Generation Technologies Research Articles

The potential of virtual reality meetings in international research projects for greenhouse gas emission mitigation

PurposeEuropean Union (EU) research projects generally involve international teams based in different countries. This means that researchers need to travel internationally to participate for in-person meetings, which are crucial for facilitating collaboration among research teams and provide a platform for teams to share their progress. Unfortunately, much of the international traveling in EU projects is done by air and therefore it has a significant carbon footprint. One potential solution that has gained attention in recent years is virtual reality (VR) and the metaverse. The aim of this work is to investigate to what degree VR meetings provide a viable alternative to physical meetings in the context of EU research projects and can thus contribute to climate change mitigation.Design/methodology/approachA three-stepped approach was chosen. First, the requirements for VR meetings were determined by collecting all relevant aspects of physical meetings through a questionnaire. Second, a set of VR meeting experiments were designed and executed. Third, carbon footprints for both physical traveling and VR meetings (lifecycle) were calculated.FindingsWe conclude that VR can be a powerful tool which can supplement international projects and mitigate carbon emissions associated with traveling for in-person meetings by an estimated 7–19 times.Originality/valueThis paper explores the suitability of the current generation of VR technology and quantitatively evaluates its effectiveness for greenhouse gas emissions mitigation in the context of a European research project.

A highly naturalistic facial expression generation method with embedded vein features based on diffusion model

Abstract Facial expression generation technology has achieved notable progress in computer vision and artificial intelligence. However, challenges persist regarding background consistency, expression clarity, and detailed representation. Additionally, the instability of generative adversarial networks (GANs) during training affects both image quality and diversity. While diffusion models have demonstrated potential advantages over GANs, research on controllable expression generation remains limited. To address these challenges, this paper proposes a highly natural facial expression generation method based on denoising diffusion implicit models (DDIM) with embedded vein features. This approach avoids adversarial training by employing gradual diffusion to generate specific expressions, thereby enhancing both the diversity and authenticity of the images. Vein features are introduced and embedded within the generated expression images to protect the intellectual property of algorithm-generated digital resources. Firstly, image and expression text guide words are combined as conditional inputs to improve the authenticity and diversity of the generated images. Secondly, a classification coding network is introduced to guide expression generation, thus enhancing the accuracy and consistency of the produced expressions. Furthermore, this paper proposes a vein feature fusion method based on multi-directional local dynamic feature coding operator (MLDFO) and integrates DDIM with frequency-domain watermarking technology to achieve image intellectual property protection. Experimental results demonstrate the effectiveness of this method across several public datasets, including FFHQ, CelebA, FV-USM, and SDUMLA-HMT. Notably, in the CelebA dataset, the average expression recognition rate increased by 11.41%, with a 100.00% recognition rate for happy expressions. The generated expression images exhibit a high degree of authenticity and consistency, and the video conversion tests reveal a natural and smooth effect. These results confirm that this method not only advances facial expression generation technology but also significantly enhances the steganographic protection of images.

Social and Behavioural Change Communication Challenges, Opportunities and Lessons from Past Public Health Emergencies and Disease Outbreaks: A Scoping Review.

Background: Documentation of social behavioural change communication (SBCC) regarding challenges, opportunities and lessons drawn from past public health emergencies is worthwhile to inform priorities for future response efforts. Aim: The aim of this review is to scope the evidence on social behavioural change communication regarding challenges, opportunities and lessons drawn from Ebola, coronavirus disease 2019 (COVID-19), monkeypox and cholera outbreaks from studies published before March 2024, and suggest priorities for future response efforts. Methods: A Boolean strategy was used to search electronic databases for relevant published articles, complemented by relevant studies identified from reference lists. Results: The challenges, opportunities, lessons learnt and priorities for SBCC were consistent across study contexts, showing marked variations over time. The significance of technology, infodemic management, and behavioural data generation emerged more frequently and became increasingly important over time. Identified challenges were uptake hesitancy, limited capacity to undertake infodemic management, inadequate funding and human resources for SBCC, competing priorities, parallel or conflicting interventions due to inadequate coordination, difficulties evaluating SBCC programmes and missed opportunities for integration into routine programmes. Existing supportive structures for SBCC, strong political will and participation, as well as rapid information exchange enabled by technological advancement, represented opportunities for enhancing the effectiveness of SBCC programmes. Key lessons were that a multisectoral approach and coordination, partnership and active collaboration amongst stakeholders; building/strengthening trust, target population segmentation and localization of interventions, are important for enhancing the effectiveness of SBCC programmes. Political will, involvement and participation represent the core of social behavioural change (communication) interventions during a public health emergency. Conclusion: SBCC programming for future response to public health emergencies and disease outbreaks should consider the diverse assortment of benefits, threats/challenges and opportunities brought about by technology, infodemics and behavioural data generation to be more effective.

Water-Triboelectrification-Complemented Moisture Electric Generator.

Energy harvesting from ubiquitous natural water vapor based on moisture electric generator (MEG) technology holds great potential to power portable electronics, the Internet of Things, and wireless transmission. However, most devices still encounter challenges of low output, and a single MEG complemented with another form of energy harvesting for achieving high power has seldom been demonstrated. Herein, we report a flexible and efficient hybrid generator capable of harvesting moisture and tribo energies simultaneously, both from the source of water droplets. The moisture electric and triboelectric layers are based on a water-absorbent citric acid (CA)-mediated polyglutamic acid (PGA) hydrogel and porous electret expanded polytetrafluoroethylene (E-PTFE), respectively. Such a waterproof E-PTFE film not only enables efficient triboelectrification with water droplets' contact but also facilitates water vapor to be transferred into the hydrogel layer for moisture electricity generation. A single hybrid generator under water droplets' impact delivers a DC voltage of 0.55 V and a peak current density of 120 μA cm-2 from the MEG, together with a simultaneous AC output voltage of 300 V and a current of 400 μA from the complementary water-based triboelectric generator (TEG) side. Such a hybrid generator can work even under harsh wild environments with 5 °C cold and saltwater impacts. Significantly, an optical alarm and wireless communication system for wild, complex, and emergency scenarios is demonstrated with power from the hybrid generators. This work expands the applications of water-based electricity generation technologies and provides insight into harvesting multiple potential energies in the natural environment with high output.

2D animation comic character action generation technology based on biomechanics simulation and artificial intelligence

AI can greatly improve the process of creating 2D character animations, especially for platformer games. The objective is to enhance visual effects quality and streamline production by incorporating biomechanics and AI-driven technology into the animation process. The current state of study shows that conventional 2D animation production has several problems, such as lengthy procedures, complicated technical requirements, and the requirement for human involvement. Both efficiency and innovation are limited by these limitations. To solve this problem, we suggest generating 2D character animations using AI-driven generative methods and biomechanics simulation. Consistently high-quality outcomes can be achieved by automating aspects of animation design. Improving animation industry innovation, streamlining production workflows, and decreasing manual labor are crucial. The viability of 2D animations generated by AI has been demonstrated in preliminary studies. Artificial intelligence’s effects on animation’s expressiveness, realism, and aesthetics are covered in detail. Furthermore, it has presented challenges with training data, choosing the right model, and fine-tuning. Beyond the field of gaming, our research has wider implications. Several industries may benefit from the benefits of 2D animations enhanced with AI and biomechanics technology. These industries include advertising, entertainment, and education.

Coal Phase-Out and Carbon Tax Analysis with Long-Term Planning Models: A Case Study for the Chilean Electric Power System

Large CO2 emissions constitute a significant problem today due to their effect on climate change, and the need to design appropriate energy policies to mitigate their consequences and reduce emissions requires a detailed analysis of one of the main sources of such emissions: the electricity system. Thus, this paper presents a study on the effects of energy policies on decarbonization by comparing the detailed phase-out of coal-fired power plants across a range of cases with the implementation of a carbon tax to meet Nationally Determined Contributions (NDCs). The case study focuses on the Chilean electricity system, using a long-term generation and transmission expansion planning model (GTEP) that incorporates a wide range of generation technologies. The study examines the long-term effects of these policies, including costs, investments, and CO2 emissions, as well as their impact on consumer prices reflected in the marginal costs of the system. The transmission system modeling covers various regions of Chile and significant projections for renewable energy sources. It evaluates three economic scenarios based on generation technology costs, fuel prices, and electricity demand under four different closure schemes and fourteen different carbon tax levels. The results indicate that implementing a carbon tax can be more cost-effective for the system than the implementation of a phase-out schedule for coal plants, taking the form of reduced CO2 emission and overall system costs, with an optimal carbon tax value of 37 USD/tCO2. Additionally, the study reveals significant effects on consumer prices, showing that a carbon tax as an energy policy leads to lower prices compared to a phase-out scheme.

Long‐term Durability of Seawater Electrolysis for Hydrogen: From Catalysts to Systems

AbstractDirect electrochemical seawater splitting is a renewable, scalable, and potentially economic approach for green hydrogen production in environments where ultra‐pure water is not readily available. However, issues related to low durability caused by complex ions in seawater pose great challenges for its industrialization. In this review, a mechanistic analysis of durability issues of electrolytic seawater splitting is discussed. We critically analyze the development of seawater electrolysis and identify the durability challenges at both the anode and cathode. Particular emphasis is given to elucidating rational strategies for designing electrocatalysts/electrodes/interfaces with long lifetimes in realistic seawater including inducing passivating anion layers, preferential OH−adsorption, employing anti‐corrosion materials, fabricating protective layers, immobilizing Cl− on the surface of electrocatalysts, tailoring Cl− adsorption sites, inhibition of OH− binding to Mg2+ and Ca2+, inhibition of Mg and Ca hydroxide precipitation adherence, and co‐electrosynthesis of nano‐sized Mg hydroxides. Synthesis methods of electrocatalysts/electrodes and innovations in electrolyzer are also discussed. Furthermore, the prospects for developing seawater splitting technologies for clean hydrogen generation are summarized. We found that researchers have rethought the role of Cl− ions, as well as more attention to cathodic reaction and electrolyzers, which is conducive to accelerate the commercialization of seawater electrolysis.

High-speed formation of pure copper layers via multibeam laser metal deposition with blue lasers

To realize a carbon-neutral society, it is necessary to shift from gasoline-powered vehicles to electric vehicles. Electric vehicles use copper components such as coil motors and batteries for which copper joining technology is important. Additive manufacturing is one of the most essential technologies for the next generation of manufacturing. Therefore, the technology for forming pure copper layer on a pure copper substrate is important. Laser metal deposition (LMD) is one of the additive manufacturing technologies. A blue diode laser is expected to be effective in shaping pure copper parts because light absorptance of pure copper at blue light is higher than that of near-infrared light. Thus, a multibeam LMD system with the blue diode laser in which metal powder was supplied perpendicular to the processing point and multiple lasers were irradiated from the surroundings was developed for additively manufactured pure copper. In our previous study, we succeeded in forming a pure copper layer on a pure copper substrate at a speed of 1.5 mm/s with blue diode lasers. However, an increase in processing speed was necessary for industrial application. It is considered that the improvement of energy density at the processing point and the control of heat input to the powder and the substrate by lasers are essential to improve the processing speed. Therefore, in this study, we designed an optical system with ten times higher energy density and calculated the heat input to the powder to form a pure copper layer at a speed of 10 mm/s or faster.

Research on the Application of Statistical Anomaly Detection in Tobacco Sales Anomaly Detection

With the rapid development of a new generation of information technology, digitalization and informatization have become key factors in enhancing the core competitiveness of the tobacco industry. Detecting and monitoring abnormal tobacco sales behaviors play a vital role in combating illegal transactions and ensuring the healthy development of the tobacco industry. Manual identification of abnormal sales behaviors presents practical issues, such as low efficiency, strong subjectivity, and a reliance on accumulated experience. Utilizing statistical probability theory to help the tobacco bureau determine the threshold for defining abnormal sales behavior can effectively improve the efficiency of anomaly detection. This study applies relevant theories of statistical anomaly detection in combination with practical production needs, establishing four threshold criteria for identifying abnormal sales behaviors: the number of days without retail data, the ratio of daily sales volume to the sales volume of the previous seven days, the number of days of available sales, and the number of days with scanning activity per week. These criteria make it possible to automate and dynamically identify abnormal sales behaviors in subsequent sales situations.

The Graph Becomes the Dataset: Compiling Historical and Current RTG Data into One Place

Radioisotope thermoelectric generator (RTG) technology has a very long and incredibly successful history of providing heat and power to some of humankind’s most successful space exploration missions. Members of the community that support and maintain this technology often like to show the entire history of RTG performance on “The Graph.” Meant to impress, The Graph does its job in that regard. Unless you were connected to the right people, however, it was very difficult to get a copy of The Graph or its underlying data. This made it difficult for many to dive into the technical details or evaluate individual RTG performance from historical missions. To make matters worse, the performance for several missions in The Graph were incomplete. In 2020, with a little extra time on their hands thanks to COVID, the authors reached throughout the RTG community to locate and collate the missing RTG data. This information was then published as an open-source tabular Dataset. Users can now build their own version of The Graph or use the data for a more detailed analysis of RTG performance. Updates to the currently operating missions in The Dataset are expected to occur on a roughly annual basis. This Dataset represents the most comprehensive, authoritative, up-to-date repository of all RTG performance available today.

Development of an Intelligent Coal Production and Operation Platform Based on a Real-Time Data Warehouse and AI Model

Smart mining solutions currently suffer from inadequate big data support and insufficient AI applications. The main reason for these limitations is the absence of a comprehensive industrial internet cloud platform tailored for the coal industry, which restricts resource integration. This paper presents the development of an innovative platform designed to enhance safety, operational efficiency, and automation in fully mechanized coal mining in China. This platform integrates cloud edge computing, real-time data processing, and AI-driven analytics to improve decision-making and maintenance strategies. Several AI models have been developed for the proactive maintenance of comprehensive mining face equipment, including early warnings for periodic weighting and the detection of common faults such as those in the shearer, hydraulic support, and conveyor. The platform leverages large-scale knowledge graph models and Graph Retrieval-Augmented Generation (GraphRAG) technology to build structured knowledge graphs. This facilitates intelligent Q&A capabilities and precise fault diagnosis, thereby enhancing system responsiveness and improving the accuracy of fault resolution. The practical process of implementing such a platform primarily based on open-source components is summarized in this paper.

Accordion-Structured Hydrogel Battery Capable of Maintaining Ion Gradients for Extended Periods.

Inspired by the electric eel, biomimetic, biocompatible energy storage, and power generation technologies show promise for applications in portable and wearable electronic devices by mimicking the electric cell tandem structure of the electric eel and utilizing ionic gradients between hydrogel compartments to generate electricity. Previously, inspired by the unique morphology of the torpedo fish, an artificial flexible power source that can output a large current was introduced. This power source uses a hydrogel-infused paper hybrid to create, accordionize, and reconfigure arbitrary-sized gel films in series and parallel, and the power output of the flexible battery was significantly enhanced. However, maintaining the ionic gradient of hydrogel batteries during storage remains a challenge. Here, by borrowing the isolation properties of the accordion structure, we propose a unique paper accordion structure design to fabricate an Accordion-Structured Hydrogel Battery (ASHB). Pretreatment of hydrogel-injected paper strips improved storage stability and maintained the ionic gradient of hydrogel cells in the nonworking state, so that the cell's gradient retention time after the assembly is completed is increased by at least 30 h compared to stacking, and its per-cell operating voltage is still able to reach. The design also makes the assembly and use of flexible batteries more modular and holistic. In the future, it may be possible to power the cells with ions generated by the human body or the metabolites of living organisms, leading to the development of more efficient, sustainable, and eco-friendly power solutions.

UNDER THE INFLUENCE OF THE INDUSTRIAL REVOLUTION: A RETROSPECTIVE ANALYSIS

The article is intended to analyze the cyclicality of the development of construction, caused by fundamental qualitative changes in the basic generations of equipment, machines, technologies, vehicles and large structures in the leading sectors of the economy, i.e. industrial revolutions. The first industrial revolution created the organizational-economic, scientific-technical and institutional prerequisites for a conceptual rethinking of the principles and norms of construction and brought to life the pre-monopolist-industrial model of the construction sector (Construction 1.0). Its main feature was the active use of metal elements (cast iron, wrought iron, steel), glass, concrete and reinforced concrete in construction production. The industrial-extensive model of Construction 2.0 covers the period from the beginning of the 20th century. until the end of the 1960s and coincides with the Second Industrial Revolution. This model is distinguished by large-scale processes of territorial and spatial concentration of construction based on the accumulation of means of production, labor and capital investments in large construction organizations and complex processes of industrialization of the construction sector. From the first half of the 1970s to the first half of the 2000s, the energy-efficient construction model (Construction 3.0), brought to life by the Third Industrial Revolution, prevails in the world. This period is characterized by the systematic orientation of construction production to the optimization of thermal energy provision of objects, the rationalization of the processes of using energy resources at all stages of the construction and production process, and the minimization of the level of consumption of energy and material resources. Today, marked by the unfolding of the Fourth Industrial Revolution, is characterized by the global development of an ecosystem-type green construction model (Construction 4.0) – an environmentally responsible and resource-saving process of social reproduction of construction products. This model is based on deep integration of green and digital transition technologies and is ensured by large-scale digitization of construction works.

Advances in Deepfake Generation and Detection Technologies: Challenges and Opportunities

In recent years, deep learning technology has been exploited to create fake videos, leading to the widespread presence of deepfake content on the Internet. This technology facilitates the production of counterfeit content, including pornographic films, fabricated news, and political misinformation, by altering or substituting the facial data, expressions, and body movements in original videos, as well as synthesizing voices of specific individuals. Various generative tools, such as generative adversarial networks (GANs), are employed in deep forgery, introducing significant risk challenges. Detection technology serves as a crucial countermeasure to mitigate the adverse effects, with methods based on spatial and frequency domain information playing a pivotal role. This paper delves into the generative tools and detection techniques of deepfake technology, examining their principles and applications, and thoroughly discusses the risk challenges encountered. The aim is to furnish references for further research and practical measures, enhancing understanding and management of this technology and its impacts, thereby fostering the advancement and refinement of the field.

Design and Modeling of Coreless Magnetoelectric Transducers for Snake-like Wave Energy Converters

With the development of the economy, people’s demand for energy is increasing, which has led to a shortage of fossil fuels. Wave energy is a widely distributed renewable energy source, and the development of wave energy generation technology can greatly alleviate the energy shortage problem. This study takes the snake-like wave energy converter (WEC) as an example and designs a coreless magnetoelectric transducer for it. The structure of the coreless magnetoelectric transducer is relatively simple, eliminating the iron core in the transducer, which can eliminate its own damping. At the same time, this structure can minimize the gap between the magnet and the coil, improve energy conversion efficiency, and work continuously under complex working conditions. This study takes two types of coreless magnetoelectric transducers as examples to analyze. This study aims to establish equivalent magnetic circuit models for the coreless magnetoelectric transducers, explore the effects of different magnets on the performance of the transducers, and optimize the parameters in the transducers. We used simulation software to analyze the transducer and verify the accuracy of the models. Finally, prototypes of the coreless magnetoelectric transducers were made, and a testing system for the transducer was established to test its energy conversion capability. Our experiments show that coreless magnetoelectric transducers have good energy conversion capabilities and can be used as transducers for snake-like WECs. At the same time, this type of transducer can also be applied to other types of WECs, providing a new approach for the research of WECs.

A Review of Challenges and Developments in Wireless Channel Key Generation Technology

In recent years, physical layer security has become one of the core technologies for wireless communication system security. Physical layer encryption is based on the inherent reciprocity, time-varying, spatial uniqueness and unpredictability of wireless communication systems to generate keys, which are naturally unforgeable and steganography-proof. However, the research of physical layer key generation technology also faces many challenges, such as the problem of poor key generation performance due to signal interference, the problem of lower randomness and slower key generation rate in quasi-static channel environment, and the problem of lower key consistency between two legitimate communication parties due to the existence of channel estimation errors; this paper provides a systematic explanation of the traditional model of key generation for wireless channels and a typical solution for this series of problems. In this paper, the traditional model of wireless channel key generation is systematically explained, and the typical solutions to this series of problems are studied, analysed and compared in terms of performance.

The future is only the beginning

Recent advancements in genome editing have captured the attention of scientists and policymakers, who contend that the technology has a large role to play in advancing food and climate security on the African continent. However, the modest results of earlier generations of biotechnology—such as genetically modified (GM) crops—raise questions about the sustainability of new technological interventions. This special feature examines lessons learned from previous generations of GM crops and other agricultural technologies, using them to analyze the portfolio of gene edited crops being developed for African farmers today. In this article, we introduce the 6 papers that make up the special feature by way of examining future-oriented discourses around the advancement of genome editing. Drawing on Science and Technology Studies, political ecology, and critical development studies, this introduction highlights the crucial factors that shape technology development, agricultural practice, and the politics of knowing and emphasizes the need to look toward multiple, diverse futures.

Comparative Study of Deflector Configurations under Variable Vertical Angle of Incidence and Wind Speed through Transient 3D CFD Modeling of Savonius Turbine

The demand for clean and sustainable energy has led to the exploration of innovative technologies for renewable energy generation. The Savonius turbine has emerged as a promising solution for harnessing wind energy in urban environments due to its unique design, simplicity, structural stability, and ability to capture wind energy from any direction. However, the efficiency of Savonius turbines poses a challenge that affects their overall performance. Extensive research efforts have been dedicated to enhancing their efficiency and optimizing their performance in urban settings. For instance, an axisymmetric omnidirectional deflector (AOD) was introduced to improve performance in all wind directions. Despite these advancements, the effect of wind incident angles on Savonius turbine performance has not been thoroughly investigated. This study aims to fill this knowledge gap by examining the performance of standard Savonius configurations (STD) compared to the basic configuration of the deflector (AOD1) and to the optimized one (AOD2) under different wind incident angles and wind speeds. One key finding was the consistent superior performance of this AOD2 configuration across all incident angles and wind speeds. It consistently outperformed the other configurations, demonstrating its potential as an optimized configuration for wind turbine applications. For instance, at an incident angle of 0°, the power coefficient of the configuration of AOD2 was 61% more than the STD configuration. This ratio rose to 88% at an incident angle of 20° and 125% at an incident angle of 40°.

Voltage Deviation Improvement in Microgrid Operation through Demand Response Using Imperialist Competitive and Genetic Algorithms

In recent decades, with the expansion of distributed energy generation technologies and the increasing need for more flexibility and efficiency in energy distribution systems, microgrids have been considered a promising innovative solution for local energy supply and enhancing resilience against network fluctuations. One of the basic challenges in the operation of microgrids is the optimal management of voltage and frequency in the network, which has been the subject of extensive research in the field of microgrid operational optimization. The energy demand is considered a crucial element for energy management due to its fluctuating nature over the day. The use of demand response strategies for energy management is one of the most important factors in dealing with renewables. These strategies enable better energy management in microgrids, thereby improving system efficiency and stability. Given the complexity of optimization problems related to microgrid management, evolutionary optimization algorithms such as the Imperialist Competitive Algorithm (ICA) and Genetic Algorithm (GA) have gained great attention. These algorithms enable solving high-complexity optimization problems by considering various constraints and multiple objectives. In this paper, both ICA and GA, as well as their hybrid application, are used to significantly enhance the voltage regulation in microgrids. The integration of optimization techniques with demand response strategies improves the overall system efficiency and stability. The results proved that the hybrid method provides valuable insights for optimizing energy management systems.

Modeling and Performance Analysis of Solid Oxide Fuel Cell Power Generation System for Hypersonic Vehicles

Advanced airborne power generation technology represents one of the most effective solutions for meeting the electricity requirements of hypersonic vehicles during long-endurance flights. This paper proposes a power generation system that integrates a high-temperature fuel cell to tackle the challenges associated with power generation in the hypersonic field, utilizing techniques such as inlet pressurization, autothermal reforming, and anode recirculation. Firstly, the power generation system is modeled modularly. Secondly, the influence of key parameters on the system’s performance is analyzed. Thirdly, the performance of the power generation system under the design conditions is simulated and evaluated. Finally, the weight distribution and exergy loss of the system’s components under the design conditions are calculated. The results indicate that the system’s electrical efficiency increases with fuel utilization, decreases with rising current density and steam-to-carbon ratio (SCR), and initially increases before declining with increasing fuel cell operating temperature. Under the design conditions, the system’s power output is 48.08 kW, with an electrical efficiency of 51.77%. The total weight of the power generation system is 77.09 kg, with the fuel cell comprising 69.60% of this weight, resulting in a power density of 0.62 kW/kg. The exergy efficiency of the system is 55.86%, with the solid oxide fuel cell (SOFC) exhibiting the highest exergy loss, while the mixer demonstrates the greatest exergy efficiency. This study supports the application of high-temperature fuel cells in the hypersonic field.