by evaluating the repeatability and reproducibility of the algorithm. The digitization accuracy is evaluated both on the entire signal and on six ECG time parameters (R-R peak distance, QRS complex duration, QT interval, PQ interval, P-wave duration, and heart rate). Results demonstrate the algorithm efficiency has an average Pearson correlation coefficient of 0.94 and measurement errors of the ECG time parameters are always less than 1 mm. Due to the promising experimental results, the algorithm could be embedded into a graphical interface, becoming a measurement and collection tool for cardiologists.

In CERME12, our working group "Algorithmics" started its work as a newly established TWG. Since algorithms have always been at the heart of mathematics and their importance has been steadily increasing since the beginnings of theoretical computer science, the design and analysis of algorithms – called algorithmics (Traub 1964, Knuth 1985) – lies at the intersection of mathematics and computer science. For this reason, on the one hand, various algorithms and algorithmic activities have their traditional place in mathematics curricula at all levels. At the school level, mathematics and computer science have interacted since the 1980s, when many schools set up labs with computers equipped with programming software. On the other hand, many questions arise in the context of teaching and learning algorithms: a first, more applied group of questions aims at algorithms in mathematics education and curricula, a second, more theoretical group of questions seeks to clarify the concepts of algorithm and algorithmic thinking, + ID der Publikation: phlu_16641 + Art des Beitrages: Buchkapitel/Beitrag in Sammelband + Seiten: 100 - 107 + Sprache: Englisch + Letzte Aktualisierung: 2023-01-31 14:17:15

In the last 15 years, the segmentation of vessels in retinal images has become an intensively researched problem in medical imaging, with hundreds of algorithms published. One of the de facto benchmarking data sets of vessel segmentation techniques is the DRIVE data set. Since DRIVE contains a predefined split of training and test images, the published performance results of the various segmentation techniques should provide a reliable ranking of the algorithms. Including more than 100 papers in the study, we performed a detailed numerical analysis of the coherence of the published performance scores. We found inconsistencies in the reported scores related to the use of the field of view (FoV), which has a significant impact on the performance scores. We attempted to eliminate the biases using numerical techniques to provide a more realistic picture of the state of the art. Based on the results, we have formulated several findings, most notably: despite the well-defined test set of DRIVE, most rankings in published papers are based on non-comparable figures; in contrast to the near-perfect accuracy scores reported in the literature, the highest accuracy score achieved to date is 0.9582 in the FoV region, which is 1% higher than that of human annotators. The methods we have developed for identifying and eliminating the evaluation biases can be easily applied to other domains where similar problems may arise.

Many complex physical systems exhibit a rich variety of discrete behavioural modes. Often, the system complexity limits the applicability of standard modelling tools. Hence, understanding the underlying physics of different behaviours and distinguishing between them is challenging. Although traditional machine learning techniques could predict and classify behaviour well, typically they do not provide any meaningful insight into the underlying physics of the system. In this paper we present a novel method for extracting physically meaningful clusters of discrete behaviour from limited experimental observations. This method obtains a set of physically plausible functions that both facilitate behavioural clustering and aid in system understanding. We demonstrate the approach on the V-shaped falling paper system, a new falling paper type system that exhibits four distinct behavioural modes depending on a few morphological parameters. Using just 49 experimental observations, the method discovered a set of candidate functions that distinguish behaviours with an error of 2.04%, while also aiding insight into the physical phenomena driving each behaviour. © 2019 Howison 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.

Efficient and safe detection of Bacillus anthracis spores (BAS) is a challenging task especially in bio-terror scenarios where the agent is concealed. We provide a proof-of-concept for the identification of concealed BAS inside mail envelopes using short-wave infrared hyperspectral imaging (SWIR-HSI). The spores and two other benign materials are identified according to their typical absorption spectrum. The identification process is based on the removal of the envelope signal using a new automatic new algorithm. This method may serve as a fast screening tool prior to using classical bioanalytical techniques.

Electrocardiography (ECG) is essential in many heart diseases. However, some ECGs are recorded by paper, which can be highly noisy. Digitizing the paper-based ECG records into a high-quality signal is critical for further analysis. We formulated the digitization problem as a segmentation problem and proposed a deep learning method to digitize highly noisy ECG scans. Our method extracts the ECG signal in an end-to-end manner and can handle different paper record layouts. In the experiment, our model clearly extracted the ECG waveform with a Dice coefficient of 0.85 and accurately measured the common ECG parameters with more than 0.90 Pearson's correlation. We showed that the end-to-end approach with deep learning can be powerful in ECG digitization. To the best of our knowledge, we provide the first approach to digitize the least informative noisy binary ECG scans and potentially be generalized to digitize various ECG records.

Author summary Conferences are great venues for disseminating algorithmic bioinformatics results, but they unfortunately do not offer an opportunity to make major revisions in the way that journals do. As a result, it is not possible for authors to fix mistakes that might be easily correctable but nevertheless can cause the paper to be rejected. As a reviewer, I wish that I had the opportunity to tell the authors, “Hey, you forgot to do this really important thing, without which it is hard to accept the paper, but if you could go back and fix it, you might have a great paper for the conference.” This lack of a back and forth can be especially problematic for first-time submitters or those from outside the field, e.g., biologists. In this article, I outline Ten Simple Rules to follow when writing an algorithmic bioinformatics conference paper to avoid having it rejected.

A facile strategy, engineered for low-cost mass production, to synthesize biomass-derived activated carbon/reduced graphene oxide composite electrodes (GBPCs) by one-pot carbonization of blotting papers containing graphene oxide (GO) and zinc chloride (ZnCl2) was proposed. Benefitting from the water absorption characteristic of blotting papers in which the voids between the celluloses can easily absorb the GO/ZnCl2 solution, the chemical activation and reduction of GO can synchronously achieve via one-step carbonization process. As a result, the GBPCs deliver a large specific surface area to accumulate charge. Simultaneously, it provides high conductivity for electron transfer. The symmetric supercapacitor assembled with the optimal GBPCs in 6 M KOH electrolyte exhibits an excellent specific capacitance of 204 F g&minus, 1 (0.2 A g&minus, 1), outstanding rate capability of 100 F g&minus, 1 (20 A g&minus, 1). Meanwhile, it still keeps 90% of the initial specific capacitance over 10,000 cycles. The readily available raw material, effective chemical activation, simple rGO additive, and resulting electrochemical properties hold out the promise of hope to achieve low-cost, green, and large-scale production of practical activated carbon composite materials for high-efficiency energy storage applications.

Medicine has entered the digital era, driven by data from new modalities, especially genomics and imaging, as well as new sources such as wearables and Internet of Things. As we gain a deeper understanding of the disease biology and how diseases affect an individual, we are developing targeted therapies to personalize treatments. There is a need for technologies like Artificial Intelligence (AI) to be able to support predictions for personalized treatments. In order to mainstream AI in healthcare we will need to address issues such as explainability, liability and privacy. Developing explainable algorithms and including AI training in medical education are many of the solutions that can help alleviate these concerns.

The application of big data, radiomics, machine learning, and artificial intelligence (AI) algorithms in radiology requires access to large data sets containing personal health information. Because machine learning projects often require collaboration between different sites or data transfer to a third party, precautions are required to safeguard patient privacy. Safety measures are required to prevent inadvertent access to and transfer of identifiable information. The Canadian Association of Radiologists (CAR) is the national voice of radiology committed to promoting the highest standards in patient-centered imaging, lifelong learning, and research. The CAR has created an AI Ethical and Legal standing committee with the mandate to guide the medical imaging community in terms of best practices in data management, access to health care data, de-identification, and accountability practices. Part 1 of this article will inform CAR members on principles of de-identification, pseudonymization, encryption, direct and indirect identifiers, k-anonymization, risks of reidentification, implementations, data set release models, and validation of AI algorithms, with a view to developing appropriate standards to safeguard patient information effectively.

Interferon (IFN)-γ release assays (IGRAs) are probably the most accurate tests for the detection of latent Mycobacterium tuberculosis infection, but IGRAs are labour intensive and the transport of samples over longer distances is difficult. IFN-γ-induced protein (IP)-10 is expressed at 100-fold higher levels than IFN-γ, and IP-10 release assays have comparable performance to IGRAs. The aim of this study was to explore the diagnostic potential of a novel IP-10 release assay based on dried plasma spots (DPS). The presence of IP-10 and IFN-γ was determined in plasma and in DPS by ELISA. Diagnostic algorithms for plasma and DPS tests for IP-10 were developed on a training cohort comprising 60 tuberculosis (TB) patients and 59 healthy controls. Diagnostic accuracy was assessed in a validation cohort comprising 78 TB patients and 98 healthy controls. Plasma was measured in Spain and DPS samples were sent to Denmark using the conventional postal service for analysis. IP-10 was readily detectable in both plasma and DPS, and correlation was excellent (r2 = 0.95). QuantiFERON-TB Gold In-Tube (QFT-TB) and IP-10 in DPS and plasma rendered comparable sensitivity (78%, 82% and 84%, respectively), specificity (100%, 97% and 97%, respectively) and indeterminate rates (p>0.55). The DPS-based IP-10 test has comparable diagnostic accuracy to the QFT-TB and samples can be sent via conventional mail over long distances for analysis without affecting the results.

I review my scientific career in terms of eight areas and 16 papers. The first two areas are associated with childhood. The other six are associated with residual maximum likelihood (REML), canonical transformation, inbreeding in selected populations, average information residual maximum likelihood (AIREML), the computer program ASReml and sampling-based estimation.

Photodegradation of lignin is one of the major postprocessing problems in paper production, as this renders yellowing of the paper and reduced paper quality. In this study, we have explored the photochemical properties of substituted stilbene derivatives believed to be key chromophores in the photodegradation of lignin derived from cinnamyl alcohol. In particular, the present work focuses on the computation of UV/vis electronic absorption spectra for different methoxylated stilbenes and their proposed photodegradation products. All calculations were performed using the time-dependent formalism of density functional theory (TD-DFT) and the B3LYP hybrid functional. It is concluded that the methodology employed is capable of reproducing not only the overall spectra, but also subtle features owing to the effects of different substitution patterns. For the strongly absorbing first excited singlet state (HOMO --LUMO excitation) of the methoxylated stilbenes, the calculated transition energies are, albeit somewhat fortuitously, in excellent agreement with experimental data. The light-induced yellowing indirectly caused by the presence of stilbenes can be rationalized in terms of the absorption spectra of the resulting photodegraded o-quinones, for which distinct transitions in the 420-500 nm region of the visible spectrum lacking prior to degradation are observed.

In the present study, plant-scale process integration was applied to an Indian paper mill using the water cascade analysis (WCA) technique. Three limiting constraints, chemical oxygen demand (COD), total dissolved solids (TDS), and adsorbable organic halides (AOX), were considered for the study. A nearest neighbor algorithm was used to distribute the freshwater and recycled water among the plant operations. It was found that the limiting critical constraint depends upon the types of processes and streams involved in the integration. The limiting critical constraint can differ for different sections of the same industry, and can differ in different schemes of integration. After process integration, a 55.6% reduction in effluent flow, a 36% reduction in COD, and a 73% reduction in AOX were observed. After process integration, a 35.21% reduction in pollution costs can be achieved and, assuming the average production of the mill to be 225 tons per day, a savings of Indian rupees (INR) 1.73 per kg of paper produced can be achieved by employing process integration. The water cess was calculated as INR 3024.77 per day without integration for the sections that were considered for integration, while after integration, a 41.53% savings in the form of water cess was calculated.

Quantitative non-destructive analysis of individual constituents of historic rag paper is crucial for its effective preservation. In this work, we examine the potentials of mid- and near-infrared spectroscopy, however, in order to fully utilise the selectivity inherent to spectroscopic multivariate measurements, genetic algorithms were used to select spectral data derived from information-rich FT-IR or UV-vis-NIR measurements to build multivariate calibration models based on partial least squares regression, relating spectra to gelatine content in paper. A selective but laborious chromatographic method for the quantification of hydroxyproline (HYP) has been developed to provide the reference data on gelatine content. We used 9-fluorenylmethyl chloroformate (FMOC) to derivatise HYP, which was subsequently determined using reverse-phase liquid chromatographic separation and fluorimetric detection. In this process, the sample is consumed, which is why the method can only be used as a reference method.The sampling flexibility afforded by small-size field-portable spectroscopic instrumentation combined with chemometric data analysis, represents an attractive addition to existing analytical techniques for cultural heritage materials. (C) 2010 Elsevier B.V. All rights reserved.

Cardiac patients after an acute event and/or with chronic heart disease deserve special attention to restore their quality of life and to maintain or improve functional capacity. They require counselling to avoid recurrence through a combination of adherence to a medication plan and adoption of a healthy lifestyle. These secondary prevention targets are included in the overall goal of cardiac rehabilitation (CR). Cardiac rehabilitation can be viewed as the clinical application of preventive care by means of a professional multi-disciplinary integrated approach for comprehensive risk reduction and global long-term care of cardiac patients. The CR approach is delivered in tandem with a flexible follow-up strategy and easy access to a specialized team. To promote implementation of cardiac prevention and rehabilitation, the CR Section of the EACPR (European Association of Cardiovascular Prevention and Rehabilitation) has recently completed a Position Paper, entitled 'Secondary prevention through cardiac rehabilitation: A condition-oriented approach'. Components of multidisciplinary CR for seven clinical presentations have been addressed. Components include patient assessment, physical activity counselling, exercise training, diet/nutritional counselling, weight control management, lipid management, blood pressure monitoring, smoking cessation, and psychosocial management. Cardiac rehabilitation services are by definition multi-factorial and comprehensive, with physical activity counselling and exercise training as central components in all rehabilitation and preventive interventions. Many of the risk factor improvements occurring in CR can be mediated through exercise training programmes. This call-for-action paper presents the key components of a CR programme: physical activity counselling and exercise training. It summarizes current evidence-based best practice for the wide range of patient presentations of interest to the general cardiology community.

We study the effects of ambient air humidity on the dynamics of imbibition in a paper. We observed that a quick increase of ambient air humidity leads to depinning and non-Washburn motion of wetting fronts. Specifically, we found that after depinning the wetting front moves with decreasing velocity v∝ (hp /hD )γ, where hD is the front elevation with respect to its pinned position at lower humidity hp, while γ≅1/3. The spatiotemporal maps of depinned front activity are established. The front motion is controlled by the dynamics of local avalanches directed at 30 to the balk flow direction. Although the roughness of the pinned wetting front is self-affine and the avalanche size distribution displays a power-law asymptotic, the roughness of the moving front becomes multiaffine a few minutes after depinning. © 2013 American Physical Society., This work was supported by the PEMEX under the research grants SENER-CONACYT No. 143927 and No. 116458.

Insulin infusions are commonly utilized to control hyperglycemia in critically ill patients and decrease hyperglycemia associated complications. Safety concerns have been raised in trials evaluating methods of glycemic control regarding the incidence of hypoglycemia and its relationship to increased mortality. Electronic glycemic management systems (eGMS) may result in less variable blood glucose (BG) control and less hypoglycemia. This study aimed to compare BG control, time in target BG range, and the rate of hypoglycemia when critically ill patients were managed with an insulin infusion guided by paper-based protocol (PBP) versus eGMS.This retrospective review compared critically ill patients ≥ 18 years old that received insulin infusion from March to May 2015 (PBP group) and October to January 2017 (eGMS group). The primary outcome was the incidence of hypoglycemia. Secondary outcomes included frequency and severity of hypoglycemia, duration in glycemic target, length of insulin therapy, as well as ICU and hospital length of stay.Fifty-four patients were evaluated, 27 in each group. Percentage of days with BG70 mg/dL was significantly reduced after eGMS implementation (21.5% v 1.3%, P.0001) including the frequency of severe hypoglycemia (BG40 mg/dL) (5.4% v 0.01%, P.0001). Patients in the eGMS group spent a greater amount of time in target BG range (31.5% v 63.7%, P.0001).An eGMS has the potential to address many of the unmet needs of an optimal glycemic control strategy, minimizing hypoglycemia, and glycemic variability in a heterogeneous critically ill population.

Previous studies have shown that drug concentrations in blood can change during storage, especially at room temperature, but even labile drugs such as cocaine may be stable in dried blood spots (DBS). A new method has been developed for the analysis of hydrolytically labile drugs in blood spots on filter paper in order to assess their degradation during a storage period of one month. The drugs selected included flunitrazepam, temazepam, oxazepam, lorazepam, nitrazepam, diazepam, and cocaine. A Guthrie card 903 was spotted with 100 microL of blood containing the drugs at concentrations of 1000 ng/mL and left overnight to dry at room temperature. The filter paper was suspended in extraction buffer for 1 h with ultrasonication. Drugs were then extracted from the buffer by solid-phase extraction using Clean Screen((R)) columns and analyzed by liquid chromatography-tandem mass spectrometry. Method validation showed that all calibration curves were linear over the concentration range 5-200 ng/spot with correlation coefficients of 0.994-0.999. Interday and intraday precisions at three concentrations (10, 50, and 100 ng/spot) were 1.6-18.3% and 2.8-14.7%, respectively. Limits of detection were 0.29-0.74 ng/spot, and lower limits of quantitation were 0.99-2.46 ng/spot. Recoveries of all analytes were in the range 81-106%. DBS were stored in duplicate at room temperature, 4 degrees C, and -20 degrees C for up to one month. Degradation of the drugs in DBS at all storage conditions was less than for the corresponding liquid blood samples stored under similar conditions and more than 80% of each analyte could be recovered from the samples.

Good cross-directional control of sheet variables in a paper machine depends on a number of factors. One such factor is the correct alignment of actuators with their corresponding responses. The alignment changes with time either locally or across the whole paper sheet due to a variety of reasons. In this paper, we provide an online mapping technique based on estimating the cross-correlation between actuator movement and the measurements. This procedure involves two steps–in the first step (called alignment monitoring) we determine if the current mapping is wrong at any CD position, and in the second step (called re-mapping), the alignment of actuators is corrected. The main advantage of this method is in its ability to re-align under closed loop conditions with minimal operational disruption.

Organic acid is an important factor that accelerates the aging of cellulosic insulation materials. In this study, the interactions between cellulose and five acids, representative of what may be found in an aging transformer, were studied using molecular dynamics. The adsorption process of the five acids onto the surface of crystalline cellulose shows that the three low molecular acids are more readily adsorbed onto cellulose than the two high molecular acids. The deformation and adsorption energies of the acids all increase with an increase in molecular weight when they are stably interacting with cellulose. However, the differences between adsorption energies and deformation energies are positive for the three low molecular acids, whereas they are negative for the two high molecular acids. This indicates that the attachments onto cellulose of low molecular acids are considerably more stabilized than those of the high molecular acids. This is consistent with the experimental results. Furthermore, based on the calculated solubility parameters of acids, the experimental result that the three low molecular acids are to a large degree absorbed onto the cellulose, whereas the two high molecular acids remain in the oil, was theoretically elucidated using the theory of similarity and intermiscibility.

The aim of this study was to compare the depiction ability of small grayscale contrasts in ink-jet printouts of digital radiographs on different print media with CRT monitor. A CCD-based digital cephalometric image of a stepless aluminum wedge containing 50 bur holes of different depth was cut into 100 isometric images. Each image was printed on glossy paper and on transparent film by means of a high-resolution desktop inkjet printer at specific settings. The printed images were viewed under standardized conditions, and the perceptibility of the bur holes was evaluated and compared to the perceptibility on a 17-in CRT monitor. Thirty observers stated their blinded decision on a five-point confidence scale. Areas (Az) under receiver operating characteristics curves were calculated and compared using the pair wise sign tests. Overall agreement was estimated using Cohen’s kappa device and observer bias using McNemar’s test. Glossy paper prints and monitor display revealed significantly higher (P

Good scientific writing is essential to career development and to the progress of science. A well-structured manuscript allows readers and reviewers to get excited about the subject matter, to understand and verify the paper’s contributions, and to integrate these contributions into a broader context. However, many scientists struggle with producing high-quality manuscripts and typically get little training in paper writing. Focusing on how readers consume information, we present a set of 10 simple rules to help you get across the main idea of your paper. These rules are designed to make your paper more influential and the process of writing more efficient and pleasurable.

Cyclic dominance of three species is a commonly occurring interaction dynamics, often denoted the rock-paper-scissors (RPS) game. Such a type of interactions is known to promote species coexistence. Here, we generalize recent results of Reichenbach et al. [Nature (London) 448, 1046 (2007)] of a four-state variant of the RPS game. We show that spiral formation takes place only without a conservation law for the total density. Nevertheless, in general, fast diffusion can destroy species coexistence. We also generalize the four-state model to slightly varying reaction rates. This is shown both analytically and numerically not to change pattern formation, or the effective wavelength of the spirals, and therefore not to alter the qualitative properties of the crossover to extinction.

Blank-slate theories of human intelligence propose that reasoning is carried out by general-purpose operations applied uniformly across contents. An evolutionary approach implies a radically different model of human intelligence. The task demands of different adaptive problems select for functionally specialized problem-solving strategies, unleashing massive increases in problem-solving power for ancestrally recurrent adaptive problems. Because exchange can evolve only if cooperators can detect cheaters, we hypothesized that the human mind would be equipped with a neurocognitive system specialized for reasoning about social exchange. Whereas humans perform poorly when asked to detect violations of most conditional rules, we predicted and found a dramatic spike in performance when the rule specifies an exchange and violations correspond to cheating. According to critics, people's uncanny accuracy at detecting violations of social exchange rules does not reflect a cheater detection mechanism, but extends instead to all rules regulating when actions are permitted (deontic conditionals). Here we report experimental tests that falsify these theories by demonstrating that deontic rules as a class do not elicit the search for violations. We show that the cheater detection system functions with pinpoint accuracy, searching for violations of social exchange rules only when these are likely to reveal the presence of someone who intends to cheat. It does not search for violations of social exchange rules when these are accidental, when they do not benefit the violator, or when the situation would make cheating difficult.

Idiopathic pulmonary fibrosis (IPF) is a fatal progressive lung disease occurring in adults. In the last decade, the results of a number of clinical trials based on the updated disease classification have been published. The registration of pirfenidone and nintedanib, the first two pharmacological treatment options approved for IPF, marks a new chapter in the management of patients with this disease. Other nonpharmacological treatments such as lung transplantation, rehabilitation and palliation have also been shown to be beneficial for these patients. In this review, past and present management is discussed based on a comprehensive literature search. A treatment algorithm is presented based on available evidence and our overall clinical experience. In addition, unmet needs with regard to treatment are highlighted and discussed. We describe the development of various treatment options for IPF from the first consensus to recent guidelines based on evidence from large-scale, multinational, randomized clinical trials, which have led to registration of the first drugs for IPF.

Objective To evaluate the design characteristics of studies that evaluated the performance of artificial intelligence (AI) algorithms for the diagnostic analysis of medical images. Materials and methods PubMed MEDLINE and Embase databases were searched to identify original research articles published between January 1, 2018 and August 17, 2018 that investigated the performance of AI algorithms that analyze medical images to provide diagnostic decisions. Eligible articles were evaluated to determine 1) whether the study used external validation rather than internal validation, and in case of external validation, whether the data for validation were collected, 2) with diagnostic cohort design instead of diagnostic case-control design, 3) from multiple institutions, and 4) in a prospective manner. These are fundamental methodologic features recommended for clinical validation of AI performance in real-world practice. The studies that fulfilled the above criteria were identified. We classified the publishing journals into medical vs. non-medical journal groups. Then, the results were compared between medical and non-medical journals. Results Of 516 eligible published studies, only 6% (31 studies) performed external validation. None of the 31 studies adopted all three design features: diagnostic cohort design, the inclusion of multiple institutions, and prospective data collection for external validation. No significant difference was found between medical and non-medical journals. Conclusion Nearly all of the studies published in the study period that evaluated the performance of AI algorithms for diagnostic analysis of medical images were designed as proof-of-concept technical feasibility studies and did not have the design features that are recommended for robust validation of the real-world clinical performance of AI algorithms.

An Electronic Portable Information Collection audio device (EPIC-Vox) has been developed to deliver questionnaires in spoken word format via headphones. Patients respond by pressing buttons on the device. The aims of this study were to determine limits of agreement between, and test-retest reliability of audio (A) and paper (P) versions of the Brief Fatigue Inventory (BFI). Two hundred sixty outpatients (204 male, mean age 55.7 years) attending a sleep disorders clinic were allocated to four groups using block randomization. All completed the BFI twice, separated by a one-minute distracter task. Half the patients completed paper and audio versions, then an evaluation questionnaire. The remainder completed either paper or audio versions to compare test-retest reliability. BFI global scores were analyzed using Bland-Altman methodology. Agreement between categorical fatigue severity scores was determined using Cohen's kappa. The mean (SD) difference between paper and audio scores was −0.04 (0.48). The limits of agreement (mean difference±2SD) were −0.93 to +1.00. Test-retest reliability of the paper BFI showed a mean (SD) difference of 0.17 (0.32) between first and second presentations (limits −0.46 to +0.81). For audio, the mean (SD) difference was 0.17 (0.48) (limits −0.79 to +1.14). For agreement between categorical scores, Cohen's kappa=0.73 for P and A, 0.67 (P at test and retest) and 0.87 (A at test and retest). Evaluation preferences (n=128): 36.7% audio; 18.0% paper; and 45.3% no preference. A total of 99.2% found EPIC-Vox "easy to use." These data demonstrate that the English audio version of the BFI provides an acceptable alternative to the paper questionnaire.

BACKGROUND Surveillance of multiple congenital anomalies is considered to be more sensitive for the detection of new teratogens than surveillance of all or isolated congenital anomalies. Current literature proposes the manual review of all cases for classification into isolated or multiple congenital anomalies. METHODS Multiple anomalies were defined as two or more major congenital anomalies, excluding sequences and syndromes. A computer algorithm for classification of major congenital anomaly cases in the EUROCAT database according to International Classification of Diseases (ICD)v10 codes was programmed, further developed, and implemented for 1 year's data (2004) from 25 registries. The group of cases classified with potential multiple congenital anomalies were manually reviewed by three geneticists to reach a final agreement of classification as “multiple congenital anomaly” cases. RESULTS A total of 17,733 cases with major congenital anomalies were reported giving an overall prevalence of major congenital anomalies at 2.17%. The computer algorithm classified 10.5% of all cases as “potentially multiple congenital anomalies”. After manual review of these cases, 7% were agreed to have true multiple congenital anomalies. Furthermore, the algorithm classified 15% of all cases as having chromosomal anomalies, 2% as monogenic syndromes, and 76% as isolated congenital anomalies. The proportion of multiple anomalies varies by congenital anomaly subgroup with up to 35% of cases with bilateral renal agenesis. CONCLUSIONS The implementation of the EUROCAT computer algorithm is a feasible, efficient, and transparent way to improve classification of congenital anomalies for surveillance and research. Birth Defects Research (Part A), 2011. © 2011 Wiley-Liss, Inc.

Improved medical care of congenital heart disease patients increased survival into adulthood from 15% in the 1960s to over 85% in the current era. As a consequence, the prevalence of adult congenital heart disease (ACHD) increased rapidly,1 which is estimated to be >1 million ACHD patients in North America and 1.2 million in Europe. The growing number and aging of ACHD patients led to an overall increase in hospitalizations over the last decade and a substantial increase in patients presenting with heart failure (HF) (∼20%).2 The incidence of first HF-admission was 1.2 per 1000 patient-years in the Dutch national ‘CONCOR’ registry. Patients admitted with HF had a five-fold higher risk of death than those not admitted. From the same registry, the mortality was 2.8% during a follow-up period of 24 865 patient-years. Chronic HF (26%) and sudden death (19%) were recorded most frequently. The median age at death from HF was 51.0 years (range: 20.3–91.2 years).3 In another ACHD cohort, sudden death (26%) was the most common cause of death, followed by progressive HF (21%) and perioperative death (18%).4 Although patients with ACHD may not readily report symptoms, clinical HF is documented in 22.2% of patients with a Mustard repair for transposition of the great arteries (TGAs), 32.3% with congenitally corrected transposition of the great arteries (ccTGA), and 40% of patients after Fontan palliation. ### Heart failure with impaired systolic ventricular function The aetiology and triggers of impaired systolic ventricular function in ACHD patients are summarized in Table 1 . View this table: Table 1 Pathophysiology of heart failure with impaired systolic function: triggers (examples) ### Heart failure with preserved systolic ventricular function This occurs less often in ACHD patients, but is associated with specific conditions such as Shone complex and restrictive …

Motivation: Converting the vast quantity of free-format text found in journals into a concise, structured format makes the researcher's quest for information easier. Recently, several information extraction systems have been developed that attempt to simplify the retrieval and analysis of biological and medical data. Most of this work has used the abstract alone, owing to the convenience of access and the quality of data. Abstracts are generally available through central collections with easy direct access (e.g. PubMed). The full-text papers contain more information, but are distributed across many locations (e.g. publishers' web sites, journal web sites and local repositories), making access more difficult. In this paper, we present BioRAT, a new information extraction (IE) tool, specifically designed to perform biomedical IE, and which is able to locate and analyse both abstracts and full-length papers. BioRAT is a Biological Research Assistant for Text mining, and incorporates a document search ability with domain-specific IE. Results: We show first, that BioRAT performs as well as existing systems, when applied to abstracts; and second, that significantly more information is available to BioRAT through the full-length papers than via the abstracts alone. Typically, less than half of the available information is extracted from the abstract, with the majority coming from the body of each paper. Overall, BioRAT recalled 20.31% of the target facts from the abstracts with 55.07% precision, and achieved 43.6% recall with 51.25% precision on full-length papers. Availability: The software and documentation can be found at http://bioinf.cs.ucl.ac.uk/biorat

We explore the application of terahertz spectroscopic techniques for the remote determination of the water content of paper. The aim is the development of a rapid diagnostic imaging tool applicable in paper fabrication processes. THz radiation offers a high sensitivity for water, a good spatial resolution, and insensitivity to scattering at the paper surface. The advent of THz cameras makes fast large-area image detectors feasible. In this paper, we show for the case of a 0.6-THz fixed-frequency system, that the water content of paper can be determined with high accuracy. We demonstrate a quantitative (calibrated) method for determining the moisture content in paper based on extinction and phase measurements in the lower THz range with a spatial resolution in the mm-range and scanning times below two minutes.

Research paper recommenders emerged over the last decade to ease finding publications relating to researchers' area of interest. The challenge was not just to provide researchers with very rich publications at any time, any place and in any form but to also offer the right publication to the right researcher in the right way. Several approaches exist in handling paper recommender systems. However, these approaches assumed the availability of the whole contents of the recommending papers to be freely accessible, which is not always true due to factors such as copyright restrictions. This paper presents a collaborative approach for research paper recommender system. By leveraging the advantages of collaborative filtering approach, we utilize the publicly available contextual metadata to infer the hidden associations that exist between research papers in order to personalize recommendations. The novelty of our proposed approach is that it provides personalized recommendations regardless of the research field and regardless of the user's expertise. Using a publicly available dataset, our proposed approach has recorded a significant improvement over other baseline methods in measuring both the overall performance and the ability to return relevant and useful publications at the top of the recommendation list.

WOS: 000356799600005, PubMed ID: 25999021, Acute heart failure is a fatal syndrome. Emergency physicians, cardiologists, intensivists, nurses and other health care providers have to cooperate to provide optimal benefit. However, many treatment decisions are opinion-based and few are evidenced-based. This consensus paper provides guidance to practicing physicians and nurses to manage acute heart failure in the pre-hospital and hospital setting. Criteria of hospitalization and of discharge are described. Gaps in knowledge and perspectives in the management of acute heart failure are also detailed. This consensus paper on acute heart failure might help enable contiguous practice., Bayer; Cardiorentis; Medicine Company; Critical Diagnostics; Novartis; Steering Committee member of Cardiorentis; TUBITAK; Medicines Company; Cornerstone Therapeutics; Otsuka; Janssen; Apex Innovations; Inte-Section Medical; Trevena; Vifor Pharma Ltd; Amgen; Servier; Abbott Vascular; Coridea; Respicardia; Swiss National Science Foundation; Swiss Heart Foundation; Cardiovascular Research Foundation Basel; 8sense; Abbott; ALERE; Brahms; Nanosphere; Roche; Siemens; University Hospital Basel; Astra Zeneca; BG medicine; Biomerieux; Lilly; Orion; Resmed; Roche Diagnostics; Ratiopharm; BMS; Boehringer-Ingelheim; Pfizer; Daiichi Sankyo; Boehinger Ingelheim; AstraZeneca; European Union, A.M. received speaker's honoraria from Alere, Bayer, Edwards Life Sciences, The Medicines Company, Novartis, Orion, Servier, Thermofisher, Vifor Pharma and also received fee as member of advisory board and/or Steering Committee from Bayer, Cardiorentis, The Medicine Company, Critical Diagnostics.; M.B.Y. received speaker's honoraria and research fee from Novartis and received fee as Steering Committee member of Cardiorentis, and is supported by TUBITAK.; P.L. received speaker's honoraria from Beckman Coulter and Novartis and also received fees as a member of advisory board and/or Steering Committee from Bayer, Cardiorentis, The Medicines Company, Cornerstone Therapeutics, Novartis, Otsuka, Janssen, Apex Innovations, Inte-Section Medical, and Trevena.; P.P. received speaker's honoraria from Bayer, Novartis, Servier, Vifor Pharma, Amgen, Pfizer, Cardiorentis, Merck-Serono, Abbott Vascular and Respicardia and also received fee as member of advisory board and/or Steering Committee from Bayer, Cardiorentis, Novartis, Vifor Pharma Ltd, Amgen, Servier, Abbott Vascular, Coridea and Respicardia.; E.L. received consultancy fee from Novartis.; J.M. received honoraria for speaker or advisor from Abbott, Novartis, Orion, Otsuka, and Sanofi and fee as a member of Steering Committee from Corthera, Novartis, and Cardiorentis.; C.M. received research grants from the Swiss National Science Foundation and the Swiss Heart Foundation, the Cardiovascular Research Foundation Basel, 8sense, Abbott, ALERE, Brahms, Critical Diagnostics, Nanosphere, Roche, Siemens, and the University Hospital Basel, as well as speaker/consulting honoraria from Astra Zeneca, Abbott, ALERE, BG medicine, Biomerieux, Brahms, Cardiorentis, Lilly, Novartis, Pfizer, Roche, and Siemens.; V.P.H. received speaker's fee: Bayer, Orion, Resmed, Roche Diagnostics, Ratiopharm; consultation fees: Bayer, BMS, Boehringer-Ingelheim, Novartis, Pfizer, Roche Diagnostics, Servier. H.A.T. received speaker's honoraria from Daiichi Sankyo, Lilly, Medicines Company, AstraZeneca, Boehinger Ingelheim. Advisory board for Maquet Cardiovascular. Institutional research support by Maquet Cardiovascular, Teleflex, Terumo, Lilly, The Medicine Company.; G.F. has received research grants and/or has served as Committee member or Cochair of studies sponsored by Bayer, Novartis, Cardiorentis, Vifor Pharma, and the European Union.