Application Of Technology Research Articles

Efficient mapping of phase diagrams with conditional Boltzmann Generators

Abstract The accurate prediction of phase diagrams is of central importance for both the fundamental understanding of materials as well as for technological applications in material sciences. However, the computational prediction of the relative stability between phases based on their free energy is a daunting task, as traditional free energy estimators require a large amount of simulation data to obtain uncorrelated equilibrium samples over a grid of thermodynamic states. In this work, we develop deep generative machine learning models based on the Boltzmann Generator approach for entire phase diagrams, employing normalizing flows conditioned on the thermodynamic states, e.g., temperature and pressure, that they map to. By training a single normalizing flow to transform the equilibrium distribution sampled at only one reference thermodynamic state to a wide range of target temperatures and pressures, we can efficiently generate equilibrium samples across the entire phase diagram. Using a permutation-equivariant architecture allows us, thereby, to treat solid and liquid phases on the same footing. We demonstrate our approach by predicting the solid-liquid coexistence line for a Lennard-Jones system in excellent agreement with state-of-the-art free energy methods while significantly reducing the number of energy evaluations needed.

Nanocomposites of Thermosetting Polymers and Graphene Quantum Dots—Physical Attributes and Ongoing Progressions

Thermosets, before hardening, consist of independent macromolecules similar to thermoplastics, however, chemical curing of these macromolecules via heat or radiations may form irreversibly crosslinked macromolecular networks between their main chains. Graphene quantum dots are inimitable spherical nano-entities having the advantages of extremely small sizes, of 5-10 nm, very high surface area, surface/edge effects, quantum confinements and a range of physical characteristics including semiconductivity, fluorescence and magnetic properties. Similar to other nanocarbons (like graphene, fullerene or nanodiamonds), graphene quantum dots have been examined as noteworthy nanofillers to enhance the essential physical features of various macromolecular matrices, such as thermosets, thermoplastics and rubbers. Consequently, this review article was intended to systematically discuss the existing scientific state of graphene quantum dots reinforced thermosetting macromolecular matrices for the formation of high performance nanomaterials. According to the literature reports, the type, amount and molecular weight of these macromolecules seemed to affect the epoxy-quantum dots interactions and physical properties, like strength and heat stability of the resulting nanomaterials. Moreover, including graphene quantum dots in thermosetting matrices, like epoxies, hyperbranched polyesters and hyperbranched polyurethanes, has positively influenced the engineering aspects (mainly mechanical and thermal attributes) of the resulting nanocomposites owing to their interactions, compatibility and interfacial tendencies toward these matrices. Principally, epoxy/graphene quantum dots nanocomposites have been fabricated and investigated for the effects of graphene quantum nano-entities on the physical property enhancements of these irreversibly crosslinked macromolecules due to their mutual matrix-nanofiller interfaces. As per our analysis, the literature hitherto on the graphene quantum dots reinforced thermosetting matrix nanocomposites has disclosed significant property improvements of these macromolecules and their promising technological applications for high performance anticorrosion coatings, electromagnetic interference shields and biomedical fields.

Research progress on knowledge discovery in traditional Chinese medicine medical records based on artificial intelligence

Traditional Chinese Medicine (TCM) medical records represent the clinical practice records of physicians, encapsulaing a wealth of TCM clinical diagnosis and treatment experiences as well as academic thoughts of numerous TCM practitioners. Such various information provide certain basic conditions for the integration of artificial intelligence (AI) technology with TCM. Through analysing successful clinical records, AI technology can extract practical and understandable knowledge. Therefore, this paper summarizes and analyzes the application of information technology in the field of knowledge discovery research from Chinese medical records. It focuses on three key aspects: the resources of TCM Medical Records, the objects of TCM records mining, and the application of AI technology. The aim is to provide beneficial references for maximizing the value of TCM medical records.

Decentralized Integrity: Blockchain-Based Frameworks for Enhancing Software Update Security

This article examines the application of blockchain technology as a solution for secure and transparent software update distribution. As cyber threats evolve, traditional centralized update mechanisms face increasing vulnerabilities to tampering and unauthorized modifications. We propose a blockchain-based framework that leverages distributed ledger technology to create an immutable, decentralized environment for software updates. Our article demonstrates how this approach can eliminate single points of failure, ensure update integrity through cryptographic signing and network-wide verification, and enhance transparency in the update process. We discuss the system architecture, including update creation, distribution, and verification mechanisms, and evaluate its integration with existing software ecosystems. While acknowledging challenges such as scalability and implementation costs, we argue that blockchain-based solutions significantly advance securing software distribution. Our findings suggest that this approach has the potential to become a standard practice in the industry, substantially improving trust and reliability in software update systems. This article contributes to the growing body of research on blockchain applications in cybersecurity and provides insights for future developments in secure software distribution methods.

An Efficient Time‐Sensitive Networking Traffic Scheduling Method for Train Communication Network

As a critical system of rail train, the train communication network (TCN) is an integrated central platform that is used to realize the train operation control, condition monitoring, and data transmission. With the development of train intelligence, the scale of data flow in TCN continues to expand, and the control data and monitoring data must be real‐time transmitted to ensure the safe and reliable operation of the train. Time‐sensitive network (TSN) can be applied as the next‐generation TCN solution, which provides end‐to‐end data transmission with extremely low delay and high reliability based on Ethernet. For the application of TSN technology in TCN, a single frame simple scheduling method is proposed to effectively reduce the worst end‐to‐end delay of the entire network, which improve the real‐time performance of TSN‐based TCN. The network topology and data flow characteristics in TCN are analyzed, a series of scheduling constraints are constructed, and the satisfiability modulo theories (SMT) is used to obtain a gate control list (GCL) to ensure the real‐time performance of time‐trigger streams. Finally, the TCN simulation model is established using OMnet++ software, the experiment results show that the proposed method can effectively reduce the overall delay and jitter, and meet the real‐time requirement of TCN. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Rational Strategies for Preparing Highly Efficient Tin-, Bismuth- or Indium Based Electrocatalysts for Electrochemical CO2 Reduction to Formic acid.

Electrochemical carbon dioxide reduction reaction (CO2RR) is an environmentally friendly and economically viable approach to convert greenhouse gas CO2 into valuable chemical fuels and feedstocks. Among various products of CO2RR, formic acid/formate (HCOOH/HCOO-) is considered the most attractive one with its high energy density and ease of storage, thereby enabling widespread commercial applications in chemical, medicine, and energy-related industries. Nowadays, the development of efficient and financially feasible electrocatalysts with excellent selectivity and activity towards HCOOH/HCOO- is paramount for the industrial application of CO2RR technology, in which Tin (Sn), Bismuth (Bi), and Indium (In)-based electrocatalysts have drawn significant attention due to their high efficiency and various regulation strategies have been explored to design diverse advanced electrocatalysts. Herein, we comprehensively review the rational strategies to enhance electrocatalytic performances of these electrocatalysts for CO2RR to HCOOH/HCOO-. Specifically, the internal mechanism between the physicochemical properties of engineering materials and electrocatalytic performance is analyzed and discussed in details. Besides, the current challenges and future opportunities are proposed to provide inspiration for the development of more efficient electrocatalysts in this field.

Blockchain Based Decentralized Storage Drive

The "Decentralized Storage Drive" project introduces a secure, blockchain-based platform for decentralized data storage and sharing. By integrating the Interplanetary File System (IPFS) for decentralized storage, the platform ensures that data remains immutable and resistant to censorship. Solidity smart contracts deployed on the Ethereum blockchain provide robust mechanisms for access control, allowing users to manage data ownership and permissions without relying on centralized authorities. A React-based front- end interface simplifies user interaction, enabling seamless data upload and access management. This project addresses critical issues related to data privacy, security, and ownership, offering a user-friendly solution that empowers individuals with greater control over their digital assets. Throughout the development of this project, a focus on security, user control, and decentralization has been paramount. The rigorous testing of smart contracts and the integration of secure authentication methods ensure that the platform is both reliable and resilient to potential threats. The "Decentralized Storage Drive" represents a significant advancement in the field of decentralized applications, demonstrating the practical application of blockchain technology in everyday data management. Key Words: Decentralized Storage, Blockchain Technology, IPFS(InterPlanetary File System), Smart Contracts, Data Integrity, Access Control

ПАРАДИГМА ЦИФРОВОГО МАРКЕТИНГУ

The article is devoted to the analysis of features and essence of digital marketing, and in particular the content of the modern paradigm of digital marketing. The interpretation of the concepts of digitalization (there is a process of application of digital, information and communication technologies and information on income, improvement of entrepreneurial activity, transformation of business processes, formation of the digital business environment, digitization of possible procedures and operations, etc.) and digital marketing (a set of marketing actions of the modern world. At the same time, digital marketing is a dual phenomenon, as it has a hybrid character: a certain share of functions is implemented online, and the rest - in an offline environment). The content of the modern paradigm of digital marketing is clarified - a set of ways and tools for promoting services or goods in markets using various technologies. The main advantages of digital marketing are allocated: interactivity in attracting consumers for active interaction with business structures, elimination of territorial restrictions in the implementation of the marketing goal, facilitating access to the Internet resources of the enterprise, opportunities to assess the effectiveness of marketing mechanisms and activities, use of marketing in management activities in real time. The main components of digital marketing are defined: content - chats, blogs, research, electronic newsletters, publications, electronic manuals, social networks, copies of sales pages, SEO; design - photos, images of content, diagrams, videos, infographics; statistics - leading performance indicators, analytics, conversion channels, etc.

Biomimetic Nanoparticles for Basic Drug Delivery

Biomimetic nanoparticles (BMNPs) are innovative nanovehicles that replicate the properties of naturally occurring extracellular vesicles, facilitating highly efficient drug delivery across biological barriers to target organs and tissues while ensuring maximal biocompatibility and minimal-to-no toxicity. BMNPs can be utilized for the delivery of therapeutic payloads and for imparting novel properties to other nanotechnologies based on organic and inorganic materials. The application of specifically modified biological membranes for coating organic and inorganic nanoparticles has the potential to enhance their therapeutic efficacy and biocompatibility, presenting a promising pathway for the advancement of drug delivery technologies. This manuscript is grounded in the fundamentals of biomimetic technologies, offering a comprehensive overview and analytical perspective on the preparation and functionalization of BMNPs, which include cell membrane-coated nanoparticles (CMCNPs), artificial cell-derived vesicles (ACDVs), and fully synthetic vesicles (fSVs). This review examines both “top-down” and “bottom-up” approaches for nanoparticle preparation, with a particular focus on techniques such as cell membrane coating, cargo loading, and microfluidic fabrication. Additionally, it addresses the technological challenges and potential solutions associated with the large-scale production and clinical application of BMNPs and related technologies.

A large language model-based agent for wayfinding: simulation of spatial perception and memory

ABSTRACT Using agents to simulate human wayfinding processes helps to understand human decision-making and spatial cognition. The performance of large language models (LLMs) in agent-based wayfinding is still unclear. To address this, this study harnessed the thinking and reasoning capabilities of LLMs by designing an agent wayfinding framework based on cellular automata. This framework provides environmental descriptions in text form to the LLMs, enabling them to perceive the wayfinding environment and navigate within it. We simulated different spatial memory conditions for the LLM, including three types of spatial memories and one condition with no spatial memory, to observe its wayfinding behavior in a real-world setting. Multiple experiments were designed to compare the wayfinding performance of the LLM under different spatial memories, and 32 human participants conducted the same wayfinding experiments for reference. The results indicate that the LLM autonomously explores the environment and displays spatial reasoning abilities similar to humans. Furthermore, the LLM can develop reasonable wayfinding strategies to complete the tasks. This framework allows agents with different spatial memories to accurately reach their destinations. This research provides new ideas for utilizing large language models to construct more intelligent, efficient, and flexible wayfinding agents, which can help advance the application of agent technology in fields such as navigation and robotics.

Early Identification of Learning and Developmental Disorders in School-Age Children

The aim of developing an online quiz assessment tool is to identify learning disabilities like ‘Dyslexia’, ‘Dyscalculia’, ‘ADHD’ and ‘Anxiety’ as early as possible in children for better educational outcomes. This study applied modern web technologies, such as HTML, CSS, JavaScript, PHP, and FLASK to come up with an easy interface that combines the extensive questionnaire with analytical algorithms. This tool also collects user data as they use it and hence gives information and feedback to a user as well as other stakeholders instantly. By means of user testing, the interface was characterized as easily applicable which contributed to the increase of the attention to the educational needs of the target audience. The main conclusions are that the tool promotes the detection of learning disorders in children as early as possible and encourages minimizing delays in treatment. The presented project is also focused on the application of technologies in the management of development difficulties as well as principles of design that are aimed at making the assessment tools more useful.

Investigating the role of graphene in the formation and stability of [formula omitted]-phase antimonene islands

Two-dimensional materials have shown tremendous potential for various technological applications. Particularly, 2D antimony exhibits high applicability in electronics, sensors, and batteries. This 2D material, known as antimonene, presents two stable phases: α (rectangular lattice) and β (honeycomb lattice), whose formation depends on the substrate where antimony is deposited. In this study, we investigated the growth of antimonene islands on graphene, forming an antimonene/graphene heterostructure. To demonstrate the significance of graphene in the synthesis of antimonene, we also studied antimony deposited on a bare copper foil similar to the one used for the graphene substrate. Antimony deposition exhibits the β phase antimonene structure when deposited on top of monolayer graphene, but not when deposited on a bare copper foil, nor on top of multilayer graphene. Additionally, we investigated the stability of the heterostructure after exposure to air. Pure antimony islands are formed when evaporated in high vacuum on top of graphene and copper substrates, and antimony atoms oxidize upon exposure to air. After annealing the sample in ultra-high-vacuum at temperatures lower than 200 °C, more than half of pure antimony is recovered and almost all oxidized antimony is desorbed from the graphene substrate. In contrast, almost none of the oxidized antimony is desorbed from the bare copper substrate, highlighting the key role of the heterostructure on the formation and preservation of the physical and chemical properties of the deposited 2D material.

Recent Developments and Prospects of Electromagnetically Active Metamaterials in Biosensing

This paper provides an overview of the progress of research on electromagnetically active metamaterials in the field of biosensing, especially the potential of terahertz metamaterials for biosensor applications. Electromagnetically active metamaterials exhibit a negative refractive index and perfect absorption through their special structure, and their electromagnetic behavior is affected by their structure and geometry, which is different from traditional materials. The article reviews the application of terahertz technology for the bio-detection of cancer cells and apoptotic processes using periodic metal arrays by terahertz biosensors, demonstrating the advantages of terahertz biosensors, such as high sensitivity and detection without labeling. This paper presents a comprehensive overview of the advancements in research concerning electromagnetically active metamaterials within the domain of biosensing, with a particular emphasis on the potential applications of terahertz metamaterials in biosensor technology. Electromagnetically active metamaterials are characterized by their negative refractive index and perfect absorption, which arise from their distinctive structural properties. The electromagnetic behavior of these materials is significantly influenced by their design and geometry, setting them apart from conventional materials. The article examines the utilization of terahertz technology for the bio-detection of cancer cells and apoptotic processes tunability, employing periodic metal arrays in terahertz biosensors. It underscores the advantages of terahertz biosensors, which include high sensitivity and the capability to detect biological entities without the necessity for labeling. Terahertz metamaterial biosensors are promising for protein, virus, and cancer cell detection. This paper also explores the design and application of chiral metamaterials, especially indium tin oxide-based mid-infrared chiral metamaterials, to solve the problem of the large size of traditional materials and investigates their circular dichroism. Looking ahead, electromagnetically active metamaterials, especially terahertz metamaterials, are expected to improve resolving power and sensitivity, reduce costs, and expand the applications of biosensors in the biomedical field. The applications and research of these sensors will continue to advance with the advancement of micro and nanoprocessing technologies.

Technology Acceptance and Innovation Diffusion: Are Users More Inclined Toward AIGC-Assisted Design?

Artificial Intelligence Generated Content (AIGC) has shown significant potential in design, driven by advancements in artificial intelligence technology. However, understanding designers’ willingness to embrace this technology and the factors influencing their decision-making requires further research. In this study, we develop a theoretical model of user behavioral intention in AIGC-assisted design, drawing upon the Diffusion of Innovations theory and the Unified Theory of Acceptance and Use of Technology. Through empirical analysis using the PLS-SEM structural equation model, we investigate the mechanisms behind various influencing factors on behavioral intention. Our findings highlight the relative advantage as the most significant positive factor, emphasizing the importance of the innovation’s benefits in the Diffusion of Innovations theory. Designers prioritize the innovation and assistance provided by AIGC technology in the design process and ideas, recognizing the advantages of the innovation itself over mere performance improvement. This study provides valuable insights into the psychological and behavioral mechanisms guiding designers’ decision-making regarding the application of AIGC technology in design.

Enhancing horticultural harvest efficiency: The role of moisture content in ultrasonic cutting of tomato stems

Ultrasonic vibration has notable benefits in the harvesting and processing of tomato stems, particularly in reducing cutting force and minimizing moisture loss. Given the anisotropic nature of biological materials, the moisture content of tomato stems significantly impacts their physical properties. This study investigates the influence of varying moisture content on temperature and cutting force during the ultrasonic cutting of tomato stems. Initially, the moisture content of tomato stems at different maturity stages was measured using a water activity meter. Mechanical properties were characterized using a universal testing machine, and thermal properties were analyzed with a differential scanning calorimeter (DSC). Regression models were established to correlate moisture content with these material properties. Additionally, a three-dimensional microscopic model of stem skeletons, interfaces, and fiber bundles was created to simulate the fracture mechanisms during ultrasonic cutting under different moisture levels. Single-factor and response surface optimization experiments were conducted using a custom experimental setup under varying maturity stages, excitation frequencies, and voltage variations. Results showed that after 24 h, the peak temperatures for tomato stems at different maturity stages were 97.84 °C, 80.59 °C, and 74.15 °C, with corresponding cutting forces of 0.492 N, 0.544 N, and 0.998 N, respectively. The discrepancy between experimental results and simulation data was within 10 %. Higher moisture content was found to enhance the thermal conductivity of fiber materials, aiding in the fracture of fiber bundles, thus reducing cutting time and force. This study provides a theoretical foundation for the application of ultrasonic technology in the efficient harvesting and processing of industrial crops, with significant implications for horticultural crop treatment and processing.

Enhanced electrical and mechanical properties of additively manufactured pure copper with green laser

The effort to improve the additive manufacturing (AM) of copper, which is essential in various industrial sectors, has led to the exploration of green laser powder bed fusion (GL-PBF). By using a high-energy green laser, we overcome the challenges posed by the high reflectivity of copper, which has previously hindered achieving the desired component densities and functionalities through AM. This study uncovers the key role of GL-PBF process parameters on the densification, microstructure, surface roughness, mechanical properties, and electrical conductivity of pure copper parts. Our findings demonstrate that optimizing GL-PBF parameters can achieve copper components with over 99.9 % relative density and 98 % international annealed copper standard (IACS) electrical conductivity. The combination of comprehensive experiments and finite element modeling also reveals how the critical role of defect morphology in affecting electrical conductivity. This work contributes to the broader application of AM technologies, especially for high-reflectivity metals, and also provides new insights into how these defects affect conductivity and should be controlled during the AM process.

Composite Fiber Wrapping Techniques for Enhanced Concrete Mechanics

This study systematically investigates the enhancement effects of different fiber-reinforced polymer (FRP) materials on the axial compressive performance of concrete. Through experimental evaluations of single-layer, double-layer, and composite FRP reinforcement techniques, the impact of various FRP materials and their combinations on concrete’s axial compressive strength and deformation characteristics was assessed. The results indicate that single-layer CFRP reinforcement significantly improves concrete axial compressive strength and stiffness, while double-layer CFRP further optimizes stress distribution and load-bearing capacity. Among the composite FRP reinforcements, the combination with CFRP as the outer layer demonstrated superior performance in enhancing the overall structural integrity. Additionally, numerical analyses of the mechanical behavior of the reinforced structures were conducted using ABAQUS 2023HF2 finite element software, which validated the experimental findings and elucidated the mechanisms by which FRP influences the internal stress field of concrete. This research provides theoretical support and empirical data for the optimized design and practical application of FRP reinforcement technologies in engineering.

Complex Permittivity Spectra of Granular Polymer Composites with Dispersed Ag-Coated Cu Flakes

AbstractConductive particle-containing granular composites with tuneable negative permittivity are being studied to improve the performance of electromagnetic devices, such as shielding materials. In this study, we investigated the relative complex permittivity and electrical conductivity of granular composites of polyphenylene sulfide (PPS) resin and Ag-coated Cu flakes in the radio- to microwave-frequency range and compared them with those of PPS/bare Cu flake composites. Electrical conductivity measurements revealed that the PPS/Ag-coated Cu flake composites have a lower percolation threshold (φc) than the PPS/bare Cu flake composites, whereas the electrical conductivity of the PPS/Ag-coated Cu flake composites in the percolated particle state was higher at the same particle volume fraction. At particle contents above φc, a low-frequency plasmonic state of conduction electrons was achieved in the percolated particle chains in both composites, and negative permittivity spectra were obtained. The percolated PPS/Ag-coated Cu flake composites had a negative permittivity up to a higher frequency than the percolated PPS/bare Cu flake composites. Furthermore, the Drude model was used to analyze the negative permittivity spectra of the composites in the percolated particle state. The plasma frequency of the composites with percolated Ag-coated Cu flakes was higher than that of the composites with percolated bare Cu flakes. Thus, coating Ag on Cu particles improved the conductivity of the composite, leading to negative permittivity up to higher frequencies. This study contributes to the enhancement of the negative permittivity achieved by granular composites, which is useful for microwave technology applications. Graphical Abstract

The Mentoring for Teachers at Primary School 1 Jati Wetan in Developing the E-Diagnostic Assessment Model based on Literacy to Manage Learning Loss of the Learners

The implementation of online learning has an unfavorable influence on students' motivation and enthusiasm for learning. So far, assessments have been carried out, but teachers at SD 1 Jati Wetan have never carried out an evaluation with e-diagnostic assessments. Community Service Activities aim to provide knowledge sharing and application of technology in order to improve teacher competence and skills by developing e-diagnostic assessments to overcome student learning loss and improve the quality of post-pandemic learning. Teachers are able to compile literacy-based e-diagnostic assessments with optimal application of technology. This activity is carried out in stages; 1) planning stage, (2) socialization and training stage for introducing literacy-based e-diagnostic assessments, (3) training and assistance stage for designing literacy-based e-diagnostic assessments, (4) technology application stage, (5) e-implementation stage literacy-based diagnostic assessment to identify learning loss, and (6) evaluation stage of program activities and sustainability. The results of Community Service activities are in the form of developing literacy-based e-diagnostic assessments and being skilled in their application to identify learning loss. Literacy-based diagnostic assessment products are implemented programmatically and productively by teachers.

1-bit absorption-diffusion acoustic coding metasurface

Acoustic metasurfaces demonstrate unprecedented potential for flexible capabilities of the acoustic wavefront manipulation. Especially, acoustic diffusers and absorbers via acoustic metasurfaces have garnered significant attention of researchers due to the excellent performance. However, although these diffusers and absorbers have achieved excellent acoustic scattering suppression, it still remains a significant challenge to obtain higher scattering suppression. Here, a 1-bit absorption-diffusion acoustic coding metasurface (ADM) is proposed, which can achieve high-performance acoustic backward scattering reduction in the operating frequency by combining the advantages of acoustic diffusers and absorbers. In order to realize the proposed ADM, two kinds of subwavelength dual-layer unit cells with opposite reflection phases and low amplitudes are introduced. Both simulated and experimental results demonstrate that the proposed ADM can achieve the pre-designed backward acoustic scattering reduction. The proposed integrated mechanism can provide a new method for designing high-performance acoustic metasurfaces, which can have potential applications in stealth technology, noise control and other relevant applications.