Generation Technologies Research Articles

Application of large language model combined with retrieval enhanced generation technology in digestive endoscopic nursing

BackgroundAlthough large language models (LLMs) have demonstrated powerful capabilities in general domains, they may output information in the medical field that could be incorrect, incomplete, or fabricated. They are also unable to answer personalized questions related to departments or individual patient health. Retrieval-augmented generation technology (RAG) can introduce external knowledge bases and utilize the retrieved information to generate answers or text, thereby enhancing prediction accuracy.MethodWe introduced internal departmental data and 17 commonly used gastroenterology guidelines as a knowledge base. Based on RAG, we developed the Endo-chat medical chat application, which can answer patient questions related to gastrointestinal endoscopy. We then included 200 patients undergoing gastrointestinal endoscopy, randomly divided into two groups of 100 each, for a questionnaire survey. A comparative evaluation was conducted between the traditional manual methods and Endo-chat.ResultsCompared to ChatGPT, Endo-chat can accurately and professionally answer relevant questions after matching the knowledge base. In terms of response efficiency, completeness, and patient satisfaction, Endo-chat outperformed manual methods significantly. There was no statistical difference in response accuracy between the two. Patients showed a preference for AI services and expressed support for the introduction of AI. All participating nurses in the survey believed that introducing AI could reduce nursing workload.ConclusionIn clinical practice, Endo-chat can be used as a highly effective auxiliary tool for digestive endoscopic care.

Secure and Lightweight Cluster-Based User Authentication Protocol for IoMT Deployment

Authentication is considered one of the most critical technologies for the next generation of the Internet of Medical Things (IoMT) due to its ability to significantly improve the security of sensors. However, higher frequency cyber-attacks and more intrusion methods significantly increase the security risks of IoMT sensor devices, resulting in more and more patients’ privacy being threatened. Different from traditional IoT devices, sensors are generally considered to be based on low-cost hardware designs with limited storage resources; thus, authentication techniques for IoMT scenarios might not be applicable anymore. In this paper, we propose an efficient three-factor cluster-based user authentication protocol (3ECAP). Specifically, we establish the security association between the user and the sensor cluster through fine-grained access control based on Merkle, which perfectly achieves the segmentation of permission. We then demonstrate that 3ECAP can address the privilege escalation attack caused by permission segmentation. Moreover, we further analyze the security performance and communication cost using formal and non-formal security analysis, Proverif, and NS3. Simulation results demonstrated the robustness of 3ECAP against various cyber-attacks and its applicability in an IoMT environment with limited storage resources.

High‐speed and contactless inspection of defective micro‐LEDs through the photovoltaic effect

AbstractThe most significant challenge associated with micro‐light‐emitting‐diode (micro‐LED) displays, which are anticipated to be the next generation of display technology, is the high manufacturing cost. In order to reduce manufacturing costs, it is essential to improve yield. Improving the manufacturing yield of them necessitates the evaluation of micro‐LED chips prior to their installation onto substrates. However, the microsize and large quantity of these chips renders inspection difficult with conventional inspection methods. Herein, we propose a method for inspecting micro‐LED chips by measuring the voltage generated between the anode and cathode due to the photovoltaic effect using a developed proximity capacitance image sensor. As this inspection method does not require the use of probe pins to contact LED electrodes, it enables simultaneous inspection of multiple chips in a short time without causing any damage to the electrodes. In this paper, an experimental system equipped with this sensor was developed to demonstrate the basic measurement principle. Moreover, we demonstrated that more than 50,000 micro‐LED chips with a size of 60 μm × 34 μm can be simultaneously inspected in approximately 2 s.

Research Progress in Enhancing Proton Conductivity of Sulfonated Aromatic Polymers with ZIFs for Fuel Cell Applications

The escalating global temperatures and their adverse effects underscore the growing imperative for the widespread adoption of clean fuels, notably hydrogen. Proton Exchange Membrane Fuel Cells (PEMFC) emerge as a pivotal green energy technology, facilitating electricity and water generation. The optimization of PEMFC efficiency hinges on the judicious selection and fabrication of polymer membranes. Within innovative materials, Zeolitic Imidazolate Frameworks (ZIFs) represent a novel subclass within the expansive family of Metal-Organic Frameworks (MOFs). ZIFs exhibit promising potential in PEMFCs, owing to their distinctive properties such as a substantial contact surface, inherent porosity, and a sizable pore volume. This comprehensive review delves into composite membranes featuring ZIFs, shedding light on their chemical and thermal attributes. Additionally, the exploration extends to elucidating the diverse applications of ZIF compounds, accompanied by an in-depth discussion of selected chemical and thermal properties inherent to ZIF compounds. Incorporating ZIFs into various polymers yielded intriguing outcomes, demonstrating a notable enhancement in proton conductivity. The compilation of this review aims to provide researchers with foundational insights into the realm of ZIFs, serving as a valuable resource for future investigations and advancements in the field.

Transfer learning enabled transformer-based generative adversarial networks for modeling and generating terahertz channels

Terahertz communications are envisioned as a promising technology for the sixth generation and beyond wireless systems, which can support wireless links with Terabits-per-second (Tbps) data rates. As the foundation of designing terahertz communications, channel modeling and characterization are crucial to scrutinize the potential of this spectrum. However, current channel modeling in the terahertz band heavily relies on time-consuming and costly measurements. Here, we propose a transfer learning enabled transformer based generative adversarial network to mitigate this problem in terahertz channel modeling. Specifically, as a fundamental building block, a generative adversarial network is exploited to generate channel parameters. To improve the accuracy, a transformer structure with a self-attention mechanism is incorporated in generative adversarial network. Still incurring errors compared with ground-truth measurement, a transfer learning is designed to solve the mismatch between the formulated network and measurement. The proposed method can achieve high accuracy in channel modeling, while requiring only rather limited amount of measurement, which is a promising complement of current channel modeling techniques.

Humidity Sensing Using Polymers: A Critical Review of Current Technologies and Emerging Trends

In the post-pandemic era, human demand for a healthy lifestyle and a smart society has surged, leading to vibrant growth in the field of flexible electronic sensor technology for health monitoring. Flexible polymer humidity sensors are not only capable of the real-time monitoring of human respiration and skin moisture information but also serve as a non-contact human–machine interaction method. In addition, the development of moist-electric generation technology is expected to break free from the traditional reliance of flexible electronic devices on power equipment, which is of significant importance for the miniaturization, reliability, and environmentally friendly development of flexible devices. Currently, flexible polymer humidity sensors are playing a significant role in the field of wearable electronic devices and thus have attracted considerable attention. This review begins by introducing the structural types and working principles of various humidity sensors, including the types of capacitive, impedance/resistive, frequency-based, fiber optic, and voltage-based sensors. It mainly focuses on the latest research advancements in flexible polymer humidity sensors, particularly in the modification of humidity-sensitive materials, sensor fabrication, and hygrosensitivity mechanisms. Studies on material composites including different types of polymers, polymers combined with porous nanostructured materials, polymers combined with metal oxides, and two-dimensional materials are reviewed, along with a comparative summary of the fabrication and performance mechanisms of related devices. This paper concludes with a discussion on the current challenges and opportunities faced by flexible polymer humidity sensors, providing new research perspectives for their future development.

Children's Education in the Metaverse Era: Between the Rapid Growth of Information Technology and Self-learning of Generation Z

Children's Education in the Metaverse Era: Between the Rapid Growth of Information Technology and Self-learning of Generation Z

Green Power Generation from the Tigris River Using Pressure Retarded Osmosis Process

Sustainability including renewable energy and green power, is one of the important feature in recent years due to environmental constraints and the emission of CO2 from fossil fuel. Pressure retarded osmosis (PRO) process is considered one of the effective technology for power generation. This study assessed the application of pressure retarded osmosis to produce power from Tigris River water in Baghdad City, Iraq. Spiral wound TFC membrane was tested in the PRO process with different variables. The effect of different types of draw solutions (MgCl2, NaCl, Sodium Formate, KCl, Sodium Acetate), applied pressure (0 – 7bar), and draw solution concentration (0.08 and 0.4M) were tested in this work. The flux, recovery, and power density for the five draw solution in the order MgCl2>NaCl>sodium formate>KCl>sodium acetate, while the reverse solute flux in the order MgCl2<sodium acetate<KCl<sodium formate<NaCl. Experimentally the membrane pure water permeability (A) was found to be 4.87L/m2.h.bar. The result revealed that the reverse solute flux and the solute permeability coefficient for MgCl2 was 0.55g/m2.h and 8.78×10-8m/s. The flux, recovery, and power density for MgCl2 with a concentration of 0.4M and applied pressure of 7bar was 1.69 LMH, 19%, and 0.33W/m2, respectively.

Nanomedicine as a Better Therapeutic Approach: An Overview

Abstract: The fields of nanotechnology and nanomedicine have undergone a revolution. There has been a striking rise in authorized nanomedicines since 1980. Apart from functioning as thera-peutic agents, they also act as carriers for delivering various active pharmaceuticals to target or-gans. The ultimate goal of nanomedicine has always been the generation of translational technol-ogies that can improve current therapies. Nanocrystals, nanotubes, liposomes, exosomes, solid li-pid nanoparticles, polymeric nanoparticles, and metallic and magnetic nanoparticles are examples of nanostructures that are now in the market as well as in ongoing research. The preparation of these nanomaterials requires consideration of a number of difficulties. Only a few of these nano-materials were successful in obtaining marketing permission after passing all required toxicologi-cal and ethical evaluations and making them affordable to users and, at the same time, profitable to investors. Cancer, central nervous system (CNS) diseases, and cardiovascular (CVS) diseases represented the primary targets of nanotechnology applied to medicine. Therefore, this review ar-ticle is focused on providing a summary of several nano-based delivery systems, including their limitations and prospects in different therapeutic fields.

Qualitative and quantitative analysis of major components in Abelmoschus manihot flowers treated with different drying methods using UHPLC Q-Exactive MS and HPLC-PDA

The flowers of Abelmoschus manihot (L.) Medic are commonly used in clinical practice in China to cure forms of chronic kidney disease. Despite a long history of traditional use, the flowers obtained by different drying technologies have never been fully chemically characterized, and the ranges of constituents between different drying methods have not been comprehensively reported. To establish a quality control and chemical characterization method, a total of 14 batches of samples corresponding to 14 postharvest treatments were studied. Seven flavonoids were quantified using a HPLC-PDA method. The method was validated in terms of linearity (r > 0.999), precision (intra- and inter-day: 0.7–1.4%), accuracy (99.90–100.7%), detection limit (0.34–0.46µg/mL) and quantification limit (1.15–1.52µg/mL). The contents of total flavonoids in manihot flowers were as follows in descending order: Infrared Drying (50.96mg/g) > Microwave Drying (41.84mg/g) ≈ Hot-air Drying (39.58mg/g) ≈ Fresh (39.35mg/g) ≈ Primary Drying (38.95mg/g). Principal component analysis showed that samples processed with Fresh, Primary Drying, and the investigated three modern drying methods were well classified into three domains, indicating an important difference between drying methods. For the purpose of saving the flavonoids contents, infrared drying under 80~100 ℃ would be most acceptable. Furthermore, using UHPLC Q-Exactive Orbitrap MS data with targeted and non-targeted approaches, 28 compounds were identified in Abelmoschus manihot samples. Flavonoids were the main group of compounds found in Abelmoschus manihot flowers. The study could provide the scientific evidence for the selection and optimization of appropriate drying method for manihot flowers, and also provide the reference for the formation of generic primary drying processing technology for medicinal flowers containing flavonoids.

Towards a Standardized LCOE Calculation for Informed Decision-Making in Energy Policy and Investment: Application to the Colombian Context

The Levelized cost of electricity - LCOE represents a constant cost per unit of generated electrical energy, resulting from the analysis of the total costs throughout the life cycle of a generation plant. Its widespread use, thanks to its simplicity of calculation and potential of standardization, has made it one of the primary criteria for comparing electricity generation technologies. However, in the pursuit of simplification and generalization, certain aspects associated with the socioeconomic context of the region, as well as accounting and financial concepts, are excluded due to externalities or incentives related to regulatory and fiscal policies. These exclusions affect the accuracy of LCOE and introduce uncertainty when using it as a criterion for investment decision-making or allocation of public resources for the development of renewable sources. This article proposes a clear and standardized methodology for calculating LCOE, which allows for a fair and precise comparison of renewable energy generation options in rural areas. It contributes to informed and transparent decision-making in the fields of energy policy and public investment for expanding electricity service coverage. The proposed methodology is based on the financial cash flow matrix to address variability sources in the calculation, considering the local context of the generation project.

Wideband Microwave Frequency-Hopping Signal Generation Technology Based on Coherent Double Optical Comb

Wideband Microwave Frequency-Hopping Signal Generation Technology Based on Coherent Double Optical Comb

Portfolio effects in green hydrogen production under temporal matching requirements

This article investigates temporal matching requirements between electrolytic hydrogen production and dedicated renewable electricity generation for hydrogen to qualify as “green”. In contrast to previous studies which found that a more granular matching increases production costs, we study cost advantages for hourly matching through technological and spatial diversification. To this end, we develop and apply a linear cost-optimization model to quantify the resulting portfolio effects. We identify two types of portfolio effects, “technological” and “locational” ones, and quantify these for different portfolio sizes and types of power generation technologies. Portfolio effects in Germany turn out to be in the range of 3–8% when aggregating two locations, and up to 21% for a nation-wide portfolio. Finally, the implications of our findings in terms of discrimination against small players and for the modeling of temporal matching requirements are discussed.

A novel PEMFC-GT-ST power generation system employing supercritical water gasification of coal for enhanced hydrogen production

This study presents an innovative coal-fired power generation system that integrates a Proton Exchange Membrane Fuel Cell (PEMFC), Gas Turbine (GT), and Steam Turbine (ST) with a supercritical water gasification (SCWG) process designed to efficiently convert coal into hydrogen. A pivotal feature of this system is the first-time integration of advanced two-step SCWG technology with PEMFC, which significantly boosts hydrogen yield, thereby elevating overall efficiency. By effectively addressing the thermodynamic limitations of the Carnot cycle, the proposed system achieves an impressive coal-to-electricity conversion efficiency of 51.61%. Economic viability is demonstrated through a competitive levelized cost of energy (LCOE) of $0.052 per kWh and a rapid payback period of approximately 2.87 years. Furthermore, the study analyzes the impact of various operational parameters—such as coal feed capacity, water-to-coal ratio, operating temperatures of the PEMFC, fuel utilization rates, airflow, and hydrogen bypass flow—on system performance. The findings not only advance the efficiency of coal-to-electricity conversion but also contribute valuable insights to the evolution of sustainable coal-fueled power generation technologies.

Effect of operating temperature on ammonia decomposition behavior and cell performance of direct ammonia solid oxide fuel cells

Direct ammonia solid oxide fuel cells (DA-SOFC) are regarded as a promising power generation technology. Nevertheless, the catalytic reaction of ammonia on the anode surface significantly affects DA-SOFC performance. This study explores the deterioration of DA-SOFC performance in the 550–700 °C and the interaction between NH3 decomposition and electrochemical reactions. The findings indicate that, at 550 °C, compared to H2, the reduction in power density of NH3 18.58% exceeds 4.56%t of NH3 d.s.g. (mixtures, 0.75H2 + 0.25N2). The anodic polarization impedance of NH3 exceeds that of H2 and NH3 d.s.g. by 51.1% and 28.9%, respectively. Cathode utilizing O2 has a dual impact on NH3 decomposition, at lower temperatures, oxidizing the anode's active site, decreasing NH3 decomposition rate, resulting in insufficient H2 supply, reducing electron transfer coefficient. Conversely, at higher temperatures, O2 promotes NH3 decomposition by boosting H2 consumption. However, more N2 is produced, increasing the concentration loss.

Current Status and Prospects of High-Speed Direct-Drive Power Generation Technology

Current Status and Prospects of High-Speed Direct-Drive Power Generation Technology

Representative Image Outpainting and Image Super-Resolution Methods Based on Deep Learning

The image generation based on deep learning is a technology that can generate new images or outpaint old images or improve visual effect of old images through learning from input data, according to deep learning structure. The representative technologies of image generation are image outpainting and image super-resolution. Deep learning is widely utilized in the field of computer vision. Facing different needs, it is essential to choose proper ways. This essay reviews several representative and new methods of image outpainting and image super-resolution. Compared with the results generated by old methods, the results generated by new image outpainting methods introduced in this essay have greater precision and clarity, the methods of image super-resolution that are suitable for all fields and professional fields can learn from each others dataset manually to train and develop. There is still unimaginable prospect of deep learning in the field of image outpainting and image super-resolution. Therefore, it is worthy of attention.

An intelligent generative method of fashion design combining attribute knowledge and Stable Diffusion Model

Artificial intelligence generation technology has brought new opportunities to the field of fashion design. Attribute knowledge has a significant impact on the overall effect of fashion design. Contemporary generative methods of fashion design frequently yield results lacking semantic information or missing specific attributes. To address the problem, this study aims for an intelligent generative method of fashion design through constructing prompt templates and a specific attribute low-rank adaption (LoRA) to combine fashion attribute knowledge into the generative process of the Stable Diffusion Model. First, a fashion attribute knowledge graph is constructed to establish prompt templates, and natural language descriptions are transformed into professional and complete prompt through GPT-4. Second, the fashion dataset is annotated with templates to filter specific attributes for LoRA training, followed by controlling fashion attributes in generation. Furthermore, analyses of the generation of women’s jacket designs show that the proposed method consistently improves the accuracy and stability of attributes in fashion design generation.

Exploring the potential of biohydrogen as a sustainable energy solution for Pakistan: A review of production processes and policy challenges

Due to growing carbon dioxide emissions and the depletion of fossil-based energy sources, international studies have been focusing more intensely on developing hydrogen as a source of renewable energy. Biohydrogen is an exciting and green alternative energy source with various different benefits. Unlike traditional energy sources, biohydrogen production does not emit pollutants, making it a more environmentally friendly option. Biohydrogen generation, particularly from microalgae and other low-cost biomass feedstocks, so offers the dual benefit of delivering clean electricity while absorbing Carbon Dioxide. This research investigates the possibility of biohydrogen as a sustainable energy solution for Pakistan's climate issue. We examine the current state of biohydrogen generation technologies, such as dark fermentation, photo fermentation, bio photolysis, with a focus on their potential application in Pakistan. The study investigates global advances in biohydrogen research and their significance in Pakistan, demonstrating biohydrogen's potential contribution to Pakistan's energy independence and environmental targets, as well as the practical and policy-related challenges that must be addressed to advance biohydrogen energy generation and wider adoption.

“Through the looking glass: envisioning new library technologies” AI is changing what photography means for libraries

Purpose The purpose of this column is to interrogate what it means for photographs as practical storehouses of data, how that interacts with society’s understanding of photography and what all of this may mean for the role of libraries as they relate to photographs. Design/methodology/approach A new generation of camera technology, integrated into phones, is being released. This column examines the implications for society at large, adding libraries in particular. Findings Once it is easy to do dramatic photo manipulation on the device that takes the photos, it will change how users think about photos. This has implications for how libraries plan information literacy, advocate for their users in the creation of standards and manage their collections. Originality/value This column will help information professionals think through the implications of this change for the future of the profession.