Multilayer System Research Articles

Enhanced Security Framework for Multi-Layered Wireless Communication Systems

The goal is to predict a Windows machine’s probability of getting infected by various families of malware, based on different properties of that machine. The telemetry data containing these properties and the machine infections was generated by combining heartbeat and threat reports collected by Microsoft’s endpoint protection solution, Windows Defender. Each row in this dataset corresponds to a ma- chine, uniquely identified by a Machine Identifier. Has Detections is the ground truth and indicates that Malware was detected on the machine. Using the information and labels in train.csv, you must predict the value for Has Detections for each machine in test.csv. The sampling methodology used to create this dataset was designed to meet certain business constraints, both in regards to user privacy as well as the time period during which the machine was running. Malware detection is inherently a time-series problem, but it is made complicated by the introduction of new machines, machines that come online and offline, machines that receive patches, machines that receive new operating systems, etc. While the dataset provided here has been roughly split by time, the complications and sampling requirements mentioned above may mean you may see imperfect agreement between your cross validation, public, and private scores! Additionally, this dataset is not representative of Microsoft customers machines in the wild it has been sampled to include a much larger proportion of malware machines

Quantum Genetic Algorithm-Driven Optimization of Triple-Glazed Window Thickness for Enhanced Light Reduction

Abstract. Glass, a common construction material, generally lacks significant thermal properties. As technology rapidly advances, the demand for glass materials with superior heat preservation and thermal insulation capabilities increases, driven by the need to reduce building energy consumption. Multi-objective optimization problems, particularly in complex multilayered systems, require advanced numerical optimization algorithms. The quantum-inspired genetic algorithm (QIGA) offers advantages such as fast solving speed and high precision, utilizing quantum coding, variation, rotation gates, and crossing techniques. This study focuses on designing the optimal thickness of triple-layer glass to minimize sunlight penetration through windows, using QIGA to achieve this goal. The results demonstrate that triple glazing effectively reduces solar radiation entering a room, though different layer combinations lead to significant variations in total energy reduction. The study also emphasizes the importance of concurrent research in glass layer splicing technology, coating film techniques, and new glass materials to enhance overall performance. These findings contribute to the development of energy-efficient building materials that meet modern standards for thermal insulation and light control.

Optimizing pharmaceutical supply chain management through AI-driven predictive analytics: A conceptual framework

The pharmaceutical supply chain is a complex, multi-layered system that faces unique challenges, including fluctuating demand, stringent regulatory requirements, and logistical constraints. This paper explores the role of AI-driven predictive analytics in optimizing pharmaceutical supply chain management, presenting a conceptual framework that enables companies to leverage advanced data analytics for improved decision-making, risk management, and operational efficiency. Key AI techniques, such as machine learning, data mining, and predictive demand forecasting, are discussed as tools for addressing critical supply chain issues, including inventory optimization, demand variability, and regulatory compliance. The proposed framework details essential components—data collection, processing, integration with existing systems, and real-time decision-making—and outlines critical success factors for effective implementation. By offering insights into the transformative potential of predictive analytics, this paper provides actionable recommendations for pharmaceutical companies seeking to build resilient and responsive supply chains. Future research directions are also proposed, emphasizing the need for adaptable predictive models and the ethical implications of AI applications in pharmaceuticals. Keywords: Pharmaceutical Supply Chain, AI-driven Predictive Analytics, Machine Learning, Demand Forecasting, Inventory Optimization, Regulatory Compliance.

Thermal stress concentration points and stress mutations in nano-multilayer film structures

In the multilayer film-substrate system, thermal stress concentration and stress mutations cause film buckling, delamination and cracking, leading to device failure. In this paper, we investigated a multilayer film system composed of a substrate and three film layers. The thermal stress distribution inside the structure was calculated by the finite element method, revealing significant thermal stress differences between the layers. This is mainly due to the mismatch of the coefficient of thermal expansion between materials. Different materials respond differently to changes in external temperature, leading to compression between layers. There are obvious thermal stress concentration points at the corners of the base layer and the transition layer, which is due to the sudden change of the shape at the geometric section of the structure, resulting in a sudden increase in local stress. To address this issue, we chamfered the substrate and added an intermediate layer between the substrate and the transition layer to assess whether these modifications could reduce or eliminate the thermal stress concentration points and extend the service life of the multilayer structure. The results indicate that chamfering and adding the intermediate layer effectively reduce stress discontinuities and mitigate thermal stress concentration points, thereby improving interlayer bonding strength.

Boric acid-free electrodeposition process and solar–thermal energy conversion of and Ni-carbon black nanocomposite coatings

AbstractThis work focuses on the development of a multi-layered system, of bright nickel electrodeposited on a steel substrate, and a second layer composed of black nickel either with or without carbon black nanoparticles (CB NPs), aiming for an efficient conversion of incident solar radiation into heat, for the fabrication of solar collectors. The structural characterization, revealed that the bright nickel film was composed of metallic nickel, while the black coatings contained amorphous nickel compounds. SEM analysis unveiled the presence of pinholes on the surface of the bright nickel film, suggesting that the black nickel coating was ineffective in sealing them. The appearance of cracks with the increase in the deposition time was observed. With the nanocomposite of black nickel and CB NPs, these cracks can be avoided and the pinholes sealed. The CB NPs were found to reduce reflectance, enhancing the conversion of solar energy into heat. Graphical abstract

Influence of Finishing Process Parameters of HDF Boards on Selected Properties of Coatings in Modern UV Lines and Their Relation to Energy Consumption

This study analyzes the influence of energy generated by emitters on the adhesive properties of varnish coatings in multilayer UV systems. The experimental material, in the form of a cell board finished with UV varnish products, was prepared on a prototype line under the conditions of Borne Furniture in Gorzów Wielkopolski. The roughness and wettability were measured using a OneAttension tensiometer integrated with a topographic module, taking into account the Wenzel coefficient. The adhesion of the examined systems was verified using the PositiTest AT-A automatic pull-off device. Energy consumption by the prototype production line was compared to the standard line, utilizing mercury emitters and mercury emitters with added gallium. Energy consumption was calculated for selected variants. The influence of the Wenzel coefficient on the wettability angle was observed. Significant differences between contact angles (CA and CAc) were noted for coatings formed with sealers (stages I and II). The largest discrepancies, reaching up to 30 degrees, were recorded at the lowest UVA and UVV doses of 26 mJ/cm2. In adhesion tests, values below 1 MPa were obtained. Insufficient energy doses in the curing process of UV systems led to delamination between the coatings. Five variants were selected where delamination within the substrate predominated (˃90% A) and were characterized by the lowest energy consumption in the processes. Topographic images helped identify the presence of various surface microstructures at different stages of the production cycle. The greatest energy savings, up to 50%, were achieved in stages III and IV of the technological process.

Recognition of a Fungal Effector Potentiates Pathogen-Associated Molecular Pattern-Triggered Immunity in Cotton.

Plants are equipped with multi-layered immune systems that recognize pathogen-derived elicitors to activate immunity. Verticillium dahliae is a soil-borne fungus that infects a broad range of plants and causes devastating wilt disease. The mechanisms underlying immune recognition between plants and V. dahliae remain elusive. Here, a V. dahliae secretory protein, elicitor of plant defense gene (VdEPD1), acts as an elicitor that triggers defense responses in both Nicotiana benthamiana and cotton plants is identified. Targeted gene deletion of VdEPD1 enhances V. dahliae virulence in plants. Expression of VdEPD1 triggers the accumulation of reactive oxygen species (ROS) and the activation of cell death in cotton plants. Gossypium barbadense EPD1-interacting receptor-like cytoplasmic kinase (GbEIR5A) and GbEIR5D interact with VdEPD1. Silencing of GbEIR5A/D significantly impairs VdEPD1-triggered cell death in cotton plants, indicating the contribution of GbEIR5A/D to VdEPD1-activated effector-triggered immunity (ETI). VdEPD1 stimulates the expression of GbEIR5A and GbEIR5D in cotton plants. Interestingly, cotton plants with silenced GbEIR5A/D genes exhibit compromised pathogen-associated molecular patterns (PAMPs)-triggered ROS accumulation, whereas overexpression of GbEIR5A or GbEIR5D enhances PAMP-induced ROS. These findings indicate that recognition of VdEPD1 potentiates GbEIRs to enhance cotton PAMP-triggered immunity (PTI), uncovering a cooperative interplay of PTI and ETI in cotton.

Variational inequalities of multilayer elastic contact systems with interlayer friction: Existence and uniqueness of solution and convergence of numerical solution

Inspired by the layered structure models in pavement mechanics research, in this study, a class of multilayer elastic contact systems with interlayer frictional contact conditions and deformable supporting frictional contact conditions on the foundation has been constructed. Based on the nonlinear elastic constitutive equations, the corresponding system of partial differential equations and variational inequalities are respectively introduced. Under the framework of variational inequalities, the existence and uniqueness of solutions for such models, along with the approximation properties of finite element numerical solutions, are proven and analyzed. The aforementioned conclusions provide fundamental and broadly applicable theoretical support for addressing mechanical problems in multilayer elastic contact systems within the framework of variational inequalities. Finally, the numerical experimental results based on the mixed finite element method also substantiate our theoretical conclusions.

Monte Carlo simulation of the magnetic properties of a multilayer mixed-spin system (5/2, 3/2)

Monte Carlo simulation of the magnetic properties of a multilayer mixed-spin system (5/2, 3/2)

Shock-induced twinning/detwinning and spall failure in Cu–Ta nanolaminates at atomic scales

Abstract This study provides new insights into the role of interfaces on the deformation and failure mechanisms in shock-loaded Cu–Ta–Cu trilayer system. The thickness of the Ta layer, piston velocities, and shock pulse durations were varied to explore the impact of impedance mismatch and loading conditions on spallation behavior and twin formation. It was found that the interfaces play a crucial role in the dynamic response of these multilayered systems since secondary reflection waves generated at the interfaces significantly affected the peak stress and pressure profiles, influencing void nucleation and failure modes. In the trilayer systems, failure predominantly occurred at interfaces and within the Ta layer, with void nucleation sites and twinning behavior being markedly different compared to single-crystal Cu and Ta. Increasing the Ta layer thickness modified the wave interactions, leading to different failure locations. Higher piston velocities were associated with increased spall strength by enhancing wave interactions and void formation, particularly at the interfaces and within the Ta layer, under specific configurations. Additionally, shorter shock pulse durations facilitated earlier initiation of the release fan, reducing twin formation and altering the failure dynamics by accelerating twin annihilation and pressure release.

Micro-friction Mechanism Characterization of Particle-Reinforced Multilayer Systems of 316L and 430L Alloys on Gray Cast Iron

Micro-friction Mechanism Characterization of Particle-Reinforced Multilayer Systems of 316L and 430L Alloys on Gray Cast Iron

Data protection enhancement in smart grid communication: An efficient multi-layer encrypting approach based on chaotic techniques and steganography

In this study, a multi-layer encryption system is proposed through which sensitive and important data in smart grids can be secured from unauthorized persons as well as cyber threats. The suggested system is analyzed using fundamental performance assessment metrics say as average processing times across ten runs, peak signal-to-noise ratio (PSNR), and root mean square error (RMSE). The encryption process involves hiding the data encrypted by a digital dictionary and the advanced encryption standard (AES) algorithm in an image. In this way, AES encryption suggests rapid processing with a short average time per each block; similarly, the decryption technique, which includes the dictionary and AES decryption also renders the results in a justified computational time nominating it as a practical approach. It is worth noting that the small key era and dictionary construction instances provoke innovations in the general efficiency of the encryption mechanism. The conducted study, based on recorded values for PSNR, RMSE, UACI, and NPCR, demonstrates that the proposed multi-layer encryption system, which incorporates dictionary encryption and AES, is a robust and a fast method to shield important information and attaining a balance between protection and computational time.

The Accelerator State

China is creating an “accelerator state” through a multi-layered system to identify and fast track the growth of high-tech SMEs in strategic sectors. Certified high-tech SMEs enjoy unique advantages, most notably privileged access to public and private financing. An analysis of the “Little Giants” program—a central feature of the accelerator state—proves that selected firms are indeed benefiting from enhanced financing. The study also reveals flaws in its selection process. The implications for foreign actors are significant. The accelerator state aims to replace imports in key value chains, which poses a direct challenge to foreign firms. The blurred lines between state support and market forces in the scheme also make it more difficult for foreign governments to track distortionary practices and enforce fair competition.

Cooperative Nernst effect of multilayer systems: Parallel circuit model study

Transverse thermoelectric power generation has emerged as a topic of immense interest in recent years owing to the orthogonal geometry which enables better scalability and fabrication of devices. Here, we investigate the thickness dependence of longitudinal and transverse responses in film-substrate systems, i.e., the Seebeck coefficient, the Hall coefficient, the Nernst coefficient, and the anomalous Nernst coefficient in a unified and general manner based on the circuit model, which describes the system as the parallel setup. By solving the parallel circuit model, we show that the transverse responses exhibit a significant peak, indicating the importance of a cooperative effect between the film and the substrate, arising from circulating currents that occur in these multilayer systems in the presence of a temperature gradient. Finally, on the basis of realistic material parameters, we predict that the Nernst effect in bismuth thin films on doped silicon substrates is boosted to unprecedented values if the thickness ratio is tuned accordingly, motivating experimental validation. Published by the American Physical Society 2024

Role of mechanical stress localizations on the radiation hardness of AlGaN/GaN high electron mobility transistors

Abstract Multi-material, multi-layered systems such as AlGaN/GaN high electron mobility transistor (HEMTs) contain residual mechanical stresses that arise from sharp contrasts in device geometry and materials parameters. These stresses, which can be either tensile or compressive, are difficult to detect and eliminate because of their highly localized nature. We propose that their high stored internal energy make potential sites for defect nucleation sites under radiation, particularly if their locations coincide with the electrically sensitive regions of a transistor. In this study, we validate this hypothesis with molecular dynamic simulation and experiments exposing both pristine and annealed HEMTS to 2.8 MeV Au+3 irradiation. Our unique annealing process uses mechanical momentum of electrons, also known as the electron wind force (EWF) to mitigate the residual stress at room temperature. High-resolution transmission electron microscopy (TEM) and cathodoluminescence spectra reveal the reduction of point defects and dislocations near the two-dimensional electron gas region of EWF-treated devices compared to pristine devices. The EWF-treated HEMTs showed relatively higher resilience with approximately 10% less degradation of drain saturation current and ON-resistance and 5% less degradation of peak transconductance. Both mobility and carrier concentration of the EWF-treated devices were less impacted compared to the pristine devices. Our results suggest that the lower density of nanoscale stress localization contributed to the improved radiation tolerance of the EWF-treated devices. Intriguingly, the EWF is found to modulate the defect distribution by moving the defects to electrically less sensitive regions in the form of dislocation networks, which act as sinks for the radiation induced defects and this assisted faster dynamic annealing.

Dependence of interfacial mixing for thermally induced magnetization switching in Gd/Fe multilayers

The use of femtosecond laser pulses for ultrafast triggering of magnetization switching is of great interest in multilayer systems with great tunability. At present, the impact of interfacial mixing on magnetization switching has not been thoroughly investigated. In this paper, the impact of interfacial mixing on magnetization dynamics in multilayer systems is investigated by a combination of atomic spin dynamics and two-temperature models. Our results show that interfacial mixing in multilayer systems not only reduces the energy density required for magnetization switching but also expands the range of pulse durations that can trigger magnetization switching. In addition, we have investigated the dependence of the switching time on the interfacial mixing in multilayer systems. The results show that interfacial mixing can accelerate the process of magnetization dynamics, thus providing a theoretical basis for the design of faster speed optically controlled magnetic tunnel junctions.

Weyl points in a twisted multilayer photonic system

We numerically demonstrate the creation of Weyl points in a twisted multilayer photonic system. In our system, each layer is anisotropic with plasmonic response along a direction perpendicular to the layer and with anisotropic dielectric response within the layer. We show that Weyl points can be created by controlling the twist angles between the layers so that spatial-inversion symmetry is broken. Compared with existing approaches, our findings offer a potentially simpler structure for creating Weyl points and highlight the prospect of using twisted multilayer systems for achieving topological photonic effects.

Multi-layer Active Biopolymer System as a Perspective for Improving the Quality and Scope of Applying Semi-rigid Biodegradable Packaging

AbstractIn this study, the possibility of modifying a multi-layer biopolymer active system to reduce permeability to gases of a biodegradable material with potential application in food technology was analysed. A four-layer biopolymer film was used, wherein the initial two layers comprised furcellaran, whilst the subsequent two layers were a mixture of chitosan and gelatin. The film was modified with active ingredients, including silver nanoparticles (AgNPs), montmorillonite, a curcumin-capsaicin mixture and gelatin hydrolysate. The film formed an integrated, semi-rigid packaging system together with the tray, which was developed from tea brewing waste and biopolymers. Application properties were assessed by analysing mechanical parameters, key to the assessment of their quality, proving that the active ingredients significantly improved the strength properties. There was an almost twofold increase in modulus of elasticity values compared to the control film. The permeability against oxygen was also assessed as the main performance characteristic of the packaging and was only 13.64 ± 3.92 [cm3/m2 × 24 h]. The impact of the applied material innovation in packaging on the freshness of food products was also evaluated by analysing the microbiological purity of stored Salmo Salar fillet. The active, biodegradable packaging extended the shelf-life of salmon by 6 days compared to the low-density polyethylene (LDPE) film. Toxicity analysis has shown that the used active ingredients are safe for the environment and consumers.

Multi-Layered Unsupervised Learning Driven by Signal-to-Noise Ratio-Based Relaying for Vehicular Ad Hoc Network-Supported Intelligent Transport System in eHealth Monitoring.

Every year, about 1.19 million people are killed in traffic accidents; hence, the United Nations has a goal of halving the number of road traffic deaths and injuries by 2030. In line with this objective, technological innovations in telecommunication, particularly brought about by the rise of 5G networks, have contributed to the development of modern Vehicle-to-Everything (V2X) systems for communication. A New Radio V2X (NR-V2X) was introduced in the latest Third Generation Partnership Project (3GPP) releases which allows user devices to exchange information without relying on roadside infrastructures. This, together with Massive Machine Type Communication (mMTC) and Ultra-Reliable Low Latency Communication (URLLC), has led to the significantly increased reliability, coverage, and efficiency of vehicular communication networks. The use of artificial intelligence (AI), especially K-means clustering, has been very promising in terms of supporting efficient data exchange in vehicular ad hoc networks (VANETs). K-means is an unsupervised machine learning (ML) technique that groups vehicles located near each other geographically so that they can communicate with one another directly within these clusters while also allowing for inter-cluster communication via cluster heads. This paper proposes a multi-layered VANET-enabled Intelligent Transportation System (ITS) framework powered by unsupervised learning to optimize communication efficiency, scalability, and reliability. By leveraging AI in VANET solutions, the proposed framework aims to address road safety challenges and contribute to global efforts to meet the United Nations' 2030 target. Additionally, this framework's robust communication and data processing capabilities can be extended to eHealth monitoring systems, enabling real-time health data transmission and processing for continuous patient monitoring and timely medical interventions. This paper's contributions include exploring AI-driven approaches for enhanced data interaction, improved safety in VANET-based ITS environments, and potential applications in eHealth monitoring.

Statement of Retraction: Application of particle swarm optimization, and genetic algorithm methods for maximizing the phase velocity in the multi-layer nanoscale system

Statement of Retraction: Application of particle swarm optimization, and genetic algorithm methods for maximizing the phase velocity in the multi-layer nanoscale system