Continuous Drift Research Articles

Human-to-swine introductions and onward transmission of 2009 H1N1 pandemic influenza viruses in Brazil.

Once established in the human population, the 2009 H1N1 pandemic virus (H1N1pdm09) was repeatedly introduced into swine populations globally with subsequent onward transmission among pigs. To identify and characterize human-to-swine H1N1pdm09 introductions in Brazil, we conducted a large-scale phylogenetic analysis of 4,141 H1pdm09 hemagglutinin (HA) and 3,227 N1pdm09 neuraminidase (NA) gene sequences isolated globally from humans and swine between 2009 and 2022. Phylodynamic analysis revealed that during the period between 2009 and 2011, there was a rapid transmission of the H1N1pdm09 virus from humans to swine in Brazil. Multiple introductions of the virus were observed, but most of them resulted in self-limited infections in swine, with limited onward transmission. Only a few sustained transmission clusters were identified during this period. After 2012, there was a reduction in the number of human-to-swine H1N1pdm09 transmissions in Brazil. The virus underwent continuous antigenic drift, and a balance was established between swine-to-swine transmission and extinction, with minimal sustained onward transmission from humans to swine. These results emphasize the dynamic interplay between human-to-swine transmission, antigenic drift, and the establishment of swine-to-swine transmission in shaping the evolution and persistence of H1N1pdm09 in swine populations.

Emergence of ATP‐ and GTP‐Binding Aptamers from Single RNA Sequences by Error‐Prone Replication and Selection**

AbstractThe spontaneous emergence of function from diverse RNA sequence pools is widely considered an important transition in the origin of life. Here we show that diverse sequence pools are not a prerequisite for the emergence of function. Starting five independent selection experiments each from a single RNA seed sequence ‐ comprising a central homopolymeric poly‐A (or poly‐U) segment flanked by different conserved primer binding sites ‐ we observe transformation (continuous drift) of the seeds into low diversity sequence pools by mutation, truncation and recombination without ever reaching that of a random pool even after 24 rounds. Upon continuous error prone replication and selection for ATP binding we isolate specific ATP‐ or GTP‐binding aptamers with low micromolar affinities. Our results have implications for early RNA evolution in the light of the high mutation rates associated with both non‐enzymatic and enzymatic prebiotic RNA replication.

Joint PMD Tracking and Nonlinearity Compensation With Deep Neural Networks

Overcoming fiber nonlinearity is one of the core challenges limiting the capacity of optical fiber communication systems. Machine learning based solutions such as learned digital backpropagation (LDBP) and the recently proposed deep convolutional recurrent neural network (DCRNN) have been shown to be effective for fiber nonlinearity compensation (NLC). Incorporating distributed compensation of polarization mode dispersion (PMD) within the learned models can improve their performance even further but at the same time, it also couples the compensation of nonlinearity and PMD. Consequently, it is important to consider the time variation of PMD for such a joint compensation scheme. In this paper, we investigate the impact of PMD drift on the DCRNN model with distributed compensation of PMD. We propose a transfer learning based selective training scheme to adapt the learned neural network model to changes in PMD. We demonstrate that fine-tuning only a small subset of weights as per the proposed method is sufficient for adapting the model to PMD drift. Using decision directed feedback for online learning, we track continuous PMD drift resulting from a time-varying rotation of the state of polarization (SOP). We show that transferring knowledge from a pre-trained base model using the proposed scheme significantly reduces the re-training efforts for different PMD realizations. Applying the hinge model for SOP rotation, our simulation results show that the learned models maintain their performance gains while tracking the PMD.

Strong Averaging Principle for a Class of Slow-fast Singular SPDEs Driven by α-stable Process

In this paper, the strong averaging principle is researched for a class of Hölder continuous drift slow-fast SPDEs with α-stable process by the Zvonkin’s transformation and the classical Khasminskii’s time discretization method. As applications, an example is also provided to explain our result.

Pathwise unstable invariant manifolds reduction for stochastic evolution equations driven by nonlinear noise

This paper is concerned with the pathwise dynamics of the stochastic evolution equation: du + Audt = F(u)dt + G(u)dW(t) on a separable Hilbert space H with the Lipschitz continuous drift term F(u) as well as the Lipschitz continuous diffusion term G(u). We first introduce the notion of generalized random dynamical systems (GRDSs) and show that the equation can generate a GRDS. We then construct a pathwise unstable manifold for the GRDS provided that the Lipschitz constants of the drift term and the diffusion term satisfy a spectral gap condition. At last, we present a pathwise unstable manifold reduction for the GRDS.

Liquid consumption and Islam: The Continual Drift Adjustment (CDA) framework

PurposeThe purpose of this paper is to explore the tendencies of liquid consumption in Muslim communities and analyse its impact on Muslims’ consumption practices from the holistic perspective. Liquid consumption refers to a transient and less-materialised mode of consumption that requires both minimal attachment to possessions and hybrid ownership.Design/methodology/approachThis is a conceptual paper that is based on the distinction between Islam as a holistic perspective and Islamic practice as it is applied in different contexts and situations. The Continual Drift Adjustment (CDA) framework of Muslim consumers’ behaviour is developed to be deployed as an analysis framework.FindingsThe CDA framework maintains that some problematic cases of Muslim consumption behaviours indicate the drift towards disbalance. Depending on their nature, liquid consumption practices can have different impacts on the drift. Liquid consumption practices underscored by instrumental dissemblance, intellectual insecurity and spiritual scepticism intensify the drift, whereas the incorporation of spiritual sincerity, faithful submission and existential gratefulness into practices and behaviour helps to attenuate the drift.Research limitations/implicationsThis research contributes to the theory of liquid consumption by incorporating the religious perspective. Liquid consumption in Islam is a complex area of research, specifically considering the ambivalent meanings of liquidity in Islamic thought.Practical implicationsMarketers of liquid consumption solutions must be aware of these offerings’ double-edged impact on the well-being of Muslim communities. Muslim consumers should be guided towards spiritual sincerity, faithful submission and existential gratefulness in the best way possible, although it must be noted that the customary techniques of marketing would lean towards stimulating the disbalance.Originality/valueThis research is unique because it deals with a topic that has not been researched in the Islamic marketing discipline to this date.

DP-IINK: A Framework for Drift Prediction With Inter- and Intranode Knowledge Transfer With Less Data

A gas sensor provides a system with signals to monitor and respond to events that matter. However, some widely deployed sensors behave with drift, leading to inaccurate measurement. The system could malfunction due to the drift. Even more, if the system is not robust enough, the mistaken measurement could trigger some serious consequences. A drift prediction framework is necessary to contain this malfunction. On the other hand, when sensors are deployed in large quantities, it limits their maintenance cost, including the calibration cost. Data-driven frameworks show good potential for cheap calibration. But there are some challenges. First, sensor drift keeps occurring. The drift models need to be retrained over time. Second, the drift models for gas sensors of the same type cannot be a one-for-all way because they vary due to small manufacturing discrepancies. Third, drift models for a sensor could even be different only because the sensor is under different scenarios. In this article, we propose a new framework for drift prediction with inter- and intranode knowledge transfer (DP-IINK) for widely deployed low-cost gas sensors. Knowledge transfer is employed for inter- and intranode ways, as well as for continuous and discontinuous drift. Our evaluation shows that our proposed framework achieves a mean absolute percentage error (MAPE) as low as 5.18% for drift prediction with less data.

In situ enzymatic generation of Au/Pt nanoparticles as an analytical photometric system: proof of concept determination of tyramine

In situ enzymatic generation of bimetallic nanoparticles, mainly Au/Pt, overcomes the drawbacks (continuous absorbance drift, modest LOQ, and long-time reaction) observed when AuNP alone are produced. In this study, Au/Pt nanoparticles have been characterized by EDS, XPS, and HRTEM images using the enzymatic determination of tyramine with tyramine oxidase (TAO) as a model. Under experimental conditions, the Au/Pt NPs show an absorption maximum at 580 nm which can be related to the concentration of tyramine in the range 1.0 × 10-6M to 2.5 × 10-4M with a RSD of 3.4% (n = 5, using 5 × 10-6M tyramine). The Au/Pt system enables low LOQ (1.0 × 10−6 M), high reduction of the absorbance drift, and a significant shortening of the reaction time (i.e., from 30 to 2 min for a [tyramine] = 1 × 10−4M); additionally, a better selectivity is also obtained. The method has been applied to tyramine determination in cured cheese and no significant differences were obtained compared to a reference method (HRP:TMB). The effect of Pt(II) seems to involve the previous reduction of Au(III) to Au(I) and NP generation from this oxidation state. Finally, a three-step (nucleation-growth-aggregation) kinetic model for the generation of NPs is proposed; this has enabled us to obtain a mathematical equation which explains the experimentally observed variation of the absorbance with time.Graphical abstract

Divergence time of mites of the family Laelapidae based on mitochondrial barcoding region.

Using the mitochondrial barcoding region to correlate research with 58 species in 19 genera of the family Laelapidae with the aim of determining the origin, phylogenetic relationships, and biogeographic historical distribution characteristics of mites in the family Laelapidae. Phylogenetic trees were obtained using Bayesian inference (BI) and Maximum-likelihood (ML) methods, based on three fossil records calibrated as molecular clock nodes, to estimate the divergence time of mites in the family Laelapidae as well as to apply Dispersal-Extinction-Cladogenesis (DEC) analyses to obtain biogeographic history inferences. The result showed species of the genera Hyperlaelaps and Haemolaelaps and some species of the genus Androlaelaps in the family Laelapidae were divided into clades of the genus Laelaps in both the BI and ML trees. Divergence time estimates and biogeographic history analysis revealed that the family Laelapidae likely diverged from other taxa during the Middle Jurassic (ca. 156.73 Mya), with Asia considered the most likely ancestral region for the family Laelapidae. Species of various genera began to undergo massive diversification events during the Cenozoic Tertiary. The results suggest that some genera in the family Laelapidae need to be re-defined or new genera need to be established; the Late Cretaceous to Late Neogene warm period would have promoted the divergence and expansion of species in the family Laelapidae. The divergence and dispersal of the family Laelapidae species is most likely a joint response to the continued northward drift of the Indian plate away from the Gondwana paleo-continent and gradually closer to Asia during the Late Cretaceous and the geological activity of the Tibetan Plateau during the Cenozoic Tertiary. The results strengthen our understanding of the origin and evolution of species in the family Laelapidae.

REVERBERATION OF PANDEMIC MIGRANT FOOTPRINTS AND POLICY MANIFESTATION: A PROGRESSIVE STATE APPROACH OF NORTH-EAST INDIA

This is the defining moment of our generation. We are facing a global health crisis, one that is killing people, spreading human suffering, and upending people’s lives. The Covid-19 pandemic and sudden global lockdown across nations has brought migrant livelihoods to a halt. The headlines around Covid-19 are enough to scare us witless. The migrant crisis brought to the fore the unfulfilled obligations of the governments to restore work to its most vulnerable citizens in the era of economic liberalization. The migration debate has become central to political circle which largely involves rehearsing to false dichotomies whereas migrants are in continuous drift. Debate is just not restricted to utility of limited public funds. We have to create an ‘island of opportunities’ in this ‘ocean of distress’. The research poses the questions, namely: 1. How did immigration occur in North-east India? 2) How were the debates relating to migrants from North-east India? 3) How did the government of North-east India respond to the situation of migrants from North-east India during the Covid-19 pandemic? It was found and concluded that growing rural distress with agricultural failing leading to heavy debt burdens was the primary reason of immigration in North-east India. “The Assam Accord” signed between the “Government of India” and the “Leaders of the Assam Movement” in 1985 effectively legitimized all immigrants entering Assam before 24, December 1971. The SHG’s under National Rural Livelihoods Mission (NRLM) and Assam State Rural Livelihoods Mission (ASRLM) had adopted series of remedial measures during the Covid-19 pandemic for people, including migrants from North-east India.

Stochastic differential equation with piecewise continuous arguments: Markov property, invariant measure and numerical approximation

<p style='text-indent:20px;'>For the stochastic differential equation with piecewise continuous arguments, multiplicative noises and dissipative drift coefficients, we show that the solution at integer time is a Markov chain and admits a unique invariant measure. In order to numerically preserve the invariant measure, we apply the backward Euler method to the equation, and prove that the numerical solution at integer time is also a Markov chain and possesses a unique numerical invariant measure. By establishing several a priori estimations, we present the time-independent weak error analysis for the method via Malliavin calculus, which implies that the numerical invariant measure converges to the original one with weak order 1. Numerical experiments verify the theoretical analysis.</p>

Approximation of the invariant distribution for a class of ergodic SDEs with one-sided Lipschitz continuous drift coefficient using an explicit tamed Euler scheme

We study the behavior in a large time regime of an explicit tamed Euler-Maruyama scheme applied to a class of ergodic Ito stochastic differential equations with one-sided Lipschitz continuous drift coefficient and bounded globally Lipschitz diffusion coefficient. Our first main contribution is to prove moments for the numerical scheme, which, on the one hand, are uniform with respect to the time-step size, and which, on the other hand, may not be uniform but have at most polynomial growth with respect to time. Our second main contribution is to apply this result to obtain weak error estimates to quantify the error to approximate averages with respect to the invariant distribution of the continuous-time process, as a function of the time-step size and of the time horizon. The explicit tamed Euler scheme is shown to be computationally effective for the approximation of the invariant distribution: even if the moment bounds and error estimates are not proved to be uniform with respect to time, the obtained polynomial growth results in a marginal increase in the upper bound of the computational cost. To the best of our knowledge, this is the first result in the literature concerning the approximation of the invariant distribution for stochastic differential equations with non-globally Lipschitz coefficients using an explicit tamed Euler-Maruyama scheme.

Large deviation principle for distribution dependent S(P)DEs with singular drift

In this paper, we first prove that the large deviation principle is preserved under a homeomorphism. As an application, we establish the large deviation principle for distribution dependent stochastic differential equations with Dini continuous drift, semilinear distribution dependent stochastic partial differential equations with Dini continuous drift, respectively.

Drift of MEMS Capacitive Accelerometers for One-Year Room-Temperature Storage: A Simulation and Experimental Study

In this study, the drift of microelectromechanical system (MEMS) accelerometers stored at room temperature for one year is investigated by both finite-element analysis (FEA) simulation and experiments. In the simulation, a comprehensive FEA model considering the die-attach adhesive viscoelasticity was established to emulate the deformation of the sensor package structure during storage. Then drift models of the scale factor and bias of the accelerometer were built according to the deformed structure. To validate the simulation results, several accelerometers were packaged and their outputs were tested and recorded once per month. The two parameters displayed a continuous drift owing to the release of the packaging stress in the chip. The scale factor drifts were negative and about 2500 ppm for different types of sensors. However, the bias drifts were positive or negative, and their magnitudes were ranging from 12 to 32 mg in storage. Moreover, they reached a steady state after about ten months (< 50 ppm per month for the scale factor) and six months (< 1 mg per month for bias) of room-temperature storage. The results in this article provide meaningful guidance for the application of MEMS accelerometers.

Moderate deviations for the Langevin equations: Strong damping and fast Markovian switching

In this paper, we obtain a moderate deviations principle (MDP) for a class of Langevin dynamic systems with a strong damping and fast Markovian switching. To facilitate our study, first, analysis of systems with bounded drifts is dealt with. To obtain the desired moderate deviations, the exponential tightness of the solution of the Langevin equation is proved. Then, the solution of its first-order approximation using local MDPs is examined. Finally, the MDPs are established. To enable the treatment of unbounded drifts, a reduction technique is presented near the end of the paper, which shows that Lipschitz continuous drifts can be dealt with.

On the existence and the Hölder regularity of the local time of the Brownian bridge

Abstract In this paper, we will establish the existence and the Hölder regularity of the local time of the Brownian bridge. Our results are obtained by using a result on Malliavin calculus in [K. Es-Sebaiy, D. Nualart, Y. Ouknine and C. A. Tudor, Occupation densities for certain processes related to fractional Brownian motion, Stochastics 82 2010, 1–3, 133–147] for a Gaussian process with an absolutely continuous random drift, jointly with the classical approach based on the concept of local nondeterminism for Gaussian processes introduced by Berman [S. M. Berman, Local nondeterminism and local times of Gaussian processes, Indiana Univ. Math. J. 23 1973/74, 69–94].

A margin recipe for the management of intra-fraction target motion in radiotherapy.

Strategies to limit the impact of intra-fraction motion during treatment are common in radiotherapy. Margin recipes, however, are not designed to incorporate these strategies. This work aimed to provide a framework to determine how motion management strategies influence treatment margins. Two models of intra-fraction motion were considered. In model 1 motion was instantaneous, before treatment starts and in model 2 motion was a continuous drift during treatment. Motion management strategies were modelled by truncating the underlying error distribution at cσ, with σ the standard deviation of the distribution and c a free parameter. Using Monte Carlo simulations, we determined how motion management changed the required margin. The analysis was performed for different number of treatment fractions and different standard deviations of the underlying random and systematic errors. The required margin for a continuous drift was found to be well approximated by an average position of the target at ¾ of the drift. Introducing a truncation at cσ, the relative change in the margin was equal to 0.3c. This result held for both models, was independent of σ or the number of fractions and naturally generalizes to the situation with a residual (systematic) error. Treatment margins can be determined when motion management strategies are applied. Moreover, our analysis can be used to study the potential benefit of different motion management strategies. This allows to discuss and determine the most appropriate strategy for margin reduction.

Movement Patterns of Juvenile Loggerhead Turtles (Caretta caretta L. 1758) and Green Turtles (Chelonia mydas L. 1758) Hatched in Captivity and Released in the Korean Waters.

Simple SummaryDespite the continuous observation and drift of globally endangered sea turtles in Korean waters, relevant research and protection policies are deficient. To restore sea turtle populations near Korea, the Ministry of Oceans and Fisheries, Republic of Korea, has been hatching and rearing sea turtles in captivity and releasing juveniles into the sea. We satellite-tracked juvenile loggerhead and green turtles to confirm their movement patterns and adaptability in the wild. The tracked sea turtles used sea currents for movement, and the tracking duration and movement patterns differed according to their body size. In addition, while the loggerhead turtles moved to the Northeast East Sea, the green turtles tended to move west or southwest from the release point. By considering the release time and location, according to the growth level and species, the adaptability of artificially hatched and reared turtles to natural habitats is expected to be high.With most sea turtle populations declining, activities to conserve their habitat and nesting grounds and restore their populations are being implemented worldwide. To preserve the Northwestern Pacific populations, the National Marine Biodiversity Institute of Korea has been releasing artificially propagated sea turtles, but whether these individuals join the wild population remains unknown. The present study aimed to determine the movement patterns of artificially propagated juvenile loggerhead (Caretta caretta) and green (Chelonia mydas) turtles fitted with satellite transmitters on their carapaces and released in the waters of Jeju or Yeosu, Republic of Korea, between August 2018 and April 2022. Loggerheads traveled northward to the East Sea, whereas green turtles moved west or southwest. Two 36-month-old and two 48-month-old loggerheads moved toward their potential nursery grounds and toward their feeding grounds, respectively. Three green turtles with a curved carapace length (CCL) of <40 cm moved toward their nursery or feeding grounds, while three individuals (CCL > 45 cm) moved toward their inshore foraging areas. The travel paths were closely related to the direction of local sea currents. Our results implied that releasing artificially propagated sea turtles, considering their age and CCL, can positively contribute to the conservation of Northwestern Pacific populations.

A stochastic particle Fokker–Planck method with nonlinear production terms for a variable hard-sphere gas

The stochastic particle Fokker–Planck (FP) method has been gaining increasing attention in the field of rarefied gas dynamics due to its potential to reduce the computational costs of the direct simulation Monte Carlo method. The FP method approximates the discrete binary collisions of the Boltzmann equation as continuous drift–diffusion phenomena in velocity space. Consistency between the FP method and the Boltzmann equation is achieved by matching production terms. The Maxwell molecular model has been widely used in this process due to the possibility of obtaining closed-form solutions for these production terms. However, it is well known that the Maxwell molecular model has difficulty predicting strong shock waves since it cannot provide accurate relaxation rates for the moments. By contrast, the variable hard-sphere (VHS) molecular model is able to capture the transport properties of real gases better than the Maxwell molecular model. Nonetheless, there have so far been no reports associated with an accurate VHS molecular model for the stochastic particle FP method. In this paper, two different molecular models are developed to describe a monatomic gas interacting through a VHS potential. The proposed VHS molecular models are evaluated using Grad's 13- and 26-moment distribution functions; hence, they are named the G13 and G26 molecular models. The G13 and G26 molecular models include additional nonlinear moments compared with the conventional Maxwell molecular model. A one-dimensional shock wave and two-dimensional hypersonic cylinder flow are considered for validation. The results show that the proposed molecular models perform better than the Maxwell molecular model in predicting supersonic and hypersonic shock waves.

A Virion-Based Combination Vaccine Protects against Influenza and SARS-CoV-2 Disease in Mice.

ABSTRACTVaccines targeting SARS-CoV-2 have been shown to be highly effective; however, the breadth against emerging variants and the longevity of protection remains unclear. Postimmunization boosting has been shown to be beneficial for disease protection, and as new variants continue to emerge, periodic (and perhaps annual) vaccination will likely be recommended. New seasonal influenza virus vaccines currently need to be developed every year due to continual antigenic drift, an undertaking made possible by a robust global vaccine production and distribution infrastructure. To create a seasonal combination vaccine targeting both influenza viruses and SARS-CoV-2 that is also amenable to frequent reformulation, we have developed an influenza A virus (IAV) genetic platform that allows the incorporation of an immunogenic domain of the SARS-CoV-2 spike (S) protein onto IAV particles. Vaccination with this combination vaccine elicited neutralizing antibodies and provided protection from lethal challenge with both pathogens in mice. This approach may allow the leveraging of established influenza vaccine infrastructure to generate a cost-effective and scalable seasonal vaccine solution for both influenza and coronaviruses.IMPORTANCE The rapid emergence of SARS-CoV-2 variants since the onset of the pandemic has highlighted the need for both periodic vaccination “boosts” and a platform that can be rapidly reformulated to manufacture new vaccines. In this work, we report an approach that can utilize current influenza vaccine manufacturing infrastructure to generate combination vaccines capable of protecting from both influenza virus- and SARS-CoV-2-induced disease. The production of a combined influenza/SARS-CoV-2 vaccine may represent a practical solution to boost immunity to these important respiratory viruses without the increased cost and administration burden of multiple independent vaccines.