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Rethinking Movement Portrayal: Recurring Frames Along with Animations ConvNets.
Although transcription by RNA polymerase (RNAP) is highly processive, elongation can be transiently halted by RNAP pausing. Pausing provides time for diverse regulatory events to occur such as RNA folding and regulatory factor binding. The transcription elongation factors NusA and NusG dramatically affect the frequency and duration of RNAP pausing, and hence regulation of transcription. NusG is the only transcription factor conserved in all three domains of life; its homolog in archaea and eukaryotes is Spt5. PIM447 molecular weight This review focuses on NusG-dependent pausing, which is a common occurrence in Bacillus subtilis. B. NusG induces pausing about once per 3 kb at a consensus TTNTTT motif in the non-template DNA strand within the paused transcription bubble. A conserved region of NusG contacts the TTNTTT motif to stabilize the paused transcription elongation complex (TEC) in multiple catalytically inactive RNAP conformations. The density of NusG-dependent pause sites is 3-fold higher in untranslated regions, suggesting that pausing could regulate the expression of hundreds of genes in B. subtilis. We describe how pausing in 5' leader regions contributes to regulating the expression of B. subtilis genes by transcription attenuation and translation control mechanisms. As opposed to the broadly accepted view that NusG is an anti-pausing factor, phylogenetic analyses suggest that NusG-dependent pausing is a widespread mechanism in bacteria. This function of NusG is consistent with the well-established role of its eukaryotic homolog Spt5 in promoter-proximal pausing. Since NusG is present in all domains of life, NusG-dependent pausing could be a conserved mechanism in all organisms.Introduction As many as 12.5% of patients who undergo ureteral stent placement fail to have their stent removed in a timely manner. Because retained stents can be a source of substantial morbidity, there is a need for solutions to help urologists track their stented patients. Materials and Methods We developed a cloud-based software that is agnostic to the device manufacturer and can be seamlessly integrated into the electronic health record (EHR). The software automatically registers patients who undergo ureteral stent placement and then follows them through their postoperative course to ensure timely follow-up for device removal. To validate our software's performance, we reviewed the medical records of patients who underwent stent placement for any indication at our institution between February 1, 2018, and February 28, 2018. Results During our 1-month pilot study, a total of 51 ureteral stents were placed during 49 procedures that were performed on 46 patients. Our software effectively captured all of these procedures. It was able to properly distinguish 31 procedures where the patient who underwent stenting had follow-up scheduled before surgery. More importantly, it alerted our schedulers to 18 procedures for which no return visit had been scheduled. Furthermore, our software was able to register follow-up attendance, correctly identifying 10 procedures where patients failed to arrive. Conclusion We describe a high-fidelity software solution for automated tracking of ureteral stents that is agnostic to the device manufacturer and can be seamlessly integrated into the EHR, causing minimal disruption to provider workflows.Students are often reluctant to report the academic dishonesty of their peers. Loyalty to friends and classmates has previously been identified as an important reason for this. This paper explores loyalty conflicts among students from upper secondary school, through bachelor's, to Ph.D. level. Drawing on semi-structured qualitative interviews (N = 72) conducted in Denmark, Ireland and Hungary, we show that loyalty considerations among students can be complex and draw on a range of norms including responsibility. The study demonstrates how students are often willing to assume substantial personal responsibility for dealing with the academic dishonesty of a peer, often preferring this to reporting. However, when deciding on the right course of action, they also perceive tensions between the norms of the good researcher and student and their own norms of being a good friend and person. The loyalty considerations and tension were identified in all three countries and across the educational levels, which suggests that this is a cross-cultural challenge. We argue that institutions should formally decide whether they want students to take some degree of responsibility themselves for addressing less serious cases of academic dishonesty and communicate their decision to their students.There has been much recent interest in the protein "corona," the nonspecific adsorption of proteins on the surface of nanoparticles used in biological applications. This research investigates an analogous DNA corona. We find that particles (200 nm and 1 μm) incubated with DNA form a DNA corona, with a higher concentration of DNA adsorbed on the surface of cationic nanoparticles. With protein present, a combined DNA and protein corona is formed although DNA in solution displaces protein from the nanoparticle surface. Displacement of protein from the nanoparticle surface is dependent on the concentration of DNA in solution and was also observed for planar surfaces. Overall, we expect this investigation of the DNA corona to be important for nanomedicine applications, as well as disease states, especially systemic lupus erythematosus, in which biological particles with bound DNA are important mediators of inflammation and thrombosis.Multiple models have been proposed to describe the epidemic spreading in the presence of interactions between two or more infectious diseases, but less is known about how dynamical aspects, such as time scales of diseases, affect the epidemic spreading. In this work, we evaluate the time shift produced in the number of people infected from one disease when interacting with another disease. Using a compartmental model, we produce different forms of relationship as competition, cooperation, and independence, assessing the effect of each one in the final result. We focus on the case of the unidirectional coupling between diseases, which enables us to study the impact of a perturbation to a driving disease on the driven one. We found that the prevalence of the driven disease is strongly affected if its time scale, defined by the time where the infection reaches the peak, is comparable to that of the driving disease. The secondary peak of the infection was observed under cooperative coupling if the time scale of the driving disease is much longer than that of the driven one.The deep time-delay reservoir computing concept utilizes unidirectionally connected systems with time-delays for supervised learning. We present how the dynamical properties of a deep Ikeda-based reservoir are related to its memory capacity (MC) and how that can be used for optimization. In particular, we analyze bifurcations of the corresponding autonomous system and compute conditional Lyapunov exponents, which measure generalized synchronization between the input and the layer dynamics. We show how the MC is related to the systems' distance to bifurcations or magnitude of the conditional Lyapunov exponent. The interplay of different dynamical regimes leads to an adjustable distribution between the linear and nonlinear MC. Furthermore, numerical simulations show resonances between the clock cycle and delays of the layers in all degrees of MC. Contrary to MC losses in single-layer reservoirs, these resonances can boost separate degrees of MC and can be used, e.g., to design a system with maximum linear MC. Accordingly, we present two configurations that empower either high nonlinear MC or long time linear MC.We show that the effect of the offset phase on the dynamics of the time-delay optoelectronic oscillators that is observed experimentally can be explained in terms of switching between the subcritical and supercritical Hopf bifurcations. The domains of the offset phase for which the system functions are determined analytically. We also show that the width of these domains exceptionally depends on the interplay between the three time scales of the system. Our theoretical results fit with the experimental measurements.In the present work, we analyze the emergence of fashion cycles and complex phenomena in a discrete time dynamic model in which a population is divided into two groups, bandwagoners and snobs. Both groups react differently to the aggregate demand for goods in the previous period and, in particular, bandwagoners imitate the consumption styles prevailing in society, while snobs try to distinguish themselves from them. We consider a first specification of the model in which the structure of the population is fixed and we show how in the case of polymorphic population it is possible to observe cyclical behaviors in collective consumption and the onset of chaotic regimes. We further propose an extension of the model in which we investigate the interdependence between the evolution of collective consumption choices and the evolution of the structure of the groups in a framework in which individuals may change the structure of preferences and then switch between being of one type or another. In the extension, we analyze how both consumption cycles (and then fashion cycles) and the evolution of the groups may lead to the emergence of chaotic dynamics, as well as the coexistence of attractors.We stabilize a prescribed cycle or an equilibrium of a difference equation using pulsed stochastic control. Our technique, inspired by Kolmogorov's law of large numbers, activates a stabilizing effect of stochastic perturbation and allows for stabilization using a much wider range for the control parameter than would be possible in the absence of noise. Our main general result applies to both prediction-based and target-oriented controls. This analysis is the first to make use of the stabilizing effects of noise for prediction-based control; the stochastic version has previously been examined in the literature, but only the destabilizing effect of noise was demonstrated. A stochastic variant of target-oriented control has never been considered, to the best of our knowledge, and we propose a specific form that uses a point equilibrium or one point on a cycle as a target. We illustrate our results numerically on the logistic, Ricker, and Maynard Smith models from population biology.In order to elucidate central elements underlying type 2 diabetes, we constructed a regulatory network model involving 37 components (molecules, receptors, processes, etc.) associated to signaling pathways of pancreatic beta-cells. In a first approximation, the network topology was described by Boolean rules whose interacting dynamics predicted stationary patterns broadly classified as health, metabolic syndrome, and diabetes stages. A subsequent approximation based on a continuous logic analysis allowed us to characterize the progression of the disease as transitions between these states associated to alterations of cell homeostasis due to exhaustion or exacerbation of specific regulatory signals. The method allowed the identification of key transcription factors involved in metabolic stress as essential for the progression of the disease. Integration of the present analysis with existent mathematical models designed to yield accurate account of experimental data in human or animal essays leads to reliable predictions for beta-cell mass, insulinemia, glycemia, and glycosylated hemoglobin in diabetic fatty rats.
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