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Riback et al. (Reports, 13 October 2017, p. 238) used small-angle x-ray scattering (SAXS) experiments to infer a degree of compaction for unfolded proteins in water versus chemical denaturant that is highly consistent with the results from Forster resonance energy transfer (FRET) experiments. There is thus no "contradiction" between the two methods, nor evidence to support their claim that commonly used FRET fluorophores cause protein compaction.
In this Comment, we review the results of pattern formation in a reaction-diffusion-advection system following the kinetics of the Gray-Scott model. A recent paper by Das [Phys. Rev. E 92, 052914 (2015)] shows that spatiotemporal chaos of the intermittency type can disappear as the advective flow is increased. This study, however, refers to a single point in the space of kinetic parameters of the original Gray-Scott model. Here we show that the wealth of patterns increases substantially as some of these parameters are changed. In addition to spatiotemporal intermittency, defect-mediated turbulence can also be found. In all cases, however, the chaotic behavior is seen to disappear as the advective flow is increased, following a scenario similar to what was reported in our earlier work [I. Berenstein and C. Beta, Phys. Rev. E 86, 056205 (2012)] as well as by Das. We also point out that a similar phenomenon can be found in other reaction-diffusion-advection models, such as the Oregonator model for the Belousov-Zhabotinsky reaction under flow conditions.
À partir des travaux des ethnologues qui ont décrit le fonctionnement des sociétés paysannes de l’Ancien Régime, nous montrons dans cet article comment le récit de l’enfance bretonne de Chateaubriand dans les ‚Mémoires d’outre-tombe‘ obéit à une logique initiatique qui donne à l’animal un rôle de premier plan. Transformée en véritable „aventure“, la capture des oiseaux devient pour l’enfant l’occasion de forger son caractère et de découvrir le sens de l’honneur, tandis que la contemplation de leur envol éveille en lui le goût des voyages qu’il n’a pas encore la possibilité d’assouvir. À Combourg, chouettes et chat noir peuplent les nuits de l’enfant et l’obligent à dompter ses peurs. Quant au cheval, que Chateaubriand a mal appris à maîtriser, il devient sous sa plume l’emblème d’une époque révolue dominée par les privilèges de l’aristocratie et le signe de l’inadaptation des derniers rois de France. Il restera à l’écrivain à s’emparer de cette familiarité avec le monde animal pour nourrir son imaginaire et sa sensibilité de plus en plus grande au sort que lui réserve la société.
Modern production infrastructures of globally operating companies usually consist of multiple distributed production sites. While the organization of individual sites consisting of Industry 4.0 components itself is demanding, new questions regarding the organization and allocation of resources emerge considering the total production network. In an attempt to face the challenge of efficient distribution and processing both within and across sites, we aim to provide a hybrid simulation approach as a first step towards optimization. Using hybrid simulation allows us to include real and simulated concepts and thereby benchmark different approaches with reasonable effort. A simulation concept is conceptualized and demonstrated qualitatively using a global multi-site example.
In the comment on "Varves of the Dead Sea sedimentary record." Quaternary Science Reviews 215 (Ben Dor et al., 2019): 173-184. by R. Bookman, two recently published papers are suggested to prove that the interpretation of the laminated sedimentary sequence of the Dead Sea, deposited mostly during MIS2 and Holocene pluvials, as annual deposits (i.e., varves) is wrong. In the following response, we delineate several lines of evidence which coalesce to demonstrate that based on the vast majority of evidence, including some of the evidence provided in the comment itself, the interpretation of these sediments as varves is the more likely scientific conclusion. We further discuss the evidence brought up in the comment and its irrelevance and lack of robustness for addressing the question under discussion.
Operational decisions in business processes can be modeled by using the Decision Model and Notation (DMN). The complementary use of DMN for decision modeling and of the Business Process Model and Notation (BPMN) for process design realizes the separation of concerns principle. For supporting separation of concerns during the design phase, it is crucial to understand which aspects of decision-making enclosed in a process model should be captured by a dedicated decision model. Whereas existing work focuses on the extraction of decision models from process control flow, the connection of process-related data and decision models is still unexplored. In this paper, we investigate how process-related data used for making decisions can be represented in process models and we distinguish a set of BPMN patterns capturing such information. Then, we provide a formal mapping of the identified BPMN patterns to corresponding DMN models and apply our approach to a real-world healthcare process.
In university teaching today, it is common practice to record regular lectures and special events such as conferences and speeches. With these recordings, a large fundus of video teaching material can be created quickly and easily. Typically, lectures have a length of about one and a half hours and usually take place once or twice a week based on the credit hours. Depending on the number of lectures and other events recorded, the number of recordings available is increasing rapidly, which means that an appropriate form of provisioning is essential for the students. This is usually done in the form of lecture video platforms. In this work, we have investigated how lecture video platforms and the contained knowledge can be improved and accessed more easily by an increasing number of students. We came up with a multistep process we have applied to our own lecture video web portal that can be applied to other solutions as well.
Traditional economic theory could not explain, much less predict, the near collapse of the financial system and its long-lasting effects on the global economy. Since the 2008 crisis, there has been increasing interest in using ideas from complexity theory to make sense of economic and financial markets. Concepts, such as tipping points, networks, contagion, feedback, and resilience have entered the financial and regulatory lexicon, but actual use of complexity models and results remains at an early stage. Recent insights and techniques offer potential for better monitoring and management of highly interconnected economic and financial systems and, thus, may help anticipate and manage future crises.
Detecting and recognizing text in natural scene images is a challenging, yet not completely solved task. In recent years several new systems that try to solve at least one of the two sub-tasks (text detection and text recognition) have been proposed. In this paper we present SEE, a step towards semi-supervised neural networks for scene text detection and recognition, that can be optimized end-to-end. Most existing works consist of multiple deep neural networks and several pre-processing steps. In contrast to this, we propose to use a single deep neural network, that learns to detect and recognize text from natural images, in a semi-supervised way. SEE is a network that integrates and jointly learns a spatial transformer network, which can learn to detect text regions in an image, and a text recognition network that takes the identified text regions and recognizes their textual content. We introduce the idea behind our novel approach and show its feasibility, by performing a range of experiments on standard benchmark datasets, where we achieve competitive results.