Standard Scheme Research Articles

On the Application of Mann-Iterative Scheme with h-Convexity in the Generation of Fractals

Self-similarity is a common feature among mathematical fractals and various objects of our natural environment. Therefore, escape criteria are used to determine the dynamics of fractal patterns through various iterative techniques. Taking motivation from this fact, we generate and analyze fractals as an application of the proposed Mann iterative technique with h-convexity. By doing so, we develop an escape criterion for it. Using this established criterion, we set the algorithm for fractal generation. We use the complex function f(x)=xn+ct, with n≥2,c∈C and t∈R to generate and compare fractals using both the Mann iteration and Mann iteration with h-convexity. We generalize the Mann iterative scheme using the convexity parameter h(α)=α2 and provide the detailed representations of quadratic and cubic fractals. Our comparative analysis consistently proved that the Mann iteration with h-convexity significantly outperforms the standard Mann iteration scheme regarding speed and efficiency. It is noticeable that the average number of iterations required to perform the task using Mann iteration with h-convexity is significantly less than the classical Mann iteration scheme. Moreover, the relationship between the fractal patterns and the input parameters of the proposed iteration is extremely intricate.

Weak convergence of tamed exponential integrators for stochastic differential equations

We prove weak convergence of order one for a class of exponential based integrators for SDEs with non-globally Lipschitz drift. Our analysis covers tamed versions of Geometric Brownian Motion (GBM) based methods as well as the standard exponential schemes. The numerical performance of both the GBM and exponential tamed methods through four different multi-level Monte Carlo techniques are compared. We observe that for linear noise the standard exponential tamed method requires severe restrictions on the step size unlike the GBM tamed method.

Bunching enhancement for coherent harmonic generation by using phase merging effects

In this paper, promising but simple schemes are investigated to enhance the micro-bunching of relativistic electron beams for coherent harmonic generation (CHG) by using phase merging effects. In contrast to the standard CHG scheme, two specially designed dispersion sections (DSs) are adopted with the DS-modulator–DS configuration. The phase space of the e beam is appropriately coupled in the first DS, and the electrons within one seed wavelength can merge to the same phase with a matched second DS. Micro-bunching of the e beam can thus be enhanced by a large margin with much higher-harmonic components. Taking e beams from laser wakefield accelerators (LWFAs) as an example, start-to-end simulations are performed to show the effectiveness and robustness of the proposed schemes with several configurations. The beam current can be optimized to several tens to hundreds of kiloamperes, and the radiation power reaches hundreds of megawatts in the extreme ultraviolet regime within a 3.5 m-long beamline. The proposed schemes offer new opportunities for future compact free-electron lasers driven by LWFAs and provides prospects for truly compact and widely applicable systems.

Decoder-ROI based Versatile Video Coding for Multi-Object Tracking Vision Task

The video encoding standards High Efficiency Video Coding (HEVC) and, more recently, Versatile Video Coding (VVC) have introduced significant advancements in multimedia communication applications, such as video conferencing, broadcasting, and notably, E-learning. However, recent developments in artificial intelligence (AI) and big data have given rise to an urgent need for a specialized video encoding model designed specifically for image and video analysis applications using machine vision. In this paper, we propose a novel video encoding approach that effectively combines the ROI Coding algorithm and the VVC encoding model. The proposed method identifies regions of interest within video frames through fundamental and deep features. Based on this, we propose an adaptive compression method for each frame block, ensuring both the execution performance of machine learning applications and minimal data encoding requirements. To achieve new coding scheme without adding bitrate, New feature extraction approach are utilizing only decoded information (Decoder-ROI). The results demonstrate that the Decoder-ROI achieved significant compression rate improvement when compared to standard and relevant VCM schemes. Furthermore, ROI exploitation contributes to a 3.25\% reduction in encoding time compared to the baseline VVC encoding standard.

Acceleration of particle-in-cell simulations using sparse grid algorithms. I. Application to dual frequency capacitive discharges

The use of sparse particle-in-cell (PIC) algorithms to accelerate the standard explicit PIC scheme has recently been successfully applied in the context of single-frequency capacitively coupled plasma discharges [Garrigues et al., J. Appl. Phys. 129, 153303 (2021)]. We have extended the sparse PIC scheme to model dual-frequency capacitive discharges. Comparisons between standard and sparse PIC algorithms show that the plasma properties as well as the electron and ion distribution functions can be retrieved with a maximum error of 2%. This work opens the interest of using the sparse PIC algorithm to perform 2D and 3D simulations under real operating conditions of capacitively coupled plasma discharges.

Anonymous Complaint Aggregation for Secure Messaging

Private messaging platforms provide strong protection against platform eavesdropping, but malicious users can use privacy as cover for spreading abuse and misinformation. In an attempt to identify the sources of misinformation on private platforms, researchers have proposed mechanisms to trace back the source of a user-reported message (CCS '19,'21). Unfortunately, the threat model considered by initial proposals allowed a single user to compromise the privacy of another user whose legitimate content the reporting user did not like. More recent work has attempted to mitigate this side effect by requiring a threshold number of users to report a message before its origins can be identified (NDSS '22). However, the state of the art scheme requires the introduction of new probabilistic data structures and only achieves a "fuzzy" threshold guarantee. Moreover, false positives, where the source of an unreported message is identified, are possible. This paper introduces a new threshold source tracking technique that allows a private messaging platform, with the cooperation of a third-party moderator, to operate a threshold reporting scheme with exact thresholds and no false positives. Unlike prior work, our techniques require no modification of the message delivery process for a standard source tracking scheme, affecting only the abuse reporting procedure, and do not require tuning of probabilistic data structures.

VISUALIZATION OF THREATS IN CIVIL SECURITY USING THREE-DIMENSIONAL SPATIAL MODELING

The article analyzes the main concepts and methods of modeling used in civil security to solve the issues of analyzing the prerequisites for the occurrence of hazards, by forecasting, preventing and managing their components. On-site research, in particular, direct measurements, can only be carried out on an already existing object. Modeling today is one of the important methods, the main methodology of which is to learn the essence of natural and social phenomena of various levels of complexity. It provides an opportunity to demonstrate various systems related to civil security using methods of applied mathematics, mathematical statistics and optimization. The task of analysis and forecasting on any object can be reduced to building a model that reflects the behavior of a natural object. The main tasks of this article are to establish modeling principles and methods for their use in civil security using the example of modeling noise maps from various sources, one of which is construction in a dense residential area. The task of analysis and forecasting on almost any object can be reduced to building a model that adequately reflects the behavior of a natural object. The basic principles on which modeling is based are defined. The principle of information sufficiency – building its model is impossible in the complete absence of information about the object. Feasibility principle – the model should ensure the achievement of the research goal with a non-zero probability value. The principle of multiplicity of models - the model should reflect exactly those properties of a real object or system that are of interest to the researcher. The principle of aggregation - the system is better decomposed as a set of subsystems, for the description of which standard schemes can be used. Principle of parameterization – the model must be built in the form of a known system, the parameters of which are unknown. Crisis simulation training is a common organizational tool for improving civil security preparedness. Although today its general advantages cannot be denied, the conditions under which these simulations offer opportunities for improvement often remain unclear.

Time-Stepping Error Estimates of Linearized Grünwald–Letnikov Difference Schemes for Strongly Nonlinear Time-Fractional Parabolic Problems

A fully discrete scheme is proposed for numerically solving the strongly nonlinear time-fractional parabolic problems. Time discretization is achieved by using the Grünwald–Letnikov (G–L) method and some linearized techniques, and spatial discretization is achieved by using the standard second-order central difference scheme. Through a Grönwall-type inequality and some complementary discrete kernels, the optimal time-stepping error estimates of the proposed scheme are obtained. Finally, several numerical examples are given to confirm the theoretical results.

Computational decomposition and composition technique for approximate solution of nonstationary problems

Stable computational algorithms for the approximate solution of the Cauchy problem for nonstationary problems are based on implicit time approximations. Computational costs for boundary value problems for systems of coupled multidimensional equations can be reduced by additive decomposition of the problem operator(s) and composition of the approximate solution using particular explicit–implicit time approximations. Such a technique is currently applied in conditions where the decomposition step is uncomplicated. A general approach is proposed to construct decomposition–composition algorithms for evolution equations in finite-dimensional Hilbert spaces. It is based on two main variants of the decomposition of the unit operator in the corresponding spaces at the decomposition stage and the application of additive operator-difference schemes at the composition stage. The general results are illustrated on the boundary value problem for a second-order parabolic equation by constructing standard splitting schemes on spatial variables and region-additive schemes (domain decomposition schemes).

P-adaptive hybridized flux reconstruction schemes

This paper presents p-adaptive hybridized flux reconstruction schemes to reduce the computational cost of implicit discretizations. We first introduce spatial and temporal discretization and discuss the adaptation algorithm via a nondimensional vorticity indicator for hybridized methods with globally continuous and globally discontinuous numerical traces. At each adaptation level, projection operations are applied to determine the new space based on the element-wise projected solution and transmission conditions. We validate our implementation and analyze performance via numerical examples. Specifically, we show via an isentropic vortex that p-adaptive hybridization of both HFR and EFR methods results in comparable numerical error to standard p-adaptive and p-uniform FR discretizations with a fraction of degrees of freedom. Results for a cylinder at Re=150 showcase speedup factors in excess of 6 for hybridized methods in comparison with p-adaptive standard FR schemes and up to 40 against p-uniform FR discretizations. Similarly, results for a NACA 0012 airfoil at Re=10,000 demonstrate speedup factors close to 6 against p-adaptive FR discretizations and up to 33 against p-uniform conventional FR. Hence, combining hybridization with adaptation yields a significant reduction in computational cost compared with standard implicit discretizations.

The vast majority of nucleic acid-loaded lipid nanoparticles contain cargo

Nucleic acid-based therapies are transforming medicine, but rely on an efficient delivery vehicle such as lipid nanoparticles (LNPs). Concerns exists in the nanomedicine field, that a large fraction of the LNPs in the ensemble does not contain any nucleic acid cargo and thus exert no functional effect. Nevertheless, how LNP lipid formulation, the LNP preparation method employed and nucleic acid cargo size correlates with the proportion of empty LNPs remains largely unexplored. Here we employ a well-established single particle based method to study nucleic acid loading heterogeneity in LNPs. We find that only a minor fraction of LNPs are “empty”, both for LNPs loaded with siRNA, mRNA and plasmids. For clinically relevant LNPs for mRNA delivery, we never detected more than 16% empty nanoparticles in the ensemble. Thus employing standard LNP lipid-cargo combinations and preparation schemes results in LNPs with the potential to serve their biomedical function.

Silicon / Perovskite Tandem Solar Cells with Reverse Bias Stability down to -40V. Unveiling the Role of Electrical and Optical Design.

The reverse bias stability is a key concern for the commercialization and reliability of halide perovskite photovoltaics. Here, the robustness of perovskite-silicon tandem solar cells to reverse bias electrical degradation down to -40V is investigated. The two-terminal tandem configuration, with the perovskite coupled to silicon, can improve the solar cell resistance to severe negative voltages when the tandem device is properly designed. While perovskite cells typically exhibit early reverse bias breakdown voltages, the serial connection with silicon cells with large shunt resistances and high voltage breakdown limits their negative polarization and prevent the passage of large current densities when reverse biased. The importance of careful optical design is illustrated, with bottom-limited conditions required to prevent the perovskite topcell from exploring its own breakdown. This aspect is of great importance in the case of partial shading events when the solar spectrum is richer in the IR components than the standard AM1.5G. Notably, 100% of efficiency retained after polarization at -40V in different stressing conditions is observed. The results presented suggest that standard industrial bypass diode schemes may be compatible with silicon/perovskite tandem photovoltaics and provide new guidelines for the standardization of the stressing protocols.

Ophthalmologic adverse events in childhood head and neck rhabdomyosarcoma survivors treated according to four different local treatment strategies

IntroductionOphthalmological adverse events (OAEs) are known to frequently occur following local treatment for pediatric head and neck rhabdomyosarcoma (HNRMS). The exact nature of these OAEs and the burden they put on survivors is less well described. Moreover, it is suspected there might be differences in the prevalence and nature of OAEs depending on local treatment strategy applied: external beam radiation therapy with photons, external beam radiation therapy with protons, macroscopically radical surgery combined with brachytherapy, or microscopically radical surgery combined with external beam radiation therapy. MethodsWe cross-sectionally assessed 98 HNRMS survivors with long (median 9 years) follow-up time, according to a predefined list of OAEs based on the Common Terminology Criteria for Adverse Events system. We added information from chart reviews on the nature and management of all OAEs scored grade ≥1. We describe the prevalence of OAEs for the different tumor sites and treatment strategies separately. ResultsOAEs occurred following treatment of all HNRMS sites. The most frequently observed OAEs are eyelid abnormalities, dry eyes, and cataracts. Sixty-two percent of survivors had several different OAEs simultaneously. In 27 % of survivors additional (surgical) treatment of OAEs was required during follow-up. The patterns observed suggest a possible relationship between OAE type and treatment strategy. ConclusionOAEs in HNRMS survivors confer a high burden of chronic toxicity. The simultaneous occurrence of multiple OAEs in individual survivors present a particularly challenging clinical scenario and demand specific expertise. We propose a standardized screening scheme to detect possible OAEs in asymptomatic survivors based on primary tumor localization.

Development of an accurate central finite-difference scheme with a compact stencil for the simulation of unsteady incompressible flows on staggered orthogonal grids

In scale-resolving simulations such as Large Eddy Simulations (LES), the spatial discretization scheme of the convective term plays a crucial role in avoiding interference between the numerical errors and the subgrid-scale model. Accurate schemes lead to lower truncation errors and better predictions of turbulent flows without the need for an excessively refined grid. To this end, a new second-order finite-difference scheme (HCDS6) has been developed for incompressible flows and orthogonal staggered grids. Compared to the standard second-order scheme, the new scheme has significantly lower dispersion errors. Compared to existing high-order schemes, the numerical stencil of HCDS6 is more compact, which makes it easier to implement, especially considering boundary conditions around complex geometries using Immersed Boundary Methods (IBM). The HCDS6 scheme conserves the discrete momentum with limited production or dissipation of discrete kinetic energy, which guarantees its numerical stability. Its performance is evaluated using an open-source CFD package called REEF3D. Three benchmarks demonstrate the key properties and performance of the scheme: the convection of an isentropic vortex, the Taylor-Green vortex flow, and turbulent channel flow. Its relatively low dispersion errors, combined with ease of implementation, make the HCDS6 scheme a promising candidate for efficient scale-resolving simulations of turbulent flows.

Dynamics of the prevalence of diseases that complicated the course of childbirth and the postpartum period (based on the materials of the Samara region)

The prevalence of diseases that complicated childbirth and the postpartum period in the Samara region for the period 2009–2021 was investigated. The study was performed based on the official statistical reporting of the Samara region according to a standard scheme. The structure of pathological conditions was assessed. Then, the dynamics were analyzed, and modeling and medium-term forecasting were conducted. Structure analysis was carried out based on the 2016 data. Forecast was performed for the medium term (5 years). Notably, premature rupture of membranes (55.8%) is the most common complication of childbirth and in the postpartum period, followed by obstructed labor (11.4%), childbirth complicated by umbilical cord pathology (10%), childbirth complicated by hypertensive disorders such as preeclampsia and eclampsia (9.3%), and various labor disorders (9.1%). However, the considered conditions indicated in the official statistical reporting explain only 61.1% of all complications of childbirth and in the postpartum period, and 38.9% of all conditions remain unknown, which makes prevention, timely diagnosis, and effective treatment of these conditions challenging. The underreporting of cases of hypertensive disorders during pregnancy is evidenced by their higher frequency during childbirth. Only 25%–30% are complications during pregnancy of the number of complications of this pathology during childbirth and the postpartum period, and the downward trend in the prevalence of this complication during pregnancy is combined with an upward trend during childbirth and the postpartum period. The prevalence of all major extragenital complications during labor and the postpartum period showed a downward trend, except diabetes mellitus. The complexity of the analysis lies in the fact that the level of registration of the same pathological conditions during pregnancy and childbirth and in the postpartum period is extremely different. The data obtained indicate the need for improving the early diagnosis of gestosis and statistical recording of complications of pregnancy and childbirth and provide basis for improving the system of monitoring pregnant women and correct diagnosis of pathology in early pregnancy.

Research on fertilization decision method for rice tillering stage based on the coupling of UAV hyperspectral remote sensing and WOFOST.

The use of chemical fertilizers in rice field management directly affects rice yield. Traditional rice cultivation often relies on the experience of farmers to develop fertilization plans, which cannot be adjusted according to the fertilizer requirements of rice. At present, agricultural drones are widely used for early monitoring of rice, but due to their lack of rationality, they cannot directly guide fertilization. How to accurately apply nitrogen fertilizer during the tillering stage to stabilize rice yield is an urgent problem to be solved in the current large-scale rice production process. WOFOST is a highly mechanistic crop growth model that can effectively simulate the effects of fertilization on rice growth and development. However, due to its lack of spatial heterogeneity, its ability to simulate crop growth at the field level is weak. This study is based on UAV remote sensing to obtain hyperspectral data of rice canopy and assimilation with the WOFOST crop growth model, to study the decision-making method of nitrogen fertilizer application during the rice tillering stage. Extracting hyperspectral features of rice canopy using Continuous Projection Algorithm and constructing a hyperspectral inversion model for rice biomass based on Extreme Learning Machine. By using two data assimilation methods, Ensemble Kalman Filter and Four-Dimensional Variational, the inverted biomass of the rice biomass hyperspectral inversion model and the localized WOFOST crop growth model were assimilated, and the simulation results of the WOFOST model were corrected. With the average yield as the goal, use the WOFOST model to formulate fertilization decisions and create a fertilization prescription map to achieve precise fertilization during the tillering stage of rice. The research results indicate that the training set R2 and RMSE of the rice biomass hyperspectral inversion model are 0.953 and 0.076, respectively, while the testing set R2 and RMSE are 0.914 and 0.110, respectively. When obtaining the same yield, the fertilization strategy based on the ENKF assimilation method applied less fertilizer, reducing 5.9% compared to the standard fertilization scheme. This study enhances the rationality of unmanned aerial vehicle remote sensing machines through data assimilation, providing a new theoretical basis for the decision-making of rice fertilization.

A computational approach for 2D elliptic singularly perturbed weakly coupled systems of convection–diffusion type with multiple scales and parameters in the diffusion and the convection terms

In this work, we consider the efficient resolution of a 2D elliptic singularly perturbed weakly coupled system of convection–diffusion type, which has small parameters at both the diffusion and the convection terms. We assume that the diffusion parameters can be distinct at each equation of the system, and also, they can have different orders of magnitude, but the convection parameter is the same at both equations of the system. Then, in general, overlapping regular or parabolic boundary layers can appear in the exact solution. The continuous problem is approximated by using the standard upwind finite difference scheme, which is constructed on a special piecewise uniform Shishkin mesh. Then, the numerical scheme is an almost first‐order uniformly convergent method with respect to all the perturbation parameters. Some numerical results, obtained with the numerical algorithm for one test problem, are presented, which show the good performance of the proposed numerical method and also corroborate in practice the theoretical results.

De-escalation treatment of patients with HPV-positive oropharyngeal squamous cell carcinoma.

e18052 Background: According to Globocan in 2020 were identified 98 412 new cases of oropharyngeal squamous cell carcinoma in the world. It was proved that the human papillomavirus (HPV) is a favorable prognostic factor. Patients with HPV-positive oropharynx cancer have higher indicators of progression-free survival (PFS) and overall survival (OS). As induction chemotherapy, the only TPF regimen (cisplatin/ docetaxel/ 5-fluorouracil) has been approved which has high toxic profile. Published results of randomized trials demonstrate the possibility of de-escalation CRT without reduction OS and PFS, but there is no data about safety of de-escalated IC regimen. Given the high toxicity of the standard regimen, as well as the presence of a favorable prognostic factor (HPV infection), since 2021 has started a prospective trial, investigating the possibility of use the dual-component IC regimen according to the TP scheme (cisplatin/ docetaxel). Objective: Improve the results of treatment of patients with locally advanced HPV- positive squamous cell carcinoma of the oropharynx by optimizing the scheme IC. Methods: In the prospective trial included 68 patients with p16-positive oropharyngeal squamous cell carcinoma (T3-4N0-1M0, or T1-4N2-3M0), who were divided into 2 equal groups. The research group received 3 cycles of IC to the de-escalated TP regimen and the control group according to the standard three-component TPF regimen. After completion IC patients of both groups had a standard CRT 70 Gy with carboplatin AUC 2.0 weekly. The primary endpoints were the assessment of objective response rate after the IC and toxicity. The Secondary endpoints: 1-year OS and PFS. Results: Complete response (CR) was achieved in 3 patients (8,8%), a partial response (PR) in 22 (64,7%), stable disease (SD) in 8 (23,5%) patients in the research arm. In the control arm: CR 4 patients (11,8%), PR 24 (70,6%), SD 6 (17,6%) patients. Both IC regimens demonstrated high efficacy rates, and there was no statistically significant ORR in the group (p=0,2133).Toxic manifestations were often observed in the arm of standard IC. The higher incidence of mucositis in the control group was statistically significant (p=0,025). The effect of IC regimen on subsequent CRT was also assessed. In the research arm, the time before the start of CRT was statistically significantly less than in the control arm (30 days vs 63 days, p=0,0035.). And the period of development mucositis of CRT in the TP group was longer than in the TPF group (34G vs 32G, p=0,0298). 1 year - PFS 94%, 1 year - OS 100% in the research group and 92% and 100% in the control arm. There was no statistically significant 1 year – PFS and 1 year - OS in the group (р=0,6547). Conclusions: The research scheme of IC demonstrated high results of an objective response, 1-year OS and 1 year - PFS, comparable to the standard TPF scheme, against the background of better tolerance.

Event-Triggered Adaptive Neural Network Tracking Control for Uncertain Systems With Unknown Input Saturation Based on Command Filters.

This brief presents a modified event-triggered command filter backstepping tracking control scheme for a class of uncertain nonlinear systems with unknown input saturation based on the adaptive neural network (NN) technique. First, the virtual control functions are reconstructed to address the uncertainties in subsystems by using command filters. A piecewise continuous function is employed to deal with the unknown input saturation problem. Next, an event-triggered tracking controller is developed by utilizing the adaptive NN technique. Compared with standard NN control schemes based on multiple-function-approximators, our controller only requires a single NN. The closed-loop system stability is analyzed based on the Lyapunov stability theorem, and it is shown that the Zeno behavior is also avoided under the designed event-triggering mechanism. Simulation studies are performed to validate the effectiveness of our controller.

A solution to achieve sequencing from SARS-CoV-2 specimens with low viral loads: concatenation of reads from independent reactions

BackgroundDuring the pandemic, whole genome sequencing was critical to characterize SARS-CoV-2 for surveillance, clinical and therapeutical purposes. However, low viral loads in specimens often led to suboptimal sequencing, making lineage assignment and phylogenetic analysis difficult. We propose an alternative approach to sequencing these specimens that involves sequencing in triplicate and concatenation of the reads obtained using bioinformatics. This proposal is based on the hypothesis that the uncovered regions in each replicate differ and that concatenation would compensate for these gaps and recover a larger percentage of the sequenced genome.ResultsWhole genome sequencing was performed in triplicate on 30 samples with Ct > 32 and the benefit of replicate read concatenation was assessed. After concatenation: i) 28% of samples reached the standard quality coverage threshold (> 90% genome covered > 30x); ii) 39% of samples did not reach the coverage quality thresholds but coverage improved by more than 40%; and iii) SARS-CoV-2 lineage assignment was possible in 68.7% of samples where it had been impaired.ConclusionsConcatenation of reads from replicate sequencing reactions provides a simple way to access hidden information in the large proportion of SARS-CoV-2-positive specimens eliminated from analysis in standard sequencing schemes. This approach will enhance our potential to rule out involvement in outbreaks, to characterize reinfections and to identify lineages of concern for surveillance or therapeutical purposes.