Uniform Sequence Research Articles

Recognition of a cryptic maximum flooding surface in shallow marine carbonate sequences using geochemical (Y/Ho) proxy data

ABSTRACTSince diagnostic primary depositional sedimentary structures and depth‐dependent grain‐size trends are rarely preserved, building a comprehensive sequence stratigraphic framework for the vast majority of the Phanerozoic carbonate platform sequences is pending. Among the two most important sequence stratigraphic surfaces, while the subaerial unconformity can be reliably identified by either karst development or the appearance of siliciclastic materials, the demarcation of the maximum flooding surface remains difficult in lithologically uniform shallow marine carbonate sequences. The present study attempts to identify the globally documented maximum flooding surface within the body of the negative carbon isotope excursion of the Palaeocene–Eocene Thermal Maximum recorded in the shallow marine carbonate platform sequences. The results show that, along with the carbonate microfacies, the yttrium to holmium ratio (Y/Ho ratio) of the carbonate fraction reliably records the sea‐level changes. A Y/Ho ratio between 70 and 80 demarcates the stratigraphic position of the maximum sea‐level state (the most open marine condition in the studied interval) and maximum flooding surface in the studied sections. Since the Y/Ho ratios remain relatively stable throughout diagenesis, they can be used for maximum flooding surface identification in shallow marine carbonate platform sequences. The possibility exists that the same method can also be applied to the mixed siliciclastic–carbonate systems.

Norm and relative uniform convergence

In this paper, we show that if H is a Dedekind complete normed Riesz space with the local Egoroff property, then H is lattice isomorphic to an ideal of an AM-space if and only if for any order bounded norm null sequence in H. Based on this, several characterizations of discrete Banach lattices with order continuous norms are provided. As an application, we find the special regulator for every relative uniform convergent sequence in discrete Banach lattices with order continuous norms.

A deep neural network reduced order model for unsteady aerodynamics of pitching airfoils

A machine learning framework is developed to compute the aerodynamic forces and moment coefficients for a pitching NACA0012 airfoil incurring in light and deep dynamic stall. Four deep neural network frameworks of increasing complexity are investigated: two multilayer perceptrons and two convolutional neural networks. The convolutional framework, in addition to the standard mean squared error loss, features an improved loss function to compute the airfoil loads. In total, five models are investigated of increasingly complexity. The convolutional model, coupled with the loss function based on force and moment coefficients and embedding the attention mechanism, is found to robustly and efficiently predict pressure and skin friction distributions over the airfoil over the entire pitching cycle. Periodic conditions are implemented to grant the physical smoothness of the model output both in space and time. An analysis of the training dataset point distributions is performed to point out the effects of adopting low discrepancy sequences, such as Latin hypercube, Sobol', and Halton, compared to random and uniform sequences. The current model shows improved performances in predicting forces and pitching moment in a broad range of operating conditions.

TiCoSeRec: Augmenting Data to Uniform Sequences by Time Intervals for Effective Recommendation

TiCoSeRec: Augmenting Data to Uniform Sequences by Time Intervals for Effective Recommendation

On relative uniform convergence of triple sequence of functions

This paper discusses relative uniform convergence of triple sequence of functions that are defined on a compact domain. Another central idea that is discussed is the regular relative uniform convergence and the Cauchy relative uniform convergence of triple sequence of functions. The idea that a continuous triple sequence defined on a compact domain is relative uniform convergent if and only if it is relative uniform Cauchy has been discussed and established. Subsequently, a glimpse into Cesaro summability of triple sequences and a theorem regarding triple Cesaro summability of bounded relative uniform triple sequence of functions have been introduced.

Fixed‐time stability of nonlinear impulsive systems: Sufficient criteria and necessary condition

AbstractThis article explores the criteria for fixed‐time stability (FxTS) within nonlinear impulsive dynamical systems, encompassing both stabilizing and destabilizing impulses. Initially, employing the Lyapunov method, the article delineates a criterion for FxTS, particularly when impulsive sequences are delineated by an average impulsive interval. Following this, the article innovatively applies two integral inequalities to introduce an optimized criterion for uniform impulsive sequences, evidencing its lesser conservativeness relative to the initial criterion. Moreover, this article derives a necessary condition for dynamical systems subjected to destabilizing impulses. Intriguingly, the investigation reveals the existence of a minimal threshold for the maximum impulsive interval, below which the system cannot achieve FxTS. This result elucidates why existing literature uniformly imposes a specific condition on the impulsive interval for destabilizing impulses. Finally, the efficacy of the proposed theory is underscored through numerical examples.

Ideal Relative Uniform Convergence of Double Sequence of Positive Linear Functions

In this article, we look into the concept of ideal relative uniform convergence of a double sequence of functions. In addition, we define ideal relative uniform Cauchy and ideal regular relative uniform convergence of a double sequence of positive linear functions defined on a compact domain D with respect to the scale function σ(x) defined on D. We also introduced several classes of ideal relative uniform convergent double sequences of functions and investigated their algebraic and topological properties.

Finding automatic sequences with few correlations

Although automatic sequences are algorithmically very simple, some of them have pseudorandom properties. In particular, some automatic sequences such as the Golay–Shapiro sequence are known to be 2-uncorrelated, meaning that they have the same correlations of order 2 as a uniform random sequence. However, the existence of ℓ-uncorrelated automatic sequences (for ℓ ⩾ 3) was left as an open question in a recent paper of Marcovici, Stoll and Tahay. We exhibit binary block-additive sequences that are 3-uncorrelated and, with the help of analytical results supplemented by an exhaustive search, we present a complete picture of the correlation properties of binary block-additive sequences of rank r ⩽ 5, and ternary sequences of rank r ⩽ 3.

Outcrop-to-subsurface correlation and sequence stratigraphy of a mixed carbonate–siliciclastic ramp using element geochemistry and well logging; Upper Cretaceous Kometan Formation, Zagros Foreland, NE Iraq

Surface analogues are suitable tools to link reservoir models to real facies but they require a robust outcrop-to-subsurface stratigraphic correlation. In this study, we correlate gamma-ray (GR), and porosity logs from nine wells drilled in the Cretaceous Kometan Formation, a prolific carbonate reservoir of northern Iraq, with geochemical logs from three sections representing surface analogues. The sections were sampled for microfacies, X-ray diffraction mineralogy, and element geochemistry using X-ray fluorescence spectrometry calibrated by ICP-MS data. Six microfacies composed of mudstones to packstones with planktonic, and benthic foraminifers were identified in outcrop, and interpreted as middle ramp, outer ramp, and basin deposits. The microfacies show increasing Al and K, and decreasing Ca concentration trends from the middle ramp to the basin settings. Their subsurface analogues are carbonates, marls and shales with benthic foraminifers, deposited in proximal, inner to middle ramp parts of the Kometan mixed carbonate–siliciclastic ramp system. The K + Al logs are correlated for 33 km, and the subsurface GR logs for over 100 km distance, but both reflect detrital admixture in biogenic carbonate. However, the outcrop- and subsurface log patterns show opposite vertical trends. The subsurface, inner ramp GR maxima in the middle Kometan, correlate with the outcrop K + Al minima jointly reflecting landwards and seawards shifts of the middle ramp carbonate factory during transgressions and regressions, respectively. The maxima and minima are interpreted as maximum regression (mrs) and maximum flooding surfaces (mfs) in the T–R sequence-stratigraphic model. Neutron-density and sonic logs indicate that the best reservoir quality is achieved in fractured pure carbonates, which are controlled by these T–R cycles. The results highlight the importance of elemental geochemistry in stratigraphic correlation of lithologically uniform sequences, and suggest that outcrop geochemistry can be correlated with well logs.

On Forcibly k-Connected Uniform Hypergraphic Sequences

On Forcibly k-Connected Uniform Hypergraphic Sequences

Employing plant DNA barcodes for pomegranate species identification in Al-Baha Region, Saudi Arabia

The Punica granatum (Pomegranate) tree attracted a lot of interest for its nutritious fruits and therapeutic benefits. Although research on genetic diversity is important to develop breeding programs and implement efficient cultivar improvement, the genetic diversity of pomegranates in Saudi Arabia has not been investigated completely. The two important pomegranate cultivars in Al-Baha region of Saudi Arabia (Bidah-red and Bidah-green), which have recently gained considerable attention due to their unique sweet taste, were studied using DNA barcodes because information about their phylogeny is limited. To reveal the phylogeny of these two cultivars, three DNA barcodes [the internal transcribed spacer 2 (ITS2), ribulose 1,5-biphosphate carboxylase (rbcL), and intergenic spacer region (trnH-psbA)] were used. The ITS2 and psbA-trnH had sufficient polymorphism to allow distinction at the cultivar level, whereas the rbcL region had a uniform sequence; hence, it failed to discriminate among the cultivars. The two cultivars were found to be clustered in the same clade on the phylogenetic tree constructed using the ITS2 and psbA-trnH sequences, suggesting that they are either closely related or have adapted to their locations. As the ITS2 region exhibited higher polymorphism than psbA-trnH, the phylogenetic tree based on ITS2 indicated that Bidah-red and Bidah-green are distinct cultivars. We conclude that ITS2 and psbA-trnH DNA barcodes are capable of authenticating and identifying pomegranate cultivars and can assist in improving pomegranate quality in the future through molecular breeding.

Accurate measurement of high-reflective surface based on adaptive fringe projection technique

Fringe projection profilometry (FPP) is one of the most effective methods to obtain three-dimensional surface topography information about an object. However, for objects with large variations in surface reflectance, it is difficult to measure the saturated regions with conventional FPP. In this paper, a new adaptive fringe projection (AFP) method is proposed to solve this problem. Compared with existing methods, the proposed method can automatically generate low-intensity projected fringe patterns instead of requiring manual adjustment. First, we built a projection intensity model for the captured pixels and defined the surface reflection factor and environmental factor for saturated pixels. Then, a small number of uniform grayscale pattern sequences were projected to mark the saturated areas, while the surface reflection factor and the environment factor of individual pixels were calculated and a surface coefficient look-up table (SCLUT) was created. The low-intensity projected fringe patterns were automatically calculated and generated based on the captured uniform grayscale sequences of images to establish the mapping relationship between the camera image plane and the projector image plane. Finally, the optimal projection intensities of pixels in the saturated regions were calculated according to the SCLUT, and adaptive fringe patterns were generated. Experiments show that using the adaptive fringe patterns generated by the proposed method to measure objects can accurately adjust the projection intensity and substantially improve the measurement accuracy of high-reflective surface.

An Interferometric-Synthetic-Aperture-Radar-Based Method for Predicting Long-Term Land Subsidence in Goafs through the Concatenation of Multiple Sources of Short-Term Monitoring Data

The land subsidence occurring over a goaf area after coal mining is a protracted process. The accurate prediction of long-term land subsidence over goaf areas relies heavily on the availability of long-term land subsidence monitoring data. However, the scarcity of continuous long-term land subsidence monitoring data subsequent to the cessation of mining significantly hinders the accurate prediction of long-term land subsidence in goafs. To address this challenge, this study proposes an innovative method based on interferometric synthetic aperture radar (InSAR) for predicting long-term land subsidence of goafs following coal mining. The proposed method employs a concatenation approach that integrates multiple short-term monitoring data from different coal faces, each with distinct cessation times, into a cohesive and uniform long-term sequence by normalizing the subsidence rates. The method was verified using actual monitoring data from the Yangquan No. 2 mine in Shanxi Province, China. Initially, coal faces with the same shapes but varying cessation times were selected for analysis. Using InSAR monitoring data collected between June and December of 2016, the average subsidence rate corresponding to the duration after coal mining cessation on each coal face was back-calculated. Subsequently, a function relating subsidence rate to the duration after coal mining cessation was fitted to the data. Finally, the relationship between cumulative subsidence and the duration after coal mining cessation was derived by integrating the function. The results indicated that the relationship between subsidence rate and duration after coal mining cessation followed an exponential function for a given coal face, whereas the relationship between cumulative subsidence and duration after coal mining cessation conformed to the Knothe time function. Notably, after the cessation of coal mining, significant land subsidence persisted in the goaf of the Yangquan No. 2 mine for a duration ranging from 5 to 10 years. The cumulative subsidence curve along the long axis of the coal face ultimately exhibited an inclined W-shape. The proposed method enables the quantitative prediction of residual land subsidence in goafs, even in cases where continuous long-term land subsidence monitoring data are insufficient, thus providing valuable guidance for construction decisions above the goaf.

Machine learning discovery of optimal quadrature rules for isogeometric analysis

We propose the use of machine learning techniques to find optimal quadrature rules for the construction of stiffness and mass matrices in isogeometric analysis (IGA). We initially consider 1D spline spaces of arbitrary degree spanned over uniform and non-uniform knot sequences, and then the generated optimal rules are used for integration over higher-dimensional spaces using tensor products. The quadrature rule search is posed as an optimization problem and solved by a machine learning strategy based on adaptive gradient-descent. However, since the optimization space is highly non-convex, the success of the search strongly depends on the number of quadrature points and the parameter initialization. Thus, we use a dynamic programming strategy that initializes the parameters from the optimal solution over the spline space with a lower number of knots. With this method, we found optimal quadrature rules for spline spaces when using IGA discretizations with up to 50 uniform elements and polynomial degrees up to 8, showing the generality of the approach in this scenario. For non-uniform partitions, the method also finds an optimal rule in a reasonable number of test cases. We also assess the generated optimal rules in two practical case studies, namely, the eigenvalue problem of the Laplace operator and the eigenfrequency analysis of freeform curved beams, where the latter problem shows the applicability of the method to curved geometries. In particular, the proposed method results in savings with respect to traditional Gaussian integration of up to 44% in 1D, 68% in 2D, and 82% in 3D spaces.

Model predictive control of nonlinear processes using neural ordinary differential equation models

Neural Ordinary Differential Equation (NODE) is a recently proposed family of deep learning models that can perform a continuous approximation of a linear/nonlinear dynamic system using time-series data by integrating the neural network model with classical ordinary differential equation solvers. Modeling nonlinear dynamic processes using data has historically been a critical challenge in the field of chemical engineering research. With the development of computer science and neural network technology, recurrent neural networks (RNN) have become a popular black-box approach to accomplish this task and have been utilized to design model predictive control (MPC) systems. However, as a discrete-time approximation model, RNN requires strictly uniform step sequence data to operate, which makes it less robust to an irregular sampling scenario, such as missing data points during operation due to sensor failure or other types of random errors. This paper aims to develop a NODE model and construct an MPC based on this novel continuous-time neural network model. In this context, closed-loop stability is established and robustness to noise is addressed using a variety of data analysis techniques. An example of a chemical process is utilized to evaluate the performance of NODE-based MPC. Furthermore, the performance of the NODE-based MPC under Gaussian and non-Gaussian noise is investigated, and the subsampling method is found to be effective in building models for MPC that are suitable for handling the presence of non-Gaussian noise in the data.

Regional seismic stratigraphic framework and depositional history of the post-Valanginian passive margin sequences in the Northern Carnarvon Basin, North West Shelf of Australia

The post-rift succession of the Northern Carnarvon Basin (north-western Australia) has commonly been interpreted as a relatively simple and uniform sequence that records a transition from siliciclastic to carbonate sedimentation deposited on a passive margin. However, given the significant vertical and lateral variation in seismic facies visible on seismic data, this interpretation likely oversimplifies the depositional history of the margin. Regional composite seismic lines that cross most of the basin, integrated with lithological and biostratigraphic information from exploration wells, provide the context for a better understanding of the depositional processes and environments that characterize the post-rift continental margin succession. We show that the sedimentary sequences deposited above the Valanginian breakup unconformity contain a wide variety of seismic facies that can be linked to a number of different marine depositional environments, with the greatest lateral variation occurring in the Turonian – Rupelian and in the Tortonian – Present. The former interval consists of three dominant seismic facies, namely polygonally faulted, incised, and parallel bedded, which we interpret to indicate a lateral transition from an environment primarily dominated by fine-grained pelagic/hemipelagic deposition to one dominated by energetic bottom currents that created both depositional and erosional features, such as contourite drifts and associated moats. The latter interval is expressed by sigmoidal and continuous reflections which pass laterally into more chaotic reflection packages, which we interpret as clinoforms and mass-transport complexes (MTCs). The development of bottom currents may be connected to changes in circulation associated with the opening of oceans adjacent to the northwest margin of Australia, while the MTCs may indicate increased regional seismic activity and slope instability resulting from the development of collisional plate boundaries. Definition of these sequences highlights the significant changes that have occurred in the sedimentary processes that operated on the margin, and their potential link to its tectonic evolution.

Self-Assembly of Amphiphilic Alternating Copolymers by Chain Folding in Water: From Uniform Composition and Sequence to Monodisperse Micelles

Self-Assembly of Amphiphilic Alternating Copolymers by Chain Folding in Water: From Uniform Composition and Sequence to Monodisperse Micelles

Three new species of the family Cirolanidae Dana, 1852 (Isopoda, Cymothoida) from the shallow Brazilian bathyal.

Three new species of isopod crustaceans of the family Cirolanidae-Dolicholana ivanyae spec. nov., Natatolana hadassae spec. nov. and Politolana cleoniceae spec. nov.-are described from the shallow waters of the Brazilian bathyal. The specimens were collected from the shallow bathyal zone of the Potiguar Basin, off the Brazilian state of Rio Grande do Norte, from Pernambuco and Bahia, and the Campos Basin, off Rio de Janeiro and São Paulo states. Dolicholana ivanyae spec. nov. can be distinguished from its congeners by the subrectangular shape of the head, its very long frontal lamina, which surpasses article 2 of the peduncle of antenna 1, and its densely setose pereopod 7. Natatolana hadassae spec. nov. is unique due to the subacute posteroventral angle of epimeron 4, ischial pereopod 3 as produced as those of pereopods 1 and 2, and the distal margin of the pleotelson with 10 robust distal setae. Politolana cleoniceae spec. nov. differs from its congeners based on the combination of the following traits: the pereon-pleon articulation is tight, with pleonite 1 clearly visible, and not covered completely by pereonite 7, while the pleon (in the dorsal-ventral view) is arched in a uniform sequence with the pereon, and the uropodal endopod is shorter than the exopod. In addition to these findings, the known geographical distribution of Dolicholana brucei, which was described recently from Brazil, is extended southward to include Bahia, Brazil. This study increases the number of cirolanid species recorded from Brazilian waters to 23.

Uniform Sequence Better: Time Interval Aware Data Augmentation for Sequential Recommendation

Sequential recommendation is an important task to predict the next-item to access based on a sequence of interacted items. Most existing works learn user preference as the transition pattern from the previous item to the next one, ignoring the time interval between these two items. However, we observe that the time interval in a sequence may vary significantly different, and thus result in the ineffectiveness of user modeling due to the issue of preference drift. In fact, we conducted an empirical study to validate this observation, and found that a sequence with uniformly distributed time interval (denoted as uniform sequence) is more beneficial for performance improvement than that with greatly varying time interval. Therefore, we propose to augment sequence data from the perspective of time interval, which is not studied in the literature. Specifically, we design five operators (Ti-Crop, Ti-Reorder, Ti-Mask, Ti-Substitute, Ti-Insert) to transform the original non-uniform sequence to uniform sequence with the consideration of variance of time intervals. Then, we devise a control strategy to execute data augmentation on item sequences in different lengths. Finally, we implement these improvements on a state-of-the-art model CoSeRec and validate our approach on four real datasets. The experimental results show that our approach reaches significantly better performance than the other 9 competing methods. Our implementation is available: https://github.com/KingGugu/TiCoSeRec.

On forcibly k-edge-connected and forcibly super edge-connected uniform hypergraphic sequences

On forcibly k-edge-connected and forcibly super edge-connected uniform hypergraphic sequences