Technological Revolution Research Articles

Does digital inclusive finance promote carbon emission reduction of enterprises.

Can the information technology revolution lead to carbon emission reduction for firms? This study extends the limited evidence in the literature and investigate the role and mechanism of digital inclusive finance on enterprises' carbon emissions using panel data of 247 prefectural-level cities and 6019 industrial enterprises in China. Our findings indicate that digital inclusive finance can promote enterprise carbon emission reduction, and this effect remains significant after the instrumental variable estimation test. The effect has regional heterogeneity and the development of digital inclusive finance in the area east of Hu Huanyong line has a significant impact on reducing enterprise carbon emission. The role of digital inclusive finance is heterogeneous in enterprise ownership, with a remarkable effect in non-state-owned enterprises. Sub-dimension analysis indicates that the breadth of coverage, depth of use, and degree of digitalization of digital inclusive finance have differential effects on reducing enterprise carbon emissions. The stepwise regression method shows that the impact of digital inclusive finance on enterprise carbon emissions can be passed through effect of technological progress, environmental protection investment and financing constrain. This study has significant reference value for evaluating the impact of financial inclusion and policy implications in formulating differentiated strategies for achieving carbon emission reduction efficiency in enterprises.

Multichannel direct communication based on a programmable topological plasmonic metasurface

With the gradual improvement of the future wireless communication technology, the demand for high information capacity and reliable links in communication systems is also ever-increasing. Programmable topological plasmonic metasurfaces, consisting of artificially engineered structures with robust propagation pathways control, have emerged as a revolutionary technology for stable microwave and on-chip communication systems. Programmable topological plasmonic metasurfaces offer unprecedented flexibility and adaptability in managing multiple communication channels as the propagation paths can be easily reconfigured to meet specific communication requirements. Here, we have experimentally demonstrated the ability to dynamically manipulate electromagnetic waves along eight distinct topological pathways for a multichannel direct communication system. The simulation results of topological plasmonic metasurfaces with different coding schemes have showcased their excellent performance in multichannel wavefront control. Experimental results have consistently aligned with the simulation findings, validating the effectiveness of multichannel topological routes. Furthermore, an eight-channel direct communication system based on a programmable topological plasmonic metasurface is designed and implemented to transmit different information. The proposed multichannel communication system based on a programmable topological plasmonic metasurface opens up new possibilities for high-capacity, efficient, and adaptive communication systems, which hold great potential in transformative applications in areas such as 6G, Internet of Things, and beyond.

The Implications of Artificial Intelligence in Pedodontics: A Scoping Review of Evidence-Based Literature.

Artificial intelligence (AI) has emerged as a revolutionary technology with several applications across different dental fields, including pedodontics. This systematic review has the objective to catalog and explore the various uses of artificial intelligence in pediatric dentistry. A thorough exploration of scientific databases was carried out to identify studies addressing the usage of AI in pediatric dentistry until December 2023 in the Embase, Scopus, PubMed, and Web of Science databases by two researchers, S.L.R. and A.L.G. From a pool of 1301 articles, only 64 met the predefined criteria and were considered for inclusion in this review. From the data retrieved, it was possible to provide a narrative discussion of the potential implications of AI in the specialized area of pediatric dentistry. The use of AI algorithms and machine learning techniques has shown promising results in several applications of daily dental pediatric practice, including the following: (1) assisting the diagnostic and recognizing processes of early signs of dental pathologies, (2) enhancing orthodontic diagnosis by automating cephalometric tracing and estimating growth and development, (3) assisting and educating children to develop appropriate behavior for dental hygiene. AI holds significant potential in transforming clinical practice, improving patient outcomes, and elevating the standards of care in pediatric patients. Future directions may involve developing cloud-based platforms for data integration and sharing, leveraging large datasets for improved predictive results, and expanding AI applications for the pediatric population.

Nanoemulsion: Composition, Preparation and its Application in the Food Industry

Nanotechnology deals with the application of atoms, molecules, or macromolecules with sizes ranging from 1 to 100 nm to create and utilize materials with distinct and novel characteristics. Nanotechnology has gained popularity over the past few decades and is now widely regarded as a revolutionary technology in the food industry. Various nanoencapsulation techniques have been spawned by the boom in interest in nanotechnology and its application in food products. One of the most exciting encapsulating and delivering methods in the food sector is nanoemulsion. A nanoemulsion is a mixture of two immiscible liquids and a surfactant that takes the form of tiny droplets less than 200 nm in size. Delivery methods based on nanoemulsions increase the bioavailability of the bioactive substances that are encapsulated and improve food stability. Since nanoemulsions are thermodynamically unstable, they need a certain amount of energy to create them. The preparation technique chosen determines the creation and permanence of nanoemulsions. This review provides an overview of nanoemulsion terminology and formulation; and also addresses various approaches for producing nanoemulsions, including both high- and low-energy techniques. In addition, the applications of nanoemulsions in the food industry.

Political communication in the age of artificial intelligence: an overview of deepfakes and their implications

The current technological landscape has been profoundly shaped by rapid and significant advances in artificial intelligence (AI), sparking extraordinary interest in academia and beyond. Considered an unprecedented revolutionary technology, it has captured the attention of researchers, scholars, and professionals from various disciplines as it offers transformative prospects in a wide range of fields. This technological progress has sparked a broad debate on its social, ethical, and economic impacts, raising important questions that require in-depth and multidisciplinary investigations. AI thus emerges as an ever-evolving discipline with significant implications for the future of human progress. Besides being seen as an opportunity to pursue common societal goals, many observers have recognized the potential risks associated with such developments. Its integration into the political context also presents a promising opportunity to enhance the efficiency of political decisions however, its adoption raises significant challenges that require careful evaluation. The aim of this research is to explore in detail the relationship between AI and political communication, focusing on the analysis of AI's usage in this context while highlighting the phenomenon of deepfakes, which jeopardize democratic stability and security in many cases. The importance of this research contribution lies in the context where AI is assuming an increasingly prominent role in daily dynamics, making it essential to fully understand the implications and potential consequences of AI application in the political field. Furthermore, it is crucial to assess whether such initiatives can genuinely be considered democratic or if they could represent a dangerous trend towards the use of manipulative algorithms.

Application of Advanced Technology on Transport Ships as a Technological Revolution in the Maritime Industry

Application of Advanced Technology on Transport Ships as a Technological Revolution in the Maritime Industry

Metagenomics: Advances in Environmental Microbiology, Human Health, and Agriculture

Metagenomics, as a revolutionary technology, plays an important role in the study of environmental microbial ecosystems. Metagenomics has revolutionized our understanding of microbial communities by enabling the comprehensive analysis of genetic material directly from environmental samples. This paper reviews recent advances in metagenomics and its applications in environmental microbiology, human health, and agriculture. We highlight key methodologies, significant findings, and the potential of metagenomics to drive innovations across various scientific and practical domains.

COMPLEX ANALYSIS OF CRYPTOCURRENCIES AND THEIR IMPLICATIONS IN THE CONTEXT OF MONEY LAUNDERING AND TERRORISM FINANCING

This study investigates the potential role of Bitcoin in terrorism financing by analyzing the decentralization and anonymity features of cryptocurrencies that facilitate illegal transactions. In the context of delayed regulatory capacity regarding innovations in financial technology, the study explores new opportunities for terrorism financing. International reports, such as that of the financial action task force on money laundering, highlight the growing risks of terrorism financing associated with virtual currencies like Bitcoin. While terrorist financing based on emerging technologies enables terrorist organizations to swiftly transfer funds globally, this phenomenon simultaneously increases the difficulties in combating terrorism financing at the national level. In light of this technological revolution and the expansion of terrorism, the study focuses on the interaction between Bitcoin and terrorism, exploring whether terrorist attacks significantly contribute to Bitcoin price fluctuations and to what extent the cryptocurrency may evolve into a currency used for terrorism financing.

Study on the Evolution of the World Economy and International Cooperation in the Context of Carbon Neutrality

With the passage of time and the promotion of global eco-environmental protection concepts, the issue of the climate crisis has attracted the attention of all countries in the world and has become a hot topic characterized by ties. In recent years, major economies have announced their participation in carbon neutral activities one after another, actively implemented the carbon neutral targets, promoted international exchanges based on the concept of green and low carbon, deepened the degree of greening cooperation among countries, and met the needs of carbon neutral policy implementation from a strategic perspective. In the process of popularizing the concept of carbon neutrality, global economies have been able to participate in ecological and environmental protection activities together. Nowadays, there are certain changes in the global development pattern, and a scientific and technological revolution oriented to the goal of carbon neutrality has quietly arrived, and the world energy governance order has also changed. This paper analyzes the trend of the world economy in the context of carbon neutrality and the challenges of cooperation brought about by it, and puts forward the idea of participation in international cooperation from China's standpoint.

Research on the Path of Digital Enabling New Quality Productivity in Yangtze River Delta

As one of the most economically developed regions in China, the Yangtze River Delta (YRD) region has always been in the leading position in the country in terms of economic development. However, with the changes in the global economic situation and the promotion of scientific and technological innovation, the Yangtze River Delta region is also facing new development challenges and opportunities. Digital empowerment, as an important driving force of the new round of technological revolution, is of great significance to the development of new quality productivity in the Yangtze River Delta region. As new quality productivity has become the buzzword of China's economic development, how can the Yangtze River Delta recognize the timing and take the pulse of development? Therefore, this study aims to deeply explore the path of digitally-enabled new quality productivity in the Yangtze River Delta region, and provide theoretical and practical support for the sustainable development of the regional economy. By analyzing the impact of digital empowerment on new-quality productivity in the Yangtze River Delta region, this study intends to explore the mechanism of the role of digital empowerment in enhancing new-quality productivity and propose corresponding paths and strategies. Specific research questions include: what is the current status of digital empowerment in the Yangtze River Delta region? What is the impact mechanism of digital empowerment on new quality productivity? How should the path of digital empowerment of new quality productivity in the Yangtze River Delta region be constructed?

The ICT–Economic Growth Nexus: Revisiting the Impact of the Internet on GDP

Over the past decades, the intensive development of information and communication technologies (ICT) has prompted numerous studies assessing the relationship between ICT and economic growth. Initial doubts about the importance of the Internet for economic growth have recently been replaced by conclusions supporting the positive significance of this technological revolution. However, despite the abundant research conducted in recent years, the obtained outcomes do not allow for a consensus, particularly regarding the impact of specific types of ICT. This paper investigates the connection between Internet usage and economic growth. The estimation is based on a broad group of economies (88 countries) from 2006 to 2020 using data from the International Telecommunication Union database. The results suggest a statistically significant relationship between Internet usage and GDP growth.

Legal implications of artificial intelligence in health care

The last few years have seen a boom in the popularity of artificial intelligence (AI) around the world, and the health care sector has not been immune from what has been perceived by some as a revolutionary technology. Although AI has been around for many years, including in the field of health care, the recent introduction of consumer-facing generative AI tools has put a spotlight on the technology that has drawn attention from governments, corporations, consumers and more. Health care systems, physician groups, health insurance companies, and others in the space have shown an eagerness to explore AI's potential to improve various aspects of health care, but new legal risks and challenges are unfolding every day. This contribution looks at the latest health care-related measures in the United States and international legal and regulatory landscapes, as well as data privacy implications and discrimination concerns coming out of AI-enabled solutions. It also discusses concerns that health care systems and physicians alike are monitoring, including the potential for medical errors resulting from AI, liability considerations, and malpractice insurance trends.

Ligand substitution as a strategy to tailor cationic conductivity in all-solid-state batteries

An increased electrification of society calls for a revolution of battery technologies to further improve energy densities, safety and reduce dependencies on critical raw materials. Here we present a new type of fast magnesium electrolytes for all solid-state batteries created as solid solutions of two other fast Mg2+ ionic conductors, Mg(BH4)2 ∙ NH3 and Mg(BH4)2 ∙ CH3NH2. However, the different ligands introduce stacking faults in the structures of the solid solutions, which are eliminated upon heating to T > 40 °C. The stacking faults appear to influence ionic conductivity, as the samples are less conductive after heating. Interestingly, the ionic conductivity does not correlate directly with the relative ligand content, as the highest conductivity is observed for the 1:1 molar composition (σ(Mg2+) = 7.3 ∙ 10−6 S cm−1 at 40 °C), which also has the lowest melting point of 60 °C. Thus, this work demonstrates a new approach to increase cationic conductivity using mixed ligand systems to alter conduction pathways and introduce microstructural strain.

Digital Transformation - The Game Changer in Indian Insurance Sector

Information technology has graduated from playing a supportive role to becoming a strategic game changer disrupting established paradigms, notions and players. It is time to take stock of the current wave of technological revolution that is powered by newer technologies such as artificial intelligence, big data, et al. This article takes a look at the various aspects of InsurTech, the technologies driving transformation and their specific applications, the risks and concerns, regulatory involvement, and the role of professionals in this hi-tech environment.

Reshaping the Industrial Policy Framework of Turkiye: Integrating Exports at the Core of AI-Driven Development

This study explores the evolving landscape of industrial policy amid deglobalization, protectionism, and the technological revolution driven by artificial intelligence (AI). The shift in industrial policies across the US and EU, driven by geopolitical tensions, climate change, and economic rivalry, has resulted in increased protectionist measures. The US, once an advocate of free-market principles, now implements policies like the CHIPS Act to enhance domestic manufacturing and reduce reliance on China. For developing countries like Turkiye, integrating exports into industrial policy is crucial. Despite Turkiye's significant export growth, challenges such as low R&D spending and a small share of high-tech exports persist. The article emphasizes the need for a dedicated institution, the Industrial Policy Institutes of Turkey (TEPE), to focus on innovation, competitiveness, and sustainable development. TEPE would encompass various sub-institutions dedicated to high technology, energy, defense, and digitalization. AI can play a strategic role in analyzing sectors, optimizing supply chains, and enhancing export competitiveness. By leveraging AI, Turkiye can transform its industrial policies and position itself more robustly in the global market, ensuring economic resilience and growth.

EfficientNet-deep quantum neural network-based economic denial of sustainability attack detection to enhance network security in cloud

ABSTRACT Cloud computing (CC) is a future revolution in the Information technology (IT) and Communication field. Security and internet connectivity are the common major factors to slow down the proliferation of CC. Recently, a new kind of denial of service (DDoS) attacks, known as Economic Denial of Sustainability (EDoS) attack, has been emerging. Though EDoS attacks are smaller at a moment, it can be expected to develop in nearer prospective in tandem with progression in the cloud usage. Here, EfficientNet-B3-Attn-2 fused Deep Quantum Neural Network (EfficientNet-DQNN) is presented for EDoS detection. Initially, cloud is simulated and thereafter, considered input log file is fed to perform data pre-processing. Z-Score Normalization ;(ZSN) is employed to carry out pre-processing of data. Afterwards, feature fusion (FF) is accomplished based on Deep Neural Network (DNN) with Kulczynski similarity. Then, data augmentation (DA) is executed by oversampling based upon Synthetic Minority Over-sampling Technique (SMOTE). At last, attack detection is conducted utilizing EfficientNet-DQNN. Furthermore, EfficientNet-DQNN is formed by incorporation of EfficientNet-B3-Attn-2 with DQNN. In addition, EfficientNet-DQNN attained 89.8% of F1-score, 90.4% of accuracy, 91.1% of precision and 91.2% of recall using BOT-IOT dataset at K-Fold is 9.

The application of deep learning-based technique detection model in table tennis teaching and learning

With the development of computer technology, the teaching methods of table tennis have ushered in a new technological revolution. To solve the problem of traditional teaching methods overly focusing on athlete limbs and athlete force movements, this study uses an improved deep learning algorithm technology detection model to analyze the trajectory of table tennis and provide targeted tactical training for athletes. The results showed that the success rate and accuracy score of the model were 95 % and 96 %, respectively, with a calculation time of only 21.75 ms, indicating high analytical accuracy and computational efficiency. Meanwhile, the winning rate of the training strategy under this method can reach over 65 %, effectively improving the winning rate of athletes. This proves that the proposed technology detection model has good algorithm performance and data analysis ability, and can provide data support for table tennis training and teaching work.

Comparative Analysis of Loss Functions in TD3 forAutonomous Parking

Autonomous parking is a revolutionary technology that has transformed the automotive industry with the rise of deep reinforcement learning, in particular, the Twin-Delayed Deep Deterministic Policy Gradient Algorithm (TD3). Nonetheless, the robustness of TD3 remains a significant challenge due to bias in Q-value estimates when determining how good an Action, A, taken at a particular state, S. To investigate this gap, this paper analyzes different loss functions in TD3 to better approximate the true Q-value, which is necessary for optimal decision making. Three loss functions are evaluated; Mean Squared Error (MSE), Mean Absolute Error (MAE) and Huber Loss via a simulation experiment for autonomous parking. The results showed that TD3 with Huber Loss has the highest convergence speed with the fastest Actor and Critic loss convergence. The Huber Loss function is found to be more robust and efficient than either loss function such MSE or MAE used in isolation, making it a suitable replacement for existing loss functions in the TD3 algorithm. In the future, TD3 with Huber Loss will be used as the base model to solve overestimation problem in TD3 when the estimated Q-values that represent the expected rewards of taking an action in a particular state, are higher than their true values.

Autonomous Driving Strategy for a Specialized Four-Wheel Differential-Drive Agricultural Rover

Recently, the agriconstruction machinery sector has been involved in a great technological revolution. The reasons that may explain this are strictly connected to the mitigation of climate change. At the same time, there is a necessity to ensure an adequate production level in order to meet the increasing food demand due to the current population growth trend. In this context, the development of autonomously driven agricultural vehicles is one of the areas on which tractor manufacturers and academics are focusing. The fundamental prerequisite for an autonomous driving vehicle is the development of an appropriate motion strategy. Hence, the vehicle will be able to follow predetermined routes, accomplishing its missions. The aim of this study was the development of path-planning and path-following algorithms for an agricultural four-whee differential-drive vehicle operating in vineyard/orchard environments. The algorithms were completely developed within the MATLAB software environment. After a brief description of the geometrical characteristics of the vehicle, a parametric process to build a virtual orchard environment is proposed. Then, the functional principles of the autonomous driving algorithms are shown. Finally, the algorithms are tested, varying their main tuning parameters, and an indicator to quantify the algorithms’ efficiency, named relative accuracy, is defined. The results obtained show the strong dependence between the relative accuracy and lookahead distance value assigned to the rover. Furthermore, an analysis of rover positioning errors was performed. The results in this case show a lower influence of the location error when the accuracy of the positioning device is within 2 cm.

Hybrid Organic-Si C-MOSFET Image Sensor Designed with Blue-, Green-, and Red-Sensitive Organic Photodiodes on Si C-MOSFET-Based Photo Signal Sensor Circuit.

The resolution of Si complementary metal-oxide-semiconductor field-effect transistor (C-MOSFET) image sensors (CISs) has been intensively enhanced to follow the technological revolution of smartphones, AI devices, autonomous cars, robots, and drones, approaching the physical and material limits of a resolution increase in conventional Si CISs because of the low quantum efficiency (i.e., ~40%) and aperture ratio (i.e., ~60%). As a novel solution, a hybrid organic-Si image sensor was developed by implementing B, G, and R organic photodiodes on four n-MOSFETs for photocurrent sensing. Photosensitive organic donor and acceptor materials were designed with cost-effective small molecules, i.e., the B, G, and R donor and acceptor small molecules were Coumarin6 and C_60, DMQA and MePTC, and ZnPc and TiOPc, respectively. The output voltage sensing margins (i.e., photocurrent signal difference) of the hybrid organic-Si B, G, and R image sensor pixels presented results 17, 11, and 37% higher than those of conventional Si CISs. In addition, the hybrid organic-Si B, G, and R image sensor pixels could achieve an ideal aperture ratio (i.e., ~100%) compared with a Si CIS pixel using the backside illumination process (i.e., ~60%). Moreover, they may display a lower fabrication cost than image sensors because of the simple image sensor structure (i.e., hybrid organic-Si photodiode with four n-MOSFETs).