Related Technologies Research Articles

Systematic Analysis and Research on Integrated Circuit Design Optimization

After decades of development of integrated circuits, there has been great progress in all aspects. These advances are reflected in the optimization of manufacturing processes and circuits. When designing a circuit, considering the production cost and the performance of the circuit, the optimal design of the circuit is always a very important link. In this paper, two kinds of optimization ideas are introduced. One is from the point of view of the physical design of the circuit, two methods are introduced, which are adjusting the input power and reducing the circuit device. The other is to optimize the circuit from the point of view of algorithm. Genetic algorithm and simulated annealing algorithm are introduced. After optimizing the circuit, the circuit energy consumption is reduced, the circuit delay is reduced, the circuit runs faster, and the overall performance is also improved. In the future, with the development of related technologies, the optimization of integrated circuits will be faster.

Advances in Engineered Nano-Biosensors for Bacteria Diagnosis and Multidrug Resistance Inhibition.

Bacterial infections continue to pose a significant global health challenge, with the emergence of multidrug-resistant (MDR) bacteria and biofilms further complicating treatment options. The rise of pan-resistant bacteria, coupled with the slow development of new antibiotics, highlights the urgent need for new therapeutic strategies. Nanotechnology-based biosensors offer fast, specific, sensitive, and selective methods for detecting and treating bacteria; hence, it is a promising approach for the diagnosis and treatment of MDR bacteria. Through mechanisms, such as destructive bacterial cell membranes, suppression of efflux pumps, and generation of reactive oxygen species, nanotechnology effectively combats bacterial resistance and biofilms. Nano-biosensors and related technology have demonstrated their importance in bacteria diagnosis and treatment, providing innovative ideas for MDR inhibition. This review focuses on multiple nanotechnology approaches in targeting MDR bacteria and eliminating antimicrobial biofilms, highlighting nano-biosensors via photodynamics-based biosensors, eletrochemistry biosensors, acoustic-dynamics sensors, and so on. Furthermore, the major challenges, opportunities of multi-physical-field biometrics-based biosensors, and relevant nanotechnology in MDR bacterial theranostics are also discussed. Overall, this review provides insights and scientific references to harness the comprehensive and diverse capabilities of nano-biosensors for precise bacteria theranostics and MDR inhibition.

Futuristic Silicon Photonic Biosensor with Nanomaterial Enhancement for PSA Detection

This article describes a novel electrochemical on-chip biosensor that utilises the anti-PSA antibody (Ab) and silver nanoparticles (AgNPs) to enhance the sensing and detection capability of the prostate-specific antigen (PSA) in the blood. The AgNPs are prepared, characterised, and applied to a silicon photonic on-chip biosensing receptor platform designed to enhance the accurate detection of PSA. The AgNPs were synthesised by a chemical reduction method using silver nitrate (AgNO3) as the precursor. Transmission electron microscopy (TEM), selected area electron diffraction (SAED), energy dispersion X-ray spectroscopy (EDS), small angle X-ray scattering (SAXS), X-ray diffraction (XRD), and light microscopy were among the methods used in the characterisation and analysis of the AgNPs. Each stage of the immunosensor fabrication was characterised using cyclic voltammetry. The proposed immunosensor was applied in the detection of PSA, a prostate cancer biomarker, with a high sensitivity and a limit of detection of 0.17 ng/mL over a linear concentration range of 2.5 to 11.0 ng/mL. The immunosensor displayed good stability and was selective in the presence of interfering species like immunoglobulin (Ig) in human serum, ascorbic acid (AA), and diclofenac (Dic). The detectivity and sensitivity are significantly higher than previous reports on similar or related technologies.

Employee feedback: how to provide feedback and recognition regularly

Purpose This paper explores the transformative impact of regular employee feedback and recognition in the workplace. This study aims to provide a comprehensive understanding of the role of feedback in fostering a culture of accountability and appreciation, thereby improving organizational effectiveness and employee satisfaction. Design/methodology/approach The paper adopts a qualitative approach, drawing on extensive professional experience and contemporary Human Relations practices. It synthesizes insights from various employee engagement strategies, feedback mechanisms and recognition programs implemented in diverse organizational settings. The methodology includes an analysis of best practices in feedback delivery, the role of technology in Human Relations and the challenges of implementing effective feedback systems. The approach is grounded in practical Human Relations expertise, offering a real-world perspective on managing employee engagement. Findings This paper finds that clear communication of expectations, setting achievable goals, providing resources and acknowledging success are key to effective feedback. The study also reveals the importance of personalized, empathetic feedback approaches and the strategic use of technology in HR processes. Research limitations/implications The insights presented are based on the author’s extensive experience and existing literature, which may not encompass all possible scenarios in diverse organizational contexts. Future research could benefit from empirical studies to validate these findings across different industries and company sizes. Practical implications This paper offers actionable strategies for HR professionals and managers to enhance employee engagement through effective feedback and recognition. The paper also discusses the integration of technology in feedback processes and the importance of ongoing training for effective feedback delivery. These insights are valuable for organizations aiming to foster a positive work environment and high employee morale. Social implications The study highlights the social dimension of workplace feedback, emphasizing its role in building a supportive and inclusive work culture. It underscores the importance of recognizing diverse feedback preferences and the impact of empathetic, personalized communication on employee well-being and job satisfaction. The paper advocates for feedback practices that contribute to a more engaged, motivated and socially connected workforce. Originality/value This paper offers a unique blend of practical HR expertise and strategic insights into employee feedback and recognition. It fills a gap in the literature by providing a comprehensive view of the impact of feedback on employee engagement and organizational performance. The paper’s value lies in its practical applicability and its contribution to the understanding of effective feedback strategies in modern workplaces.

Identifying up-to-date urban land-use patterns with visual and semantic features based on multisource geospatial data

The cognition of up-to-date urban land-use patterns has important guiding significance for grasping the current status of urban development, promoting sustainable urban planning and social development. Despite the emergence of various methods for identifying land-use patterns with the advent of geographic big data and related technologies, several issues, such as the suitability of the data used for exploring land-use patterns and the provision of sufficient information to characterize the land functions, are worthy of further discussion. This paper establishes a framework that fuses visual and semantic features to identify the up-to-date urban land-use patterns based on multisource geospatial data. The proposed framework mainly consists of two components: the first component is a fine-grained land-use type identification model with deep learning networks that employ an Inception-based feature extractor to obtain visual features in remote sensing (RS) images and a BERT-based feature extractor to extract semantic features from human activity-related data; the second component is the evaluation of the land-use patterns at the parcel level from diverse perspectives. The experiments on real-world data demonstrate the effectiveness and superiority of the proposed method over alternative methods for identifying the up-to-date urban land-use patterns.

THE IMPACT OF AI ON MARKETING: OPPORTUNITY OR THREAT?

Today we are talking about a new generation of AI, about generative AI, which came into mass use at the end of last year. Artificial intelligence is useful if we know how to use it and it has certainly been fundamentally changing the marketing universe for some time. In marketing, AI tools help in customer segmentation, in finding new customers who show propensity to buy, in product recommendations, in sales, in customer support, in the production of advertising messages, in the generation of responses on social networks, in purchasing behavior research, in algorithms for predicting buyer behavior, etc. ChatGPT and related technologies are the reality of individuals and organizations. New technologies develop very quickly and exponentially, where we do not know where and how the development will go, but we know that changes will happen. It is best to start preparing for the changes today. AI is not so much a technological change as it is a business change in organizations that requires change management, strategy and vision.

Shanghai Tourism Carbon Footprint Measurement Based on Final Consumption and Suggestions for Improvement of Urban Tourism Facilities

As a major tourist city in China, Shanghai's tourism industry generates a great deal of carbon emissions. However, China is now actively practicing measures to reduce carbon emissions in order to protect the environment. Therefore, it is particularly important to measure Shanghai tourism carbon footprint. The results of this study can help characterize the carbon emission of Shanghai's tourist industry, so that the government can better improve Shanghai's tourism - based on its characteristics and reduce the carbon emissions in a more effective manner, which can better respond to the national and global low-carbon trend. This research utilizes the "from bottom to up" approach, collects data from Shanghai's tourism final consumption, measures the sub-industrys carbon footprint using the carbon emission coefficients, and then performs a superposition calculation to determine the characteristics of Shanghai's overall tourism and sub-industry carbon footprint, and the composition of carbon footprint in transportation. It shows following problems: the national environmental protection awareness has not yet been formed, and the tourism's related technologies and service facilities have not been able to guide tourists to reduce carbon emissions. In view of the characteristics and problems, this paper puts forward three suggestions, including the innovation of tourism-related technologies, the transformation of tourism service facilities and the enhancement of national low-carbon awareness.

The impacts of connected autonomous vehicles on mixed traffic flow: A comprehensive review

The rapid improvements in communication and self-driving technology in recent years have made connected autonomous cars an essential component of urban road transit. Connected autonomous vehicles excel in eliminating uncertainties arising from human driving behaviors. Consequently, they alleviate the issue of 'phantom congestion', a phenomenon that significantly impacts traffic efficiency, safety and sustainability while simultaneously enhancing overall traffic flow stability and safety. Moreover, the increasing adoption of connected autonomous vehicles has led to improved driving efficiency, resulting in reduced energy emissions and decreased environmental pollution. This paper endeavors to conduct an extensive review concerning the effects of CAVs on mixed traffic flows, with a primary emphasis on their impact on traffic efficiency and congestion. Additionally, secondary aspects such as stability, safety, and environmental repercussions will be addressed. The article begins with a concise historical account of connected autonomous vehicles and their related technologies. Subsequently, an investigation was conducted into their impact on the mixed traffic environment, along with corresponding policy recommendations. Finally, potential avenues for future research were identified.

Examination of the Use of VR Combined with Internet Technology to Enhance the Experience of Sound Art in the Treatment of Anxiety Disorders

《Due to the rapid development of interactive technology, sound interaction, as one of the core forms of interactive art, plays an important role in sound art. Its interactivity is one of the main factors affecting audiences’ perception. As far as the interaction of sound art is concerned, it can neither be extended as sound art nor give full play to its function, which is the key difficulty in the current development. Therefore, only by making full use of the existing advantages of virtual reality and the innovation of digital processing technology that the value of art therapy can be better reflected. However, in sound art therapy, the most critical thing is to establish the correct understanding of it and followed by the selection of the most appropriate treatment method to achieve the best outcomes. On this basis, this study reviews the progress and trend of virtual reality and related technologies. The results show that virtual reality can be used as an effective means to assist sound art therapy. Also, this paper explores how to use existing Internet technology to enhance the experience of virtual reality combined with sound art to improve the feasibility and effectiveness of treating anxiety disorders. After a systematic discussion through MFSC extraction algorithm, the results indicated that the extraction rate of MFSC changed several times and the index decreased significantly before and after the LF/HF experiment, which proved that this approach is more effective than the traditional one. In addition, VR can combine existing Internet technologies, such as high-speed Internet, cloud computing, Internet of Things technology, artificial intelligence, real-time performance, etc. Through these combined methods, the practice of the use of sound art in treating anxiety disorders will be enhanced by the interaction of virtual reality and high-speed Internet technology, which will deepen patients’ experience and improve the treatment effect.《

Analysis of Financial Data Risk and Network Information Security by Blockchain Technology and Edge Computing

To solve the problem of computer network security, this study creatively establishes a new information security (IS) strategy recommendation system and a cooperative intrusion detection system (CIDS) based on blockchain (BC) and edge computing (EC) technologies. The innovation lies in the proposal of the real-time CIDS method. First, the related technologies and theories of the Bayesian network, deep learning (DL), and neural network (NN) are analyzed. Second, a real-time IS strategy recommendation system is constructed using NNs and expert systems, and CIDS is built on BC and DL networks. Finally, experiments compare recurrent NN and long-short term memory (LSTM). The research results reveal that the accuracy of LSTM can reach about 93%. The comparison between the single intrusion detection system (SIDS) and CIDS denotes that CIDS is better than SIDS in detection accuracy, and the specific performance is 97.54% > 91%. The proposed model based on business continuity management can help enterprises better protect financial data and establish a complete protection system of network information security (NIS). In this study, a CIDS with good performance is obtained, which lays a foundation for the further development of the NIS.

Expanding CAR-T cell immunotherapy horizons through microfluidics.

Chimeric antigen receptor (CAR)-T cell therapies have revolutionized cancer treatment, particularly in hematological malignancies. However, their application to solid tumors is limited, and they face challenges in safety, scalability, and cost. To enhance current CAR-T cell therapies, the integration of microfluidic technologies, harnessing their inherent advantages, such as reduced sample consumption, simplicity in operation, cost-effectiveness, automation, and high scalability, has emerged as a powerful solution. This review provides a comprehensive overview of the step-by-step manufacturing process of CAR-T cells, identifies existing difficulties at each production stage, and discusses the successful implementation of microfluidics and related technologies in addressing these challenges. Furthermore, this review investigates the potential of microfluidics-based methodologies in advancing cell-based therapy across various applications, including solid tumors, next-generation CAR constructs, T-cell receptors, and the development of allogeneic "off-the-shelf" CAR products.

Ethical dilemmas in digital diplomacy: Navigating the challenges of technology in international relations

Ethical dilemmas in digital diplomacy: Navigating the challenges of technology in international relations

IMPROVING OF LABOR LAW IN THE CONTEXTOF THE DEVELOPING OF ARTIFICIAL INTELLIGENCETECHNOLOGIES

The relevance of the research is due to the rapid development of artificial intelligence technologies and their active introduction into the economic activities of a modern employer. This trend generates quite a few theoretical and practical issues in the field of labor law, especially taking into account the desire of the legislator to stimulate the widespread introduction of artificial intelligence technologies and adopt appropriate regulatory regulation in the foreseeable future. In the article, the author analyzes the practice of using artificial intelligence technologies in labor relations and comes to the conclusion that there is a need to improve domestic labor law. Based on a comprehensive analysis of the mechanisms of legal regulation of the digital economy, the author suggests possible approaches to improving labor law in the context of the development of artificial intelligence technologies. A general approach to improving labor law can be provided through the development and approval of strategic planning documents in the field of labor. The use of “smart regulation” methods, including legal experiments and public consultations, will allow assessing the effectiveness of various options for the proposed regulatory framework in advance. Finally, it seems reasonable to take into account the accumulated experience of applying “soft law”, in particular, the ideas contained in the Code of Ethics in the field of Artificial Intelligence.

General definition of hydrogen energy and related electrochemical technologies

Electrochemical energy conversion, based on the transformation between electrical energy and chemical energy, is crucial for the storage and utilization of renewable electrical energy, as well as the eco-friendly production of valuable fuels and chemicals. Here we put forward a general definition of hydrogen energy that covers the energy storage/release in any hydrogen-involved chemical bonds, such as H–H, C–H, and N–H bonds. Given that H2 gas, hydrocarbons, and hydronitrogens are not only high-energy-density fuels but also important industrial feedstock s, the successful implementation of efficient energy storage/release in the H–H (hydrogen cycle), C–H (carbon cycle), and N–H (nitrogen cycle) bonds are of great significance in establishing sustainable energy systems and reducing dependence on fossil fuels, which contributes to address global energy crisis and environmental problems. We provide a concise overview of the current development status of some key low-temperature (< 100 °C) electrochemical technologies relevant to general hydrogen energy, including fuel cells, water electrolysis, CO2 electrolysis, and N2 electrolysis. This discussion aims to elucidate the major challenges and future trends in this field.

Motion Comfort Optimization for Autonomous Vehicles: Concepts, Methods, and Techniques

This article outlines the architecture of autonomous driving and related complementary frameworks from the perspective of human comfort. The technical elements for measuring Autonomous Vehicle (AV) user comfort and psychoanalysis are listed here. At the same time, this article introduces the technology related to the structure of automatic driving and the reaction time of automatic driving. We also discuss the technical details related to the automatic driving comfort system, the response time of the AV driver, the comfort level of the AV, motion sickness, and related optimization technologies. The function of the sensor is affected by various factors. Since the sensor of automatic driving mainly senses the environment around a vehicle, including “the weather" which introduces the challenges and limitations of second-hand sensors in autonomous vehicles under different weather conditions. The comfort and safety of autonomous driving are also factors that affect the development of autonomous driving technologies. This article further analyzes the impact of autonomous driving on the user’s physical and psychological states and how the comfort factors of autonomous vehicles affect the automotive market. Also, part of our focus is on the benefits and shortcomings of autonomous driving. The goal is to present an exhaustive overview of the most relevant technical matters to help researchers and application developers comprehend the different comfort factors and systems of autonomous driving. Finally, we provide detailed automated driving comfort use cases to illustrate the comfort-related issues of autonomous driving. Then, we provide implications and insights for the future of autonomous driving.

Traveling wave solution of (3+1)-dimensional negative-order KdV-Calogero-Bogoyavlenskii-Schiff equation

&lt;abstract&gt;&lt;p&gt;We explored the (3+1)-dimensional negative-order Korteweg-de Vries-alogero-Bogoyavlenskii-Schiff (KdV-CBS) equation, which develops the classical Korteweg-de Vries (KdV) equation and extends the contents of nonlinear partial differential equations. A traveling wave transformation is employed to transform the partial differential equation into a system of ordinary differential equations linked with a cubic polynomial. Utilizing the complete discriminant system for polynomial method, the roots of the cubic polynomial were classified. Through this approach, a series of exact solutions for the KdV-CBS equation were derived, encompassing rational function solutions, Jacobi elliptic function solutions, hyperbolic function solutions, and trigonometric function solutions. These solutions not only simplified and expedited the process of solving the equation but also provide concrete and insightful expressions for phenomena such as optical solitons. Presenting these obtained solutions through 3D, 2D, and contour plots offers researchers a deeper understanding of the properties of the model and allows them to better grasp the physical characteristics associated with the studied model. This research not only provides a new perspective for the in-depth exploration of theoretical aspects but also offers valuable guidance for the practical application and advancement of related technologies.&lt;/p&gt;&lt;/abstract&gt;

Pathways of Media Contact to Health Literacy in Middle-Aged and Older People: The Chain Mediation Effect of Perceived Social Support and Self-Efficacy.

To understand the status of media exposure, social support, self-efficacy, and health literacy among middle-aged and older adults in China, and explore the impact path of media exposure on the health literacy of this population, providing a reference for promoting their physical and mental health. From July to November 2022, a multi-stage random sampling method was employed to survey 16,938 Chinese middle-aged and older adults aged 46 and above. Structural equation modeling and statistical analysis were conducted using LISREL 8.8 and Mplus 8.3 software. The average score for media exposure among Chinese middle-aged and older adults was (18.55±5.36), perceived social support was (60.68±12.51), self-efficacy was (28.76±5.40), and health literacy was (35.49±6.05). Statistical results revealed that media exposure has a positive impact on the health literacy of middle-aged and older adults, with a direct effect of 0.091 (p < 0.001). Mediation analysis showed that media exposure can affect the health literacy of this population through the independent mediating effects of perceived social support (β = 0.013, p < 0.001) and self-efficacy (β = 0.029, p < 0.001), as well as through a chain mediation effect involving perceived social support and self-efficacy (β = 0.015, p < 0.001). As a pathway for health information dissemination, media exposure plays a crucial role in the intervention of health literacy among middle-aged and older adults. Perceived social support and self-efficacy not only have independent mediating effects but also significant chain mediating effects in the relationship between media exposure and health literacy among this population. Therefore, improving the health literacy of middle-aged and older people can be popularized through media and improved in a multi-path, all-round, and precise way with the help of related technologies and social forces from which media literacy can be improved.

Visualization research of modern ceramic production art based on 3D modeling technology

Abstract This paper is based on the research of visual shell related technology of 3D modeling method to extract the corresponding points of the graphical shell, through matching, filtering and denoising operations, to obtain the accurate 3D visualization model and provide new creative ideas and paths for contemporary ceramic art. In the actual ceramic membrane visualization feature extraction, six feature quantities of ceramic membrane, namely, area, aspect ratio, area perimeter, circularity, diagonal length, and angular second-order moments, can be obtained. The application of the visualization technique proposed in this paper to teaching ceramic production art was assessed by the performance of the knowledge answer questions. Regarding the average score, the experimental group (75.5) performed significantly better than the control group (63.6). Significant differences were found between the experimental and control groups in mental rotation (P=0.03&lt;0.05), spatial visualization (P=0.006&lt;0.05), and spatial reasoning skills (F=6.98, P=0.014&lt;0.05). However, the two groups had no significant difference in spatial orientation (P=0.13&gt;0.05). This suggests that the immersive learning environment of visualization technology can significantly enhance learners’ spatial reasoning skills, mental rotation, and spatial orientation.

Graphene Used for Energy Conversion and Storage by Electrochemistry: A Brief Global Overview

Background: Graphene and its derivatives have been widely used in modern electrochemical- related technologies due to their versatile structure, tunable conductivity, and large specific surface area. However, there is a need to provide the latest global literature overview in this field. Methods: In this study, we reported a literature overview of current developments in the applications of graphene in energy conversion and storage by electrochemistry. In this overview, 1285 pieces of literature were retrieved and analyzed based on the web of science core database using bibliometric tools. Results: The major contributing countries are China and the United States. The most widespread fields are the development of novel nanomaterials and catalysts and approaches to improve the electrocatalytic performance of batteries and supercapacitors. The hotspots of current research include sodium-ion batteries, lithium-sulfur batteries, sulfur-doped electrodes, and the study of high-efficiency electrocatalysts for oxygen and evolution reactions. Conclusion: With the continuous development in this field, scientists are committed to continuously improving the performance of energy equipment. The applications of graphene-based materials for electrochemical energy conversion and storage are briefly summarized. The challenges and prospects for future research in this field are also discussed.

‘기계번역’ 관련 국내 번역학 연구동향 분석

This study focuses on the role and importance of machine translation in the digital transformation(DX) environment led by the artificial intelligence(AI) and examines the perspectives of translation researchers, focusing on the use of related terminology. The perspectives on ‘machine translation’(MT) from the research dataset(2014-2023) is categorized into seven types: user and object, detailed function, domain, translation quality, performance method, and purpose of use. The discussions in translation studies related to the perspective and status of MT terminology use can be comprehensively summarized as follows: 1) The status of MT and human translators; 2) Technological changes and innovative technologies in MT; 3) Coexistence of human and MT; 4) Hybridity and diversity in the use of terminology related to MT. The mixed use of different MT-related terminologies prevailing in translation academia reflects the rapid pace of changes in related technologies. Thus, it is necessary to keep options open to diversity rather than unity and consistency of terminology. In conclusion, this study provides a comprehensive overview and recognition of the topography of research, areas of interest, and the degree of focus of discussion on MT-related research in Translation Studies of Korea.