bluuebunny/crossref_metadata_2025 huggingface dataset:
Cannabinoides sintéticos: una revisión teórica integradora
Authors: Iribarren González Gaizka , Pons Díez Xavier
Published: January 2025

Los cannabinoides sintéticos son agonistas de los receptores cannabinoides, y producen efectos similares al Δ9 – tetrahidrocannabinol, principal fitocannabinoide psicoactivo del Cannabis Sativa. Los cannabinoides sintéticos son drogas catalogadas como “nuevas sustancias psicoactivas” (NPS), siendo además el tipo de sustancia más numerosa de este grupo con más de 200 tipos. Los efectos de los cannabinoides sintéticos, aunque son similares a los producidos por el THC, son del orden de 2 a 800 más potentes, pues son agonistas totales de los receptores. Entre los efectos adversos más reportados destacan la ansiedad, las náuseas, las paranoias y la taquicardia, aunque existe una fuerte relación entre los trastornos psicóticos y el consumo de cannabinoides sintéticos. A pesar de que la prevalencia de consumo de estas sustancias es relativamente baja para la población general, existen diferentes subpoblaciones como las personas privadas de libertad o las personas policonsumidoras cuyo consumo es significativamente mayor debido a distintas motivaciones de uso entre las que destaca la dificultad de rastrearlos en los análisis de drogas.
Analysis on the Effects of Ocean on Temperature
Authors: Chen Zixin
Published: January 2025

Nowadays, global climate change is one of the main concerns of modern society and an enormous issue for all humankind. Temperature is closely related to the greenhouse effect, so one of the major topics to be investigated in global climate is the factors affecting temperature rise. To estimate this change, it is typically crucial to forecast the temperature in the future. The Earth's average temperature is determined by a multi-step and complex process that uses statistical techniques and data from various sources. By collecting and summarizing data, this paper mainly focuses on analyzing the trends in sea surface temperature over the past few hundred years. Through recent studies and case analysis, this paper highlights that the ocean has become an indispensable part of mitigating climate warming and stabilizing temperature. The significance of studying the impact of the ocean on temperature lies in its role as a climate regulator, providing scientific basis for global climate change and guidance for regional adaptation efforts. Because of its enormous heat capacity and thermal inertia, the ocean is an important component of the climate system and plays a buffering and regulating role in atmospheric temperature.
Research on the Direct Conversion of Human Skin Cells into Nerve Cells
Authors: Zhang Nenghan
Published: January 2025

The direct conversion of human skin cells into nerve cells is an emerging field with potential applications in regenerative medicine. This study investigates the conversion of Human Skin-Derived Progenitor Cells (hSKPs) and Human Dermal Fibroblasts (hDFs) into neural cells using specific transcription factors or molecular cocktails. A review of the literature was conducted to inform the design of a research study employing a combination of in vitro and in vivo experiments and molecular biology techniques to induce neural differentiation in skin-derived cells. The findings demonstrate that both hSKPs and hDFs can successfully differentiate into neural cells, displaying neuronal morphology and electrophysiological functionality. These studies conclude that skin cells possess significant potential for direct reprogramming into functional neurons, providing a direct approach for studying neurological diseases and developing therapeutic strategies. However, challenges regarding the efficiency and safety of the reprogramming process persist, necessitating further optimization prior to clinical application
The Advances of CAR-T, CAR-NK, CAR-M in Solid Tumor Immunotherapy
Authors: Dong Jiaxing , Zhang Kexin
Published: January 2025

Cancer is one of the leading causes of death worldwide, responsible for around 10 million deaths annually. Although a type of immune cell therapy known as CAR-T has shown strong results in treating blood cancers, it faces challenges when used for solid tumors. These challenges include difficulty in penetrating the tumor, the presence of a suppressive environment within the tumor, et al. As a result, alternative therapies, including CAR-NKs and CAR-Ms, have gained attention. CAR-NK cells offer benefits such as lower treatment costs and fewer side effects, while CAR-M cells are able to infiltrate solid tumors more effectively and have a broader range of anti-tumor effects. This article reviews the differences between these three therapies, examining their mechanisms, advantages, and limitations. The findings suggest that combining these therapies could enhance their effectiveness, offering new hope for treating solid tumors more efficiently. CAR-NK and CAR-M therapies hold significant promise in overcoming the limitations of CAR-T and improving cancer treatment outcomes
Review on Intestinal Stem Cell
Authors: Chen Ruihan
Published: January 2025

The intestine performs the functions of absorption and protection. Located in the intestine, the intestinal stem cells play an important role in sustaining the intestinal homeostasis. The niche environment affects the intestinal stem cells functions via signaling, structural, and immune pathways. Active intestinal stem cells can differentiate into other intestinal cells and replenish them. This process is regulated by various signaling pathways, including Wnt, BMP, EGF and so on. In addition, other impact factors like aging and microbiota may also influence the intestinal homeostasis through affecting intestinal stem cells. Colorectal cancer, originating from abnormal intestinal stem, may be treated by multiple therapies
Integrating Deep Learning with Generative Design and Topology Optimization for Efficient Additive Manufacturing
Authors: Huang Lufan
Published: January 2025

Additive manufacturing (AM) through generative design and topology optimisation creates complex, lightweight structures with exceptional material efficiency and structural integrity. When coupled with deep learning functionality, generative design and topology optimisation can explore broader design spaces and optimise more efficiently, creating novel AM structures that utilise material more efficiently and have better strength and performance than their counterparts created through conventional AM methods. The study tackles how deep learning models such as convolutional neural networks (CNNs) can be integrated into generative design and topology optimisation and how these integration help optimise material usage, production time and performance. Case studies from the aerospace, automotive, and healthcare industries exemplify how these synergies resulted in more resilient, cost-effective designs that would not have been possible through conventional AM approaches. The study focuses on material usage efficiency, reduction in production time and performance improvement to showcase how deep learning integrations enhance the process from design conceptualisation, through iterations, to final production.
Research on the Advantages and Challenges of Replacing LEDs with Lasers in Functional Near-Infrared Spectroscopy Systems Based on Advanced Signal Processing Algorithms
Authors: Shang Xiurui
Published: January 2025

Functional near infrared spectroscopy (fNIRS) has received increasing attention as a non-invasive, portable brain hemodynamic monitoring tool due to its potential for use in natural Settings. Traditional fNIRS systems commonly use light-emitting diodes (LEDs) as light sources, which have become the mainstream choice because of their low cost, easy integration, low heat output, and availability of a variety of near-infrared wavelengths. However, LEDs are limited by their low optical output power and broad wavelength range, which restrict their effectiveness in deep tissue penetration and signal quality. In contrast, Laser Diodes (LD) have the advantages of good monochromaticity and high optical output power, which can provide deeper tissue penetration and higher signal stability. Therefore, this study explores the feasibility of using lasers instead of leds in fNIRS systems and their impact on signal quality and imaging depth. By comparing the performance of LED and laser-based fNIRS systems, it is evident that lasers provide significant improvements in signal quality and imaging depth, although they face challenges in terms of cost, thermal management, and safety. The research in this paper provides an important reference for the future design of fNIRS system, especially in the application scenarios requiring high precision imaging.
The Frontier Exploration and Application Prospect of Data Science
Authors: Shao Qiang
Published: January 2025

In the era of information explosion, data floods in like a relentless tide, shaping peoples world every minute and second. Data science, the most prominent discipline of our time, wields unprecedented power to propel the development of industries across the board, serving as a bridge that connects the past with the future, granting insights into the present, and predicting trends. This article delves into the allure of data science, unveiling how it has become the key to unlocking the future world. Furthermore, this review explores in detail the core concepts, key technologies, and broad applications of data science. Through in-depth research on data acquisition, processing, analysis, and visualization, it reveals the innovative applications and significant impacts of data science in multiple fields such as business intelligence, healthcare, and financial technology. At the same time, the future trends and challenges of data science are prospectively analyzed, which provides a valuable reference for further promoting the research and practice in this field.
Integrating AI into Agile Workflows: Opportunities and Challenges
Authors: Jin Ziyao
Published: January 2025

Over the past few years, Agile development approaches have become an increasingly popular methodology for software engineering, focused on iterative progress, continuous feedback, and teamwork cooperation. However, the raising difficulties of projects and more demand for faster and more efficient workflows have challenged the situation further. The introduction of Artificial Intelligence into the Agile processes paves the way to optimize decision-making, automate routine tasks, and boost team productivity. This review summarizes the innovations and challenges created by the integration of AI into Agile development practices. Using AI technologies like machine learning, predictive analysis, and natural language processing, Agile teams can enhance sprint planning, resource coordination, and risk management. Also, it presents some risks such as data privacy, workforce skills need, and possible over-dependence of AI. The paper emphasizes on providing a full overview of the innovations and challenges to the application of AI in Agile workflows, providing thoughts for future research and practices.
A Comprehensive Review of Artificial Intelligence and Machine Learning in Control Theory
Authors: Zhou Haokai
Published: January 2025

Traditional control methods, such as proportional-integral-derivative (PID) controllers and linear-quadratic regulators (LQRs), have proven effective for linear and well-modeled systems. However, these methods often perform poorly in nonlinear, complex and dynamic environments. The paper aims to investigate the modern control systems by integrating artificial intelligence (AI) techniques, such as machine learning (ML), reinforcement learning (RL), deep learning, and fuzzy logic, to enhance their adaptive, robust, and predictive capabilities. And it reviews the literature and analyzes AI integration in control systems. The proposed strategies include supervised learning for trajectory optimization and fault detection, reinforcement learning for optimal control in dynamic environments, neural networks for complex nonlinear function approximation, and fuzzy logic for handling uncertainty and imprecise inputs. AI techniques significantly enhance the ability to tackle nonlinear problems and dynamic changes, demonstrating superior performance in applications like self-driving cars adapting to various road conditions and optimal energy distribution in smart grids. Despite the challenges of computational complexity, scalability, and the safety and reliability in the implementation of interpretable AI models, this paper suggests that hybrid approaches combining traditional control and AI techniques, along with the evolution of interpretable AI and convergence with quantum control, hold great promise for advancing AI-driven control systems.
Research on the Role of Biodiversity in Protecting the Ecosystem Against Climate Change
Authors: Wu Zhonghui
Published: January 2025

As climate change intensifies, its impact on ecosystems has become increasingly severe, threatening the survival of various species and leading to habitat destruction, biodiversity loss, and ecosystem degradation. Biodiversity, encompassing the variety of life on Earth, plays a critical role in maintaining ecosystem stability, buffering against the effects of climate change, and enhancing ecosystem resilience. This study explores the multifaceted role of biodiversity in supporting ecosystem functionality amidst the challenges posed by climate change. By reviewing existing literature and case studies across different ecosystems, this research highlights biodiversity facilitates nutrient cycling and energy flow, which stabilizes the ecosystem, acts as a natural buffer against extreme weather events, and enhances ecosystem resilience by providing functional redundancy. The findings underscore the importance of biodiversity conservation as a strategy to mitigate the adverse effects of climate change and sustain the health and functionality of ecosystems worldwide.
Recent Methods of Effectively Removing Long-chain and Short-chain Per- and Poly-fluoroalkyl Substances from Drinking Water
Authors: Ji Zhiyuan
Published: January 2025

As a persistent organic pollutant, the non-biodegradable per- and poly-fluoroalkyl substances (PFAS) pervade an extensive scope of life, leading to widespread contamination of water resources including drinking water. Correlated with multiple diseases, PFAS is highly correlated with dyslipidemia. While the production of long-chain PFAS is banned, many short-chain PFAS become the alternatives. Although most short-chain alternatives show less hazard, some may possess greater harm. As a result, the removal of PFAS from drinking becomes urgent. This paper reviewed the recent methods of adsorptive removal of PFAS by activated carbon, ion exchange resins, and metal-organic frameworks. The main mechanism and innovative modifications of each adsorptive material are summarized, and both long-chain and short-chain PFAS are discussed in each section. This study aims to provide a basic understanding of the current removal approaches of PFAS for scholars. Through literature review, activated carbon and metal-organic framework remain highly effective with evident mechanisms for adsorbing long-chain PAFS, while ion exchange resins show considerable potential in adsorbing short-chain and ultrashort-chain PFAS.
Comparison of Different Nanomaterials in Anode Materials of Lithium Battery
Authors: Sun Weihao
Published: January 2025

The increasing demand for sustainable energy necessitates the enhancement of lithium-ion battery technology, especially in the advancement of superior anode materials. Contemporary lithium-ion batteries exhibit specific constraints, including comparatively poor energy density and restricted cycle life, which have stimulated growing interest in alternative battery materials with superior performance. This research conducts a literature analysis to investigate the potential of several nanomaterialsgraphene, clay mineral-derived materials, and transition metal sulfidesas improved anode materials for lithium-ion batteries. The study analyzes their characteristics, including energy storage capacity, charging speed, and cycling stability, emphasizing both their benefits and drawbacks. The study concludes that although these materials enhance battery performance considerably, obstacles persist regarding their commercialization and long-term stability. This research provides significant insights into the advancement of more efficient and sustainable lithium-ion battery technology, facilitating the global shift to renewable energy.
Effects of structural design, interface optimization, and processing on the performance of lithium battery anode silicon nanomaterials
Authors: Yu Yicheng , Zheng Yiwen
Published: January 2025

With an emphasis on the advancements in anode material research, this article offers a comprehensive summary of the major technologies used in lithium-ion batteries, a common type of electrochemical energy storage device. Because silicon has both benefits, such as low cost and high theoretical specific capacity, and significant drawbacks, including electrode pulverization and capacity loss due to volume expansion, it is the main focus of this study. This article goes into great detail on the use of silicon material nanosizing to enhance silicon anode performance, discussing how reducing particle size can mitigate the negative effects of volume changes during cycling. However, the section on compositing and structural design processes lacks sufficient depth, which limits the understanding of how these processes can further improve anode stability and efficiency. Furthermore, the article does not comprehensively cover the diverse methods utilized to enhance silicon anode performance, such as the incorporation of conductive additives or protective coatings. The challenges associated with the practical applications of silicon nanoparticles, such as scalability and cost-effectiveness, are examined in detail; nevertheless, the prospects for further research and technological advancements in these areas are not sufficiently addressed. This paper calls for more in-depth studies and innovations in compositing techniques, structural optimization, and practical solutions to realize the full potential of silicon anodes for advanced energy storage.
Development history and application scenario analysis of clock display device
Authors: Luo Dongbao
Published: January 2025

In the fast-paced environment of modern society, clock display systems have transformed from mere timekeeping devices into sophisticated combinations of technology and design, becoming indispensable in everyday life. This article begins by exploring the evolution of clock displays across various historical periods, highlighting the unique characteristics and innovations of each era. From the mechanical clocks of the past, which embodied both precision and craftsmanship, to the rise of seven-segment displays known for their efficiency and reliability, each development marks a significant leap forward. Additionally, the paper delves into the diverse applications of these systems in areas such as consumer electronics, medical devices, and aviation. In these industries, clock displays contribute to increased functionality, user engagement, and safety, often integrating with global time standards. Ultimately, the study emphasizes the growing importance of clock displays in both practical and aesthetic contexts, as they evolve to meet the demands of modern technology and design. This progression signifies not only advancements in timekeeping but also the broader impact of display technology on human experience and industrial innovation.
Application of Scene Perception and Object Detection Technology Based on Computer Vision in Autonomous Driving for Public Transportation Route Optimization
Authors: Chen Peiqi
Published: January 2025

The aim of this article is to discuss the use of computer vision and GIS-based scene perception for autonomous driving in route planning for public transportation. Blending computer vision with GIS information, the design dynamically alters routes based on the environments dynamic variations, such as traffic volume, surface, and obstruction. The system design comprises data acquisition modules, computer vision engine, GIS connectivity, and adaptive route optimization algorithm. Results from virtual cities reveal significant savings in travel time, energy use and flexibility compared to fixed-route approaches. Furthermore, the system works well and offers high detection performance in all kinds of environments. We describe how it might benefit urban transport infrastructure by describing how AVs with real-time vision can optimize routes to speed up time, eliminate delays, and increase safety. Future studies will focus on computing burden and performance under adverse weather conditions, assessing how new technologies like 5G and IoT could provide scalability. This research helps build safer, smarter and more adaptive public transport in cities.
Research of Grasping Strategy of Bionic Manipulator
Authors: Yang Yanxin
Published: January 2025

This article reviews the research progress of bionic manipulator grabbing strategies in recent years, subsequently, the classification of existing bionic manipulator grabbing strategies was sorted out in detail, including crawling strategies based on the principle of biological inspiration, crawling strategies based on mechanical models and crawling strategies based on intelligent algorithms. First, the paper outlines the structural design and control methods of bionic manipulators. Next, the classification and characteristics of existing crawling strategies are summarized. These include strategies based on biological mechanisms, those guided by intelligent optimization algorithms, and data-driven learning methods. On this basis, the advantages and disadvantages of various crawling strategies and their performance in practical applications are compared and analyzed. Finally, the paper discusses the flexibility of bionic manipulator grabbing strategies, challenges and future development trends in adaptability and intelligence. This review not only provides a comprehensive theoretical reference for researchers in the field of bionic manipulator grasping strategies but also identifies key areas for future technological development.
Research on Noise Suppression in High-Speed Optical Communication Systems
Authors: Tian Yuhang
Published: January 2025

With the rapid advancement of optical fiber communication technology, the speed and distance of information transmission have increased unprecedentedly. Multi-core fibers (MCF), which contain multiple cores, enable high-capacity and high-density information transmission. However, during signal transmission, four-wave mixing (FWM) and intercore crosstalk (ICXT) noise are generated, significantly impacting signal propagation quality. Based on the characteristics of FWM and ICXT noise, two effective noise suppression schemes are proposed. The first scheme involves reducing noise power by increasing the wavelength interval or using non-equally spaced wavelengths to mitigate phase-matching conditions. The second scheme focuses on altering the structure of the MCF; in weakly coupled MCFs, longitudinal random bending, torsion, and structural fluctuations randomly affect the power coupling coefficient. According to the noise power formula, reducing the effective fiber length, increasing the cores effective area, and using a band with a low nonlinear effect on the MCF can effectively minimize noise generation. Finally, we evaluate the proposed scheme and analyze and discuss the results.
Comparison and performance optimization of two absolute circuit designs based on Multisim
Authors: Li Haoxiang
Published: January 2025

Digital circuits are crucial in today's technology, underpinning infrastructure such as computing, communicating, and intelligent devices. Its high efficiency, accuracy and programmable capability drive the development of information processing, data transmission and automation systems. The application of digital circuits has promoted innovation in artificial intelligence, the Internet of Things and other fields, providing strong support for the intelligence and interconnection of modern society. The absolute value circuit is discussed in this paper. The absolute value circuit is implemented for converting the negative value of the input signal to a positive value, ensuring that the output signal is always non-negative. Its significance is to handle application scenarios that require non-negative values, such as signal processing, audio amplification, and sensor output. Through the absolute value circuit, negative value can avoid the negative effect on the subsequent circuit, and improve the stability and accuracy of the system. This paper first introduces all the gates used in the circuit, points out the functions of each gate circuit, and then puts forward two absolute value circuit designs, explaining their working principles, differences and advantages and disadvantages. Then the minimum delay is analyzed by the critical path logic and the sizes of each logic gate is given. Then the supply voltage is optimized after selecting the design with the smallest delay to reduce energy consumption.
Analysis and Research on the Intelligent Control System of Comprehensive Traffic Signals
Authors: Wang Jingxuan
Published: January 2025

The existing urban traffic signal control system exhibits certain inefficiencies, including prolonged waiting times and frequent traffic congestion. Research indicates that the integration of neural networks can enhance the effectiveness of intelligent traffic control systems, potentially improving overall traffic flow and reducing delays. Neural network is a highly parallel, nonlinear and highly redundant system. Meanwhile, the self-learning and self-organizing capabilities of neural network have unique advantages for those systems that cannot establish accurate mathematical models. According to the characteristics of complex, variable and random traffic conditions at urban intersections, this paper analyzes the traffic signal control by using neural network control method. This paper introduces a design method of intelligent traffic light based on dynamic time adjustment of traffic flow. By detecting the traffic flow on site, and then allocating the green time of each lane according to the neural network algorithm, the traffic flow dynamic adjustment can be realized, and the traffic capacity of the intersection can be effectively improved. This kind of intelligent control traffic lights can effectively control traffic, and has obvious effects on dreading traffic flow, improving road capacity and reducing traffic accidents.
Systematic Analysis of Sequential Circuits in Digital clock and It Display Mode Comparison
Authors: Liu Zeqi
Published: January 2025

The design idea of the seven-segment digital tube electronic clock and its potential applications against a contemporary backdrop are the main topics of this study. The seven-segment digital clock's low cost and straightforward design make it popular, especially for gadgets with tight budgets. Accurate time reading, adjustment, countdown, and warning functions are achieved through the study and design of a range of digital circuits, demonstrating the broad application potential of digital logic in time control. The circuit's synchronization, stability, and operability are checked using the Multisim simulation tool, guaranteeing the design's dependability in real-world applications. The findings of the study demonstrate the seven-segment digital clock's long-term utility in particular situations, particularly in settings where affordability and durability are crucial. However, the seven-segment digital clock is also under pressure from competitors due to the growing popularity of new display technologies like OLED and smart technology. According to the research, it can continue to be used in particular industries in the future by merging intelligent characteristics to broaden its range of applications.
Carbon Capture and Storage: Critical Analysis of Its Role amidst Net-Zero Pathway
Authors: Cheng Xiaoyi , Deng Jiayi
Published: January 2025

This article will analyze the role of carbon capture and storage technology (CCUS) in achieving a net-zero emissions path. In his article, author Naoko Ellis introduces the development, innovation, problems and challenges of CCUS, and believes that although CCUS technology has high risks and high costs, and may have a negative impact on the progress of renewable energy, CCUS should be taken into consideration when addressing complex climate issues. The article discusses the relationship between CCUS technology and renewable energy, especially its role in the energy system, and points out that CCUS technology is more applicable in heavy industry, such as high-emission industries such as cement and steel. The author also believes that in order to achieve net zero emissions, CCUS technology should be one of many technologies and coexist with other carbon reduction technologies. However, the article also mentioned that the progress of CCUS technology is far below expectations, and its high costs and uncertain risks still need further evaluation.
Numerical analysis of aerodynamic performance characteristics of NACA 2412 and NACA 4412 at Re = 4000000
Authors: Zhang Ruining
Published: January 2025

This paper conducts a numerical analysis of the two-dimensional aerodynamic characteristics of the NACA 2412 and NACA 4412 aerofoils at a Reynolds number of Re = 4106. Employing the fluid simulation software Ansys Fluent, which is based on the finite volume method, for numerical analysis. Both the geometric model and mesh of the aerofoil are established by using Fluent Meshing, and the simulation calculation is performed based on the pressure solver. Based on the Navier-Stokes equations, the SST k- turbulence model and coupled algorithm are employed for the simulation processing. The paper systematically compares the aerodynamic characteristics of NACA 2412 and NACA 4412, including the pressure and velocity distributions, as well as the variations in the lift coefficient, drag coefficient, and lift-to-drag ratio concerning the angle of attack. The results indicate that at Re = 4106, the peak value of the lift-to-drag ratio of the NACA 2412 aerofoil is attained under the 8 condition, for the NACA 4412 aerofoil, the lift-to-drag ratio reaches its peak value at a 6 angle of attack. Additionally, the stall angles of both types of aerofoils under the studied operating conditions are 16.
Comprehensive Analysis on the Modulation and Control Schemes for Modular Multilevel Converters
Authors: Wang Yuyang
Published: January 2025

The energy transition is thoroughly conducted worldwide, with a significant shift from fossil fuels to renewable sources. The most essential benefit of utilizing clean energy is environmental sustainability, which reduces greenhouse gas emissions. The technology of multilevel converters is of great significance for converting high-voltage and large-capacity electric energy and improving power consumption efficiency. Compared with traditional topology, modular multilevel converter (MMC) adopts a modular design, and each module is composed of independent sub-modules, which is highly flexible and scalable. This design allows the number of sub-modules to be increased or reduced according to actual needs, adapting to different voltages and power levels. However, its distinct characteristics, such as submodules, circulating currents, and parameter sensitivity, require a sophisticated control system to manage the external and internal variables with high dynamical performance. This paper analyzes the basic principle and topology of the modular multilevel converter; the existing research protocols are reviewed and summarized for these three challenges, respectively. Finally, prospect the future development trends and technical challenges.
Comparison of aerodynamic characteristics of NACA 2415 and NACA 4415 Aerofoils
Authors: Zhuang Yitong
Published: January 2025

This study compared the two-dimensional aerodynamic characteristics of NACA 2415 and NACA 4415 at different angles of attack. In this study, the Reynolds number is 2.3e6, under which the velocity of the air is 33 m/s. The mesh of C-type is established based on ANSYS Meshing; to simplify the calculation, the chord length is set to 1 m. The fluid simulation is done by ANSYS Fluent, and the simulation calculation is performed based on the pressure solver. The N-S equation is used as the governing equation. Velocity inlet and pressure outlet are set as the boundary condition, and the k-omega SST viscous model is chosen for the simulation processing. This study compares the aerodynamics of NACA 2415 and NACA 4415 at different angles of attack, including the pressure and velocity distribution, lift and drag coefficient, and lift-drag ratio. The results of this research would help optimize wing design and develop new aerofoil and testing.
Injectable Hydrogel-Loaded Rough Heterostructured Nanoparticles for Multi-Procedural Promotion of Diabetic Wound Healing
Authors: Hu Zhihan , Song Jiayi , Xie Mengdi
Published: January 2025

Wound healing is a complex, multifaceted biological process broadly divided into four overlapping phases: hemostasis, inflammation, proliferation, and remodeling. Each stage of wound healing is critical to successfully restoring tissue integrity, and disruption or delay in any of these stages can lead to delayed healing. Various existing nanomaterials only promote a single stage. In this study, Au-CuS nanoparticles (Au-CuS NPs) with rough surfaces were formed by using gold nanorods (Au NRs) as templates on which copper sulfide (CuS) was grown and transported in an injectable hydrogel (Au-CuS@Gel). Au-CuS@Gel can accelerate all stages of diabetic wound healing. The rough surface of Au-CuS@Gel and the injectable property of hydrogel can adhere to close the wound and generate reactive oxygen species (ROS) under near infrared (NIR) light to effectively kill bacteria in diabetic wounds. Meanwhile, the rough morphology effectively polarizes macrophages to M2 phenotype and accelerates collagen deposition. Au-CuS@Gel can be programmed to promote all stages of diabetic wound healing. It provides a new paradigm for the healing of the special wounds represented by diabetes.
Investigation of the microbial community structures and function in subsurface sediments
Authors: Fang Junting
Published: January 2025

In this study, microbial community structures were analyzed in a 5-meter-long sediment core collected from Tennessee, USA, to reveal the diversity and ecological roles of underground microorganisms. Using advanced molecular biology techniques, we classified the microorganisms in the samples and analyzed their distribution in different sedimentary layers. The results show that the microbial communities have obvious stratified distribution characteristics and are closely related to the physical and chemical properties of the sediments. This study improves our understanding of subsurface microbial ecology.
Drought prediction of Henan province in China
Authors: Liu Jiahao
Published: January 2025

Henan province is a key agricultural region in China, influenced strongly by sudden drought. There are relatively few methods to help farmers to make drought projections for the future. The paper tried to use previous monthly SPEI data of time series from 12 stations in Henan from 1978 to 2018 to achieve this purpose. The paper applied Seasonal ARIMA (Autoregressive Integrated Moving Average) to capture patterns of time series and forecast future 5-years value from 2019 to 2024. The terms of models including autoregressive (p), integrated (d), moving average (q) were found based on different tests in order to construct models by removing trends and seasonality of datasets. The final results are ARIMA models of 12 stations in Henan as well as future 5-years predictions of each station. Models effectively capture the main trends and patterns of time-series data; however, some complex patterns and hidden laws still exist in datasets, influencing the accuracy of forecasting. The paper proves Seasonal ARIMA and studying information from past data of SPEI can be useful for preparing drought in Henan. However, the progress in improving the accuracy of forecasting needs to be continued in the future.
Research on Ceramic Nanofiber Assembled Aerogel
Authors: Chen Junyu
Published: January 2025

With the accelerated advancement of science and technology, the traditional textiles material has been unable to meet the specific functional and performance requirements. Meanwhile, the special structure of aerogel exhibits the drawback of limited thermal stability. The high surface energy of the particles makes it susceptible in high-temperature environments, which can lead to a reduction in specific surface area and even collapse of the porous structure. Aerogel assembled from ceramic nanofibers could be a solution. When the fiber size is reduced from micron to nanometer, the special properties brought by the small size effect and the high specific surface area effect will give the nanofibers new properties such as in light, electricity and sound. This paper provides a comprehensive general introduction of the structure, capability, preparation, and modification techniques employed in ceramic nanofiber aerogel research. The sol-gel electrospinning method can produce nanofiber aerogel with excellent properties. The paper reveals the excellent thermal insulation properties of ceramic grains that is located on ceramic fibers such as ZrO2, SiO2 and Al2O3, combined with the porous structure of aerogel can lock gas molecules, so that they can be used in high temperature environments.
Sensory Signal Processing and Brain Imaging: From the 3D to 2D Neural Representation
Authors: Zheng Yuying
Published: January 2025

The sensory system is extremely important to humans, allowing them to interact with their surroundings. The sensory system functions by converting external stimuli into neural signals, which subsequently undergo processing to generate coherent perceptions. Three-dimensional spatial and temporal information needs to be transformed into two-dimensional neural representations, and this transformation is the basis for understanding perception, as well as cognition and action. This review covers a number of discussions, including mechanisms of sensory coding in visual modalities, neural transmission in auditory modalities, and cortical representation in tactile modalities. Interactions between sensory systems, between multisensory integration, and between neuroplasticity will also be examined. In addition, challenges and future directions will be discussed to stimulate further research on sensory processing and its applications in neural engineering.
The Impact of AI Development on Fertility Rate
Authors: Li Yunshu
Published: January 2025

Fertility treatments are set to change with the help of AI technology, which is now known to optimize fertility treatments. Evidence shows that AIs cutting-edge technologies can help eliminate infertility issues through an optimized treatment of genetic disorders and optimized embryo selections. At the same time, the need to address infertility issues has been considered a global health problem, which is indicated by the decline in global fertility rates. These fertility rates are posing a major crisis in the future in the nation that is currently dealing with an aging population and major declines. The data collection showed that there was a higher number of ART births that were directly influenced by AI-enhanced fertility technologies. The success rates, as well as the rates of failed fertilization show whether AI technologies have a positive or negative impact on fertility rates and whether they should be considered the game changer in a city and a nation where fertility rates have been declining since the early 2000s. A scoping review of the literature provided an overview of the ways in which fertility clinics are now using AI technology to enhance the chance of success for their patients.
Re-reading of the Discrimination and Rejection of Arabs in Albert's Camus’ The Stranger through Kamel Daoud’s The Meursault Investigation
Authors: A Sangeeth Kumar , Hoque Mohammed Shamsul , Venkateswara U. , Paramaguru E. , Chokkalingam Vinoth Kumar , V.L Jayapaul , Shruthi R. , A Thenmozhi
Published: January 2025

Algerian postcolonial literature has emerged as a powerful tool for contesting and reshaping the prevailing colonial narrative. This study delves into colonial power dynamics in Algeria by juxtaposing Albert Camus's The Stranger (1942) with Kamel Daoud’s The Meursault Investigation (2013), where Daoud’s novel functions as a counter-narrative to Camus’s work. It delves into the previously unexplored perspectives of characters presented in The Meursault Investigation. Haroun, the protagonist, sets out on a journey to change things in order to recover the name and identity of the "Arab." in The Stranger. Firstly, it depicted Algerian historical memory and national identity, particularly as it relates to French colonial rule in Algeria.The research employes contrapuntal reading, the way of portraying imperialism and resistance by stating Meursault as imperialist and Haroun as resistance.Through a postcolonial perspective, the study contends that Daoud reinterprets the murder's significance in The Stranger by emphasizing its historical context The research pointed out women’s status in both stories For Instance, Marie undergone sexual oppression by Meursault Whereas Meriem respected by Harun. This study looks into how Daoud was able to break down and rethink Camus' dominant colonial writing by comparing and contrasting Camus' The Stranger with Daoud's The Meursault Investigation. Daoud uses the language of the colonizers in a clever way to bring back to life the legacy and identity of the Arab Algerians, whom imperialist French colonizers erased. The study employs the 'mirror image' which is  a reversed reflection used to highlight contrasts or similarities, often to compare different perspectives or emphasize opposing themes, concept to offer a nuanced analysis of the contrasting colonial and postcolonial dynamics.
ПОВЫШЕНИЕ ЭФФЕКТИВНОСТИ БАНКОВСКИХ ОПЕРАЦИЙ ЗА СЧЕТ АВТОМАТИЗАЦИИ: ПОДХОД К МОДЕЛИРОВАНИЮ
Authors: Артык Н.Е. , Сембина Г.К.
Published: January 2025

Автоматизация бизнес-процессов стала ключевым фактором в непрерывном развитии банковской отрасли. Данное исследование посвящено всестороннему анализу влияния автоматизации на эффективность и конкурентоспособность банков в современной динамичной финансовой среде. В статье исследуются основные тенденции в автоматизации бизнес-процессов в банковском секторе и приводится углубленный анализ успешных практических примеров, свидетельствующих об эффективном внедрении автоматизированных систем. Особое внимание уделяется тому, как автоматизация повышает качество обслуживания клиентов, приводит к значительному снижению операционных расходов и повышает эффективность процессов принятия решений. Кроме того, в исследовании оцениваются потенциальные риски, связанные с автоматизацией, и предлагаются стратегические рекомендации, направленные на минимизацию этих рисков. Результаты, представленные в этом исследовании, имеют неоценимое значение для банковских менеджеров, разработчиков программного обеспечения и регуляторов финансового рынка, помогая им принимать обоснованные решения относительно автоматизации бизнес-процессов в своих организациях.
МЕТОДИКА ЭКСПРЕСС-АНАЛИЗА ЦЕННОСТИ ПРОЕКТА
Authors: Олех Т.М. , Олех Г.С.
Published: January 2025

В статье представлена методология экспресс-анализа стоимости проекта, сфокусированная на предварительной оценке осуществимости и эффективности инвестиций. В ней рассматриваются экспертные оценки сложных параметров, выраженных в виде интервальных значений на числовых шкалах. Анализируются два подхода: среднее арифметическое и взвешенное усреднение границ интервалов. Предлагаемый взвешенный метод придает большее значение более узким интервалам, предполагая, что они представляют более высокую экспертность, тем самым повышая точность и качество согласованных оценок. Расчеты и визуальные данные демонстрируют преимущества взвешенного усреднения, включая уменьшенную ширину интервала и более точные результа-ты. Метод также смещает центр интервала в сторону более узких диапазонов, что отражает большую надежность экспертных оценок. Результаты подчеркивают важность использова-ния интервальных оценок и взвешенного усреднения в экспресс-анализе, предлагая более совершенный подход к оценке проекта. Эта методология улучшает принятие решений, пре-доставляя надежную, экспертно-информированную основу для оценки осуществимости проекта и инвестиционного потенциала на начальной стадии оценки.
СБОР ДАННЫХ И ПРИМЕНЕНИЕ МОДЕЛЕЙ НЕЙРОННЫХ СЕТЕЙ ДЛЯ КЛАССИФИКАЦИИ ЯЗЫКА ЖЕСТОВ В ЗАДАЧАХ РАСПОЗНАВАНИЯ ОБРАЗОВ
Authors: Муханов С.Б. , Абдул А.Р. , Бекаулова Ж.М. , Жакыпбеков С.Ж.
Published: January 2025

В данной работе рассматривается сбор данных и применение моделей нейронных сетей для классификации языка жестов в задачах распознавания образов. Язык жестов, как важный способ коммуникации для людей с нарушениями слуха, требует эффективных технологий для его автоматического распознавания. В ходе исследования был проведён сбор разнообразных видеоданных, охватывающих различные жесты и контексты их использования. Для анализа этих данных применялись современные архитектуры нейронных сетей, включая сверточные и рекуррентные сети, что позволило достичь высокой точности классификации. Результаты показывают перспективность использования глубокого обучения для распознавания языка жестов, что открывает новые возможности для разработки вспомогательных технологий и улучшения качества жизни людей с ограниченными возможностями. Работа подчеркивает важность интеграции методов машинного обучения и компьютерного зрения для создания более интуитивно понятных интерфейсов взаимодействия.
Discharge Disposition after Total Hip Arthroplasty: A 10-Year Analysis of Trends and Predictors of Nonhome Discharge (2011-2021)
Authors: Pasqualini Ignacio , Pan Xuankang , Xu James , Austin Chiu , Ibaseta Alvaro , Khan Shujaa T. , Corces Arturo , Higuera Carlos A. , Piuzzi Nicolas S.
Published: January 2025

Background:

Total hip arthroplasty (THA) practices are evolving under the influence of the current value-based healthcare system and bundled payment models. This study aimed to (1) evaluate national trends in discharge disposition and postoperative outcomes after THA, (2) compare discharge cohorts on episode-of-care parameters, and (3) determine predictors of nonhome discharge from 2011 to 2021.

Methods:

The National Surgical Quality Improvement Program database was queried for THA data from 2011 to 2021. A total of 328,380 patients undergoing THA were identified between 2011 and 2021. Of these patients, 276,710 were discharged home and 51,670 were discharged to nonhome locations. Trends of annual discharge disposition, healthcare utilization parameters, and proxies for postoperative complications were reported. A multivariable logistic regression analysis was conducted to identify potential risk factors for nonhome discharge.

Results:

The percentage of patients who were discharged to home increased from 70.20% in 2011 to 92.42% in 2021. In those discharged to home, 30-day readmission rates, 30-day major complication rates, length of stay, any wound complications, and need for transfusion all decreased within the past decade. The percentage of patients who were discharged to nonhome locations decreased from 29.80% in 2011 to 7.58% in 2021. In this group, major complication rates within 30 days, length of stay, and need for mechanical ventilation increased from 2011 to 2021. Greater age, female sex, body mass index of <18.5, race, smoking, higher comorbidity burden, and functional status were associated with greater odds ratios of nonhome discharge.

Conclusion:

Home discharge after THA has increased substantially over the past decade, with more than 90% of patients now being discharged home. However, a small subset of higher-risk patients still requires nonhome discharge and experience worse outcomes. Focused efforts based on known discharge risk factors may allow implementing perioperative optimization strategies to further improve outcomes in this population.