Class Of Schemes Research Articles

Transforming recycled polyester/cotton (Gossypium hirsutum L.) fibers into dye-free and eco-friendly denim fabrics: Preparation, properties evaluation, and feasibility analysis

Conventional denim production is plagued by the issue of wastewater pollution from warp dyeing. In this investigation, recycled cotton (R-CO), virgin cotton (V-CO), and dope-dyed recycled polyester (R-PET) fibers were spun into blue/white spaced warp yarns through a dual-feed-opening rotor spinning technique. These yarns were woven with V-CO weft yarns to produce fabrics featuring the classic denim color scheme of blue and white stripes, without the need for warp dyeing and complex finishing processes. The resulting fabrics fulfilled industry standards for tensile strength (>600 N), tearing resistance (>50 N), abrasion resistance (>25000 cycles), pH (≈6.5), and formaldehyde content (<10 mg/kg). The fabrics' air/moisture permeability and wearability (including crease-resistance, flexibility, drapability, and washing size stability) were outstanding. The fabrics' light and crocking colorfastness ratings all exceed grade 4, indicating excellent performance. A rise in R-CO content resulted in the degradation of several properties. The production of the denim covered by this study was more cost-effective and environment-friendly than that of conventional denim. This research provides a paradigm for the conversion of waste textiles into value-added and eco-friendly textile products.

Enhancing interpolation and approximation error estimates using a novel Taylor-like formula

In this paper, we present an approach to enhance interpolation and approximation error estimates. Based on a previously derived first-order Taylor-like formula, we demonstrate its applicability in improving the P1-interpolation error estimate. Following the same principles, we have also developed a novel numerical scheme for the heat equation that provides a better error estimate compared to the classical implicit finite differences scheme. Numerical illustrations confirm this behavior.

When Federated Learning Meets Privacy-Preserving Computation

Nowadays, with the development of artificial intelligence (AI), privacy issues attract wide attention from society and individuals. It is desirable to make the data available but invisible, i.e., to realize data analysis and calculation without disclosing the data to unauthorized entities. Federated learning (FL) has emerged as a promising privacy-preserving computation method for AI. However, new privacy issues have arisen in FL-based application because various inference attacks can still infer relevant information about the raw data from local models or gradients. This will directly lead to the privacy disclosure. Therefore, it is critical to resist these attacks to achieve complete privacy-preserving computation. In light of the overwhelming variety and a multitude of privacy-preserving computation protocols, we survey these protocols from a series of perspectives to supply better comprehension for researchers and scholars. Concretely, the classification of attacks is discussed including four kinds of inference attacks as well as malicious server and poisoning attack. Besides, this paper systematically captures the state of the art of privacy-preserving computation protocols by analyzing the design rationale, reproducing the experiment of classic schemes, and evaluating all discussed protocols in terms of efficiency and security properties. Finally, this survey identifies a number of interesting future directions.

On optimizing the company’s logistics activities

The article identifies the problem of organizing an effective logistics system in a company. The classic scheme for optimizing logistics processes and reducing costs, as well as the methods for optimizing transport costs are considered. It is proposed to consider the introduction of modern software that can improve the efficiency of logistics processes.

Learning quantum symmetries with interactive quantum-classical variational algorithms

A symmetry of a state |ψ⟩ is a unitary operator of which |ψ⟩ is an eigenvector. When |ψ⟩ is an unknown state supplied by a black-box oracle, the state’s symmetries provide key physical insight into the quantum system; symmetries also boost many crucial quantum learning techniques. In this paper, we develop a variational hybrid quantum–classical learning scheme to systematically probe for symmetries of |ψ⟩ with no a priori assumptions about the state. This procedure can be used to learn various symmetries at the same time. In order to avoid re-learning already known symmetries, we introduce an interactive protocol with a classical deep neural net. The classical net thereby regularizes against repetitive findings and allows our algorithm to terminate empirically with all possible symmetries found. An iteration of the learning algorithm can be implemented efficiently with non-local SWAP gates; we also give a less efficient algorithm with only local operations, which may be more appropriate for current noisy quantum devices. We simulate our algorithm on representative families of states, including cluster states and ground states of Rydberg and Ising Hamiltonians. We also find that the numerical query complexity scales well for up to moderate system sizes.

Near-term quantum algorithm for solving the MaxCut problem with fewer quantum resources

MaxCut is an NP-hard combinatorial optimization problem in graph theory. The quantum approximate optimization algorithms (QAOAs) offer new methods for solving such problems, which are potentially better than classical schemes. However, the requirement of N qubits for solving graphs with N-vertex in QAOA, coupled with the large-N trainability issue due to barren plateaus, poses a substantial challenge for noisy intermediate-scale quantum (NISQ) devices. Recently, a hybrid quantum–classical algorithm has been proposed for solving semidefinite programs (SDPs), named NISQ SDP Solver (NSS). In this paper, we study the performance of the NSS for solving MaxCut problem via the introduction of a near-term quantum algorithm and execution of experimental simulations. Since the MaxCut problem admits a relaxation into an SDP formulation, the SDP can be solved using NSS, with a subsequent classical post-processing step converting the hybrid density matrix into a MaxCut solution. After performing these steps, the near-term quantum algorithm will also inherit the advantages of NSS. We analyze the algorithm as compared to QAOAs and find that the depth of the quantum circuit is independent of the number of edges on the graph. Our algorithm requires logN qubits and has O(1) circuit depth. This implies that it uses exponentially fewer qubits compared to QAOAs while also requiring a significantly reduced circuit depth to solve the MaxCut problem. To demonstrate the effectiveness of the NSS, we focused on 3-regular graphs, 9-regular graphs, and ER graphs. Numerical results indicate that the quantum algorithm achieves a comparable approximation ratio with classical methods by solving the original high dimensional problem within a lower dimensional ansatz space. Analysis under various initial states shows that the algorithm exhibits a remarkably stable performance.

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.

Shallow Shadows: Expectation Estimation Using Low-Depth Random Clifford Circuits.

We provide practical and powerful schemes for learning properties of a quantum state using a small number of measurements. Specifically, we present a randomized measurement scheme modulated by the depth of a random quantum circuit in one spatial dimension. This scheme interpolates between two known classical shadows schemes based on random Pauli measurements and random Clifford measurements. We focus on the regime where depth scales logarithmically in the system size and provide evidence that this retains the desirable sample complexity properties of both extremal schemes while also being experimentally feasible. We present methods for two key tasks; estimating expectation values of certain observables from generated classical shadows and, computing upper bounds on the depth-modulated shadow norm, thus providing rigorous guarantees on the accuracy of the output estimates. We achieve our findings by bringing together tools from shadow estimation, random circuits, and tensor networks.

Jet schemes over auto-arc spaces and deformations of locally complete intersection varieties

We consider reduced generalized jet schemes LZ(Y) along Z of a infinitesimal deformation Y of a complete intersection variety X over the same fat point Z. By definition, these reduced generalized jet schemes LZ(Y) live over the so-called reduced auto-arc spaces AZ, which were originally introduced by H. Schoutens and later studied by the author. Some well-known results of M. Mustaţǎ on classical jet schemes of locally complete intersections carry over to this case. For example, as a consequence of miracle flatness and some generalizations of the aforementioned results of M. Mustaţǎ, it is shown that the reduced generalized jet space, denoted Ln(Xn), of a flat deformation Xn→Dn along ▪ is usually a global flat deformation over Akn of the classical jet scheme Ln(X) provided the base scheme X is a locally complete intersection and the fibers are all of minimal dimension. Similar interesting relativized versions of those aforementioned results are also explored. Also, the initiation of the so-called regulated defect of a formal deformation in analogy to log canonical threshold is introduced. In the end, the situation is studied when the base scheme X is an algebraic curve, and the notions of so-called strong/weak deformations is introduced in this context. Finally, a so-called deformed motivic volume is defined.

IMPROVING THE INTERACTION OF THE TYPES OF TRUCK TRANSPORTATION AT THE "NIBULON" TERMINAL IN KREMENCHUTS WHEN TRANSPORTING GRAIN LOADS

Purpose. Russia's full-scale military aggression against Ukraine significantly disrupted logistics chains, including those that ensured the export of grain. The classic transportation system at “Niboulon” terminals is focused on transshipment of grain from road to river transport with subsequent transportation to foreign countries by “river-sea” vessels. To ensure the full operation of grain terminals after disruption of water transport in the water area of the Dnipro River, it is advisable to conduct a study on the shipment of grain products to alternative modes of transport (road, rail). Accordingly, the purpose of the research is to improve the interaction of types of freight transport at the Kremenchug terminal “Nibullon” in today's conditions when the work of water transport is blocked. The classic operation scheme of the "Nibulon" grain terminal was analyzed. Scientific methods and a method of improving the interaction of different types of transport in the terminal during grain transshipment are substantiated, the determination of the optimal mass of products transferred from the terminal to the main transport is proposed. Methods. An analysis of literary sources was carried out, which made it possible to establish the peculiarities of grain transportation. Methods of set theory, theory of algorithms, theory of transport processes and systems, theory of systems are used. It was established that the optimal mass of products transferred from the terminal to the main transport depends on the average daily number of cars, the gross weight of the car, the traction characteristics of the shunting locomotive and the distance between the terminal and the sorting station of the main transport. Scientific novelty. The scientific novelty obtained as a result of the research to which the article is devoted is the method of determining the average daily number of vehicles (cars, wagons, ships) arriving at the Kremenchug terminal "Nibulon", which depends on the average annual cargo turnover for each mode of transport, the weight of the cargo in the vehicle and the number of working days per year of each type. Practical significance. The mathematical expectation of the optimal mass of grain products transferred from the terminal to the main railway transport is established. In further research, the obtained results will be used as initial data for modeling the operation of grain terminals located along the Dnipro riverbed, and in the future - in the direction of the Black Sea ports of Ukraine.

ПРИНЦИПЫ И МЕТОДЫ ОБУЧЕНИЯ СЛОВОСОЧЕТАНИЯМ БУРЯТСКОГО ЯЗЫКА В АСПЕКТЕ ТРЕБОВАНИЙ ФГОС

This article is devoted to teaching phrases of the Buryat language in terms of the requirements of the Federal State Educational Standard. The Federal State Educational Standard focuses on the development of the child's personality. This task requires a new approach from the teacher to the organization of the learning process. The lesson, as it was before, remains the main unit of learning activity. But now the requirements for the lesson have changed, and a different classification of lessons has been proposed. The specificity of the system-activity approach assumes a different structure of the lesson, which differs from the usual, classical scheme. When teaching phrases of the Buryat language, the authors propose the application of strategic and tactical principles of language teaching, put forward by Dudnikov A.V. From the patterns of assimilation of native speech, discovered by the famous methodologist L. P. Fedorenko, the following principles of teaching the Buryat language follow: the principle of attention to the matter of language, the principle of understanding linguistic meanings, the principle of developing expressiveness of speech, the principle of comparing oral and written speeches. A system of exercises has been compiled aimed at improving skills and abilities in the construction and use of phrases of the Buryat language in the oral and written speech of students. The considered principles of language teaching constitute a theoretical basis on the basis of which teaching methods can be determined.

A Péclet-robust Discontinuous Galerkin method for nonlinear diffusion with advection

We analyze a Discontinuous Galerkin method for a problem with linear advection–reaction and [Formula: see text]-type diffusion, with Sobolev indices [Formula: see text]. The discretization of the diffusion term is based on the full gradient including jump liftings and interior-penalty stabilization while, for the advective contribution, we consider a strengthened version of the classical upwind scheme. The developed error estimates track the dependence of the local contributions to the error on the local Péclet numbers. A set of numerical tests support the theoretical derivations.

A second-order in time, BGN-based parametric finite element method for geometric flows of curves

Over the last two decades, the field of geometric curve evolutions has attracted significant attention from scientific computing. One of the most popular numerical methods for solving geometric flows is the so-called BGN scheme, which was proposed by Barrett et al. (2007) [8], due to its favorable properties (e.g., its computational efficiency and the good mesh property). However, the BGN scheme is limited to first-order accuracy in time, and how to develop a higher-order numerical scheme is challenging. In this paper, we propose a fully discrete, temporal second-order parametric finite element method, which integrates with two different mesh regularization techniques, for solving geometric flows of curves. The scheme is constructed based on the BGN formulation and a semi-implicit Crank-Nicolson leap-frog time stepping discretization as well as a linear finite element approximation in space. More importantly, we point out that the shape metrics, such as manifold distance and Hausdorff distance, instead of function norms, should be employed to measure numerical errors. Extensive numerical experiments demonstrate that the proposed BGN-based scheme is second-order accurate in time in terms of shape metrics. Moreover, by employing the classical BGN scheme as mesh regularization techniques, our proposed second-order schemes exhibit good properties with respect to the mesh distribution. In addition, an unconditional interlaced energy stability property is obtained for one of the mesh regularization techniques.

Design and Implementation of Extremum-Seeking Control Based on MPPT for Dual-Axis Solar Tracker

The increase in the production efficiency of photovoltaic technology depends on its alignment in relation to the solar position. Solar tracking systems perform the tracking action by implementing control algorithms that help the reduction of tracking errors. However, conventional algorithms can reduce the life of actuators and mechanisms due to control action, significantly reducing operation times and profitability. In this article, an unconventional control scheme is developed to address the mentioned challenges, presenting the design and implementation of an extremum-seeking control to perform maximum power point tracking for a two-axis solar tracker instrumented with a solar module. The proposed controller is governed by the dynamics of a classic proportional-integral scheme and assisted by sensorless feedback. Also, it has an anti-wind-up-type configuration for the integral component and counts with a variable amplitude for the dither signal. The proposal is validated experimentally by comparison between a fixed system and a two-axis system in azimuth-elevation configuration. In addition, two performance indices are defined and analyzed, system energy production and tracking error. The results show that the proposal allows producing up to 27.75% more than a fixed system, considering the tracker energy consumption due to the tracking action and a pointing accuracy with ±1.8° deviation. Finally, an analysis and discussion are provided based on the results, concluding that the proposed algorithm is a viable alternative to increase the performance of tracked photovoltaic systems.

Frequency‐Division Multiplexing Continuous Variable Quantum Dense Coding with Broadband Entanglement

AbstractQuantum dense coding (QDC) provides great potential for high‐capacity quantum communication. However, it is highly demanded for practical applications to realize high‐capacity QDC with multiple coded information. Here, a high‐capacity QDC with multiple streams is reported in different channels simultaneously through frequency‐division multiplexing (FDM). The broadband entangled state is generated from a pair of degenerate optic al parametric amplifiers with short cavity lengths. Based on the resultant broadband entanglement, multiple pieces of information coded using binary phase shift keying (BPSK) are transferred with the FDM method. As an experimental demonstration, four pieces of information composed of pseudo‐random numbers are transmitted at a rate of 4 Mbit s–1 using BPSK encoding. The decoded bit error rate reaches , which is an average 35‐fold improvement compared with the classical scheme. Furthermore, it is possible to make full use of sideband resource for four different information by using orthogonal FDM. This scheme can be extended to more different information by directly increasing the FDM sideband subchannels, and opens an avenue to construct high‐capacity quantum communication, while minimizing the cost of quantum resource.

Anderson acceleration for PWR whole-core pin-by-pin Nu-TH coupling calculation in NECP-Bamboo2.0

For PWR whole-core pin-by-pin neutronics/thermal-hydraulics (Nu-TH) coupling analysis, the Picard iteration strategy is widely employed benefitting from the convenience of implementation. Nevertheless, it is limited to the global multi-physics convergence rate regarding its oscillatory convergence behaviors in the local solution of each single-physics field. In this paper, the Anderson Acceleration (AA) scheme is employed and investigated to enhance the convergence performance of the pin-by-pin Nu and subchannel TH coupling analysis code NECP-Bamboo2.0. Different from the classical relaxation scheme where the relaxation factor is predetermined and fixed, the AA scheme utilizes the linear combination of several previous solutions to correct the current solution. The coefficients of this linear combination can be obtained by solving the residual equation, making the approach more robust. In addition, the selection of the accelerated solution vector is investigated based on the tightly coupling strategy of Nu-TH in NECP-Bamboo2.0. It is illustrated that the neutron-transport solution vector could have superior theoretical acceleration performance compared to the commonly used TH solution vector in the practical PWR analysis scenario. Finally, the AA scheme in NECP-Bamboo2.0 is validated using the VERA#6 3D single-assembly transport/TH coupling benchmark problem and the VERA#7 3D whole-core multi-physics coupling benchmark. It is demonstrated by the numerical results that the AA scheme possesses good robustness and computational efficiency. For the 3D whole-core VERA#7 benchmark, compared with the classic Picard iteration with a relaxation factor of 0.5, the AA scheme based on the neutron-transport solution vector can reduce the number of global iterations and calculation time by around 80%.

A uniform non-linear subdivision scheme reproducing polynomials at any non-uniform grid

In this paper, we introduce a novel non-linear uniform subdivision scheme for the generation of curves in Rn, n≥2. This scheme is distinguished by its capacity to reproduce second-degree polynomial data on non-uniform grids without necessitating prior knowledge of the grid specificities. Our approach exploits the potential of annihilation operators to infer the underlying grid, thereby obviating the need for end-users to specify such information. We define the scheme in a non-stationary manner, ensuring that it progressively approaches a classical linear scheme as the iteration number increases, all while preserving its polynomial reproduction capability.The convergence is established through two distinct theoretical methods. Firstly, we propose a new class of schemes, including ours, for which we establish C1 convergence by combining results from the analysis of quasilinear schemes and asymptotically equivalent linear non-uniform non-stationary schemes. Secondly, we adapt conventional analytical tools for non-linear schemes to the non-stationary case, allowing us to again conclude the convergence of the proposed class of schemes.We show its practical usefulness through numerical examples, showing that the generated curves are curvature continuous.

A Case of Food-Borne Salmonellosis in a Corn Snake (Pantherophis guttatus) after a Feeder Mouse Meal

Reptiles are usually asymptomatic carriers of Salmonella, with the manifestation of typical clinical signs of acute forms in adult and non-immunocompromised animals being considered exceptions. In the present case, an adult male corn snake (Pantherophis guttatus) was found dead due to septic shock 48 h after consuming a feeder mouse purchased online. The snake’s tissue samples and faeces were cultured for bacteria isolation. Microbiological examinations of the snake and mouse livers revealed the presence of Salmonella enterica subsp. enterica serovar Midway. A whole-genome analysis of these two isolates showed a high correlation between them: they belonged to the strain type ST-357 for the classic MLST scheme and to the strain type ST 171322 for the cgMLST scheme. Also, a virulence gene analysis revealed the presence of stdB and STM3026 genes. This report conveys a case of food-borne salmonellosis in a pet snake, transmitted from a feeder mouse, likely responsible for the snake’s death due to septic shock. It highlights the relevance of feeder mice as a source of Salmonella infections in snakes and the associated risks to human health.

High Order Asymptotic Preserving and Classical Semi-implicit RK Schemes for the Euler–Poisson System in the Quasineutral Limit

High Order Asymptotic Preserving and Classical Semi-implicit RK Schemes for the Euler–Poisson System in the Quasineutral Limit

TRA-PS: Accountable data Pub/Sub service with fast and fine-grained controllable subscription

The Cloud-based data publish/subscribe (Pub/Sub) service presents a selective manner for publishers and subscribers to share and receive data, where confidentiality and authorized access to the data are the fundamental security properties. Therefore, the methodology of attribute-based keyword search (ABKS) was applied that recently considered bilateral access control between the publisher and subscriber. However, existing data Pub/Sub solutions fail to take into account the following features: (i) the efficient revocation of subscribers; (ii) the traceability and auditability of subscriptions; (iii) the excessive time cost of decryption procedure. Therefore, we propose TRA-PS, an accountable data Pub/Sub service that implements efficient revocation, traceability, and public auditability for subscriptions. Technically, we refine the secret key of subscriber in the classic ABKS schemes with associating its identity information and binding accountability module. In addition, we implement TRA-PS and evaluate its practical performance compared to state-of-the-art work in the real cloud environment. Besides achieving accountable property, TRA-PS significantly diminishes the decryption time cost (number of attributes/keywords is 25) by 91.8%, independent of the number of attributes/keywords.