Science and Technology of Engineering, Chemistry and Environmental Protection
ISSN 2959-6157 (Print) ISSN 2960-1339 (Online) Editor-in-chief: Vinod A. Thale （Zhejiang University） Associate Editor: Syed Murawat Abbas Naqvi （Beijing Institute of Technology） Editorial Board Member: Faisal Rafique （Southern University of Science and Technology） Jian Hu （University of Kent） The Journal of Science and Technology of Engineering, Chemistry and Environmental Protection (JSTECEP) is a multidisciplinary, peer-reviewed academic publication dedicated to fostering the next generation of scientific leaders. By providing a professional platform for college students, young researchers, and early-career innovators, JSTECEP bridges the gap between classroom learning and professional academic publishing. Our mission is to democratize the exchange of scientific knowledge. We aim to support emerging scholars by providing a rigorous yet constructive peer-review process that highlights original research, innovative technical solutions, and sustainable developmental practices. Scope of Subjects The journal welcomes submissions that explore the intersections of theory and application across three primary pillars: Engineering: Advancements in mechanical, civil, electrical, and chemical systems, with an emphasis on modern technological integration. Chemistry: Research spanning organic, inorganic, and analytical chemistry, as well as biochemistry and material sciences. Environmental Protection: Innovative approaches to sustainability, climate mitigation, pollution control, and the preservation of natural resources. Why Publish With Us? Support for Emerging Voices: We prioritize high-quality work from students and young professionals who are often underrepresented in legacy journals. Rigorous Peer Review: Every article undergoes a thorough evaluation to ensure technical accuracy and academic integrity. Interdisciplinary Reach: Our broad scope encourages authors to submit work that solves complex, real-world problems involving multiple scientific disciplines. Commitment to Innovation: We celebrate "outside-the-box" thinking and technical creativity that addresses the environmental and industrial challenges of the 21st century. All articles will be submitted to: Google Scholar, Crossref, U.S. Librarian Database, ProQuest (part of Clarivate’s Web of Science), Ulrich's Periodicals Directory, SEMANTIC SCHOLAR, OpenAlex.
Research on Three-dimensional Reconstruction
Nowadays, with the continuous development of the field of computer vision and computer graphics, 3D reconstruction technology has become an area that has attracted much of people’s attention. 3D reconstruction refers to creating a 3D model of an object in the real world by extracting information from multiple 2D images or sensor data. This technology has important usages in many fields, including virtual reality, augmented reality, cultural heritage preservation, medical image processing, industrial design, etc. This thesis examines the application of 3D reconstruction in various fields, discusses the definition of development history, its wide application in life, and its advantages and disadvantages. This article is divided into four parts and discusses the algorithm research of 3D reconstruction in four fields. Through an in-depth study of 3D reconstruction technology, we can better understand its role in different fields and provide strong support for developing and innovating related applications. As more accurate devices and algorithms continue to advance, 3D reconstruction technology is expected to show its significant potential in more and more fields and create more realistic and useful digital experiences for us.
Copyright (c) 2025 Science and Technology of Engineering, Chemistry and Environmental Protection
Prospects for silicon being replaced by other materials in integrated circuit applications
Currently, silicon is the most widely used semiconductor material. However, in recent years, the development of integrated circuits has encountered more and more limitations, among which the physical characteristics of single-crystal silicon materials are an important reason. With the expansion of integrated circuit scale and the continuous reduction of manufacturing processes, silicon has gradually reached its physical limit. At the same time, silicon has a higher calorific value and a higher performance loss. Therefore, people are actively seeking alternatives to silicon in integrated circuits. This paper reviews the characteristics of three new semiconductor materials, graphene, silicon carbide, gallium nitride, and current research on their applications. Silicon carbide and gallium nitride materials have shown outstanding performance in power-integrated circuits, while graphene has many applications. However, they still have many defects before being used on a large scale. In short, in integrated circuit applications, when new materials replace silicon, many problems remain to be solved.
In recent years, with the development of the semiconductor industry, Moore’s Law has gradually become ineffective, making it increasingly difficult for people to improve chip manufacturing processes. Many people believe that Moore’s Law will no longer exist. However, with Samsung announcing the production of 3-nanometer gate-all-around (GAA) architecture process technology chips on June 30, 2022, the chip process has been further advanced. Moore’s Law is expected to continue in the coming years. This article will mainly introduce why GAAFET will become the mainstream field-effect transistor in the future. The potential problems that GAAFET may encounter in its future development will also be analyzed, including massive research and development costs and a longer research and development cycle.
Comparison of Degradation Differences in Typical Urban Wastewater Dissolved Organic Matter
Dissolved organic matter (DOM) is a class of organic mixtures commonly found in natural water bodies with complex structures and diverse sources, which are closely related to the structure and function of the water body environment. Given the declining quality and quantity of lake waters in China, studying the dynamic degradation/change processes of DOM in lakes is essential to understand and manage the ecological health of these water bodies. In this experiment, by conducting photocatalytic experiments of DOM, we analyzed and compared the changes of absorbance and DOC concentration of different kinds of urban wastewater water samples with time, and the results showed that the degradation efficiencies of DOC were in the order of domestic wastewater>farming wastewater>industrial wastewater from the largest to the smallest, and the degradation efficiencies of the light-absorbable substances at the wavelength of 254 nm were farming wastewater>industrial wastewater>domestic wastewater. This study not only explored the photo-degradation process of DOM in urban wastewater, but also provided a scientific basis for wastewater treatment and management, with a view to optimizing the wastewater treatment process, improving the level of water quality management and reducing the impact of harmful pollutants on the environment.
Copyright (c) 2026 Science and Technology of Engineering, Chemistry and Environmental Protection
Effects of Water and Nitrogen on Ecophysiological Characteristics of Two Dominant Grassland Species on the Semiarid Loess Plateau
To investigate the eco-physiological traits in response to water and nitrogen supplying conditions of native species is of importance for understanding their eco-adaptation to the local environment, and also finding rational agronomy measures for using them in artificial grassland construction. In this study, using Bothriochloa ischaemum (C4 grass) and Lespedeza davurica (C3 legume) as research materials, a pot experiment was conducted to compare the leaf photosynthetic traits, leaf fluorescence parameter characteristics and leaf relative water content of the two dominant native species under three different soil moisture conditions (80%FC, 60%FC and 40%FC) and two nitrogen supplying (0 g N kg-1 and 0.025 g N kg-1) conditions when sown individually or in mixture. Results showed that as soil water content decreased from 80% FC (field capacity) to 40% FC, leaf net photosynthetic rate (Pn), transpiration rate (Tr), intercellular CO2 concentration (Ci), and stomatal conductance (Gs) of monocultured plants showed an increasing trend, while the photosynthetic parameters of mixculture plants generally exhibited a decreasing trend. The Pn values of L. davurica were significantly higher than those of B. ischaemum (P<0.05), and the maximum value was 12.50 mmol m-2 s-1. As soil water content decreased, the initial fluorescence values (Fo), maximum potential quantum yield of PSII (Fv/Fo), and maximum photochemical efficiency (Fv/Fm) values under no nitrogen treatment showed no significant change (P>0.05). Overall, the data indicated that when B. ischaemum and L. davurica were mixcultured, there existed a significant mutualistic effect under low soil water situation, indicating mixculture of B. ischaemum and L. davurica was beneficial for coping with drought in the semiarid region.
The Breakthrough Path of Chemical Industry Practitioners under the Vision of “Carbon Neutrality”
Carbon neutrality is an unstoppable trend. In the context of increasingly stringent policy constraints, pushing regulatory rigidity to its limits, “chemists” face severe challenges in both survival and transformation. How to respond to these changes and achieve a breakthrough is the mission and responsibility of “chemists.” This article delves into the internal mechanisms of carbon neutrality, exploring the contributions and feasible paths for chemists within this vision. By enhancing management through park circularity and technological innovation through process intensification, chemists can achieve a victorious breakthrough under the carbon neutrality vision.
The low-carbon development path of China’s animal husbandry industry
To address global warming, China has committed to achieving carbon neutrality by 2060. As a major source of carbon emissions in China, it is necessary to implement carbon reduction measures in animal husbandry. This paper mainly explores the mainstream low-carbon development measures for animal husbandry from three aspects: production, processing, and transportation. At the same time, suggestions have been put forward for the green and low-carbon development of animal husbandry in the future, which can provide reference for research on low-carbon development of animal husbandry.
Comparison of the differences in photochemical degradation of dissolved organic matter in rivers, lakes, and ponds by adding nanoparticles TiO2.
This study examines the photolysis of Dissolved Organic Matter (DOM) in urban rivers, lakes, and ponds using photocatalysis experiments. Employing a photochemical reactor and UV spectrophotometer, we investigated the precise effects of TiO2 nanoparticles and illumination duration on the degradation efficiency, rate, and kinetics in water bodies. Simultaneously, an analysis was conducted on the photochemical degradation process of DOM from various sources. The results demonstrate that the photocatalyst TiO2 can effectively improve DOM degradation and light absorption degradation efficiency, with longer illumination durations inversely correlating with DOM content. Both Dissolved Organic Carbon (DOC) and 254 nm absorbance degradation kinetics follow pseudo-first-order degradation kinetics. Notably, the pond exhibited the most significant change in degradation efficiency, reaching 96.7%. Our findings suggest that degradation efficiency in water bodies may be influenced by surrounding vegetation, population density, and rainfall conditions. This study contributes to a deeper understanding of DOM degradation processes by photocatalysts and provides a feasible method to effectively mitigate water pollution.
Research on Diffraction Patterns of Smartphone Screens
Smartphone screen is composed of pixels which are not of uniform size and arranged evenly. When illuminated by a laser, the reflected beam diffracts, producing a diffraction pattern with structure of mesh shape that exhibits characteristics similar to a two-dimensional reflection grating. In this paper, the general diffraction formula of a two-dimensional non-uniform grating is derived, while a simplified form in a special case is explored. The influence of laser incidence angle on the diffraction pattern is analyzed. The diffraction patterns by formula calculation and Fourier transform are obtained using MATLAB simulation. The rationality of the derived formula is verified through simulation and experiments. Also, the pixel density of the smartphone screen is calculated based on the diffraction pattern obtained from the experiment. The application scenarios of the research results are proposed. Comparing the discrepancy in diffraction patterns of different types of screens whose arrangements of sub pixels in smartphones are also different, the mechanism of grating diffraction is displayed directly. Theoretical calculations, simulations and experiments are applied for comparing and confirming each other.
Electronegativity Impact on metal (Copper, Iron, Zinc) Lewis acid catalysts in the Biginelli Reaction: A Comparative Study
The Biginelli reaction is a very practical multi-component reaction, and the products 3,4-Dihydropyrimidine-2(1H)- ones (DHPMs) play an important role in the pharmacy scope. Herein, CuCl2, FeCl3, and ZnCl2 were used to investigate the catalytic activity differences among these metal Lewis acid catalysts for the Biginelli reaction under controlled conditions. Based on reaction mechanism, we believe that highly electronegative metals are beneficial for activating imines and enol intermediates, thereby increasing reaction yields.
Overview of Red Tide Disasters in the Coastal Waters off Qinhuangdao
As an important fishery and tourism resource city in northern China, Qinhuangdao has experienced frequent red tide disasters in recent years, which has had a serious impact on the marine ecological environment and human life. This paper first analyzes the characteristics, causes, and influencing factors of red tide disasters in Qinhuangdao waters then summarizes the existing coping strategies for red tide disasters and finally puts forward the coping strategies for red tide disasters in Qinhuangdao waters.
Differential comparison of degradation efficiencies in urban environmental waters and effluents and with and without nanoparticles
DOM is an important component of water bodies and provides unimaginable vitality to the entire water body. This paper employed a filter configuration method to extract dissolved organic matter and sewage. In the control group, nanoparticles are added to set up a control group. The degradation efficiency of urban water bodies and sewage and their degradation efficiency in the presence or absence of nanoparticles was compared using a UV spectrophotometer and a photochemical reaction meter. By analyzing the degradation efficiency of DOC, we observed that the degradation efficiency of urban water is much higher than that of wastewater, and nanoparticles can increase the reaction rate. This effect is particularly pronounced in pond water, which can provide a reference for the standard of wastewater discharge and urban water management.
The Cognitive Benefits of Virtual Reality Technology in Anatomy learning
As an innovative educational tool, virtual reality technology is gradually gaining traction in the field of medical education. This paper aims to delve into the cognitive advantages of virtual reality technology in anatomy learning. Initially, it provides an overview of development history and current status of virtual reality technology application in education. It systematically analyzes the limitations of traditional anatomy learning and the cognitive requirements for effective learning. Subsequently, building upon the exploration of the application and integration methods of virtual reality technology in anatomy learning, such as virtual anatomy laboratories and software, this paper elaborates on the cognitive advantages of virtual reality technology in anatomy learning. It discusses how virtual reality enhances spatial perception and three-dimensional comprehension, boosts student participation and interactivity, and deepens emotional engagement and memory retention. The effects and significance in practical application are further illustrated through typical case studies of virtual reality technology implementation in anatomy education both domestically and internationally. However, challenges persist in the application of virtual reality technology, including technical limitations and teaching practice difficulties. Through the research presented in this thesis, a better understanding of the role of virtual reality technology in anatomy learning can be attained, offering valuable insights for the improvement and innovation of medical education.
Comparative Study of Colloidal Particles on Organic Matter Degradation in Environmental Water and Typical Urban Sewage
Water, as a critical natural resource in urban areas, faces severe pollution due to human production and living activities. Previous studies have shown that dissolved organic matter (DOM) significantly affects water quality. To deepen our understanding of the impact of colloidal particles on DOM, we conducted a comparative study on organic matter degradation by colloidal particles in environmental water and typical urban sewage. The experiments revealed that colloidal particles accelerate the photodegradation of DOM in all six experimental water bodies. This research is pivotal for solving the challenges of water pollution confronting society.
In recent years, the fusion of advanced technologies with virtual reality has opened new cultural preservation and engagement avenues. This dissertation explores the innovative application of Neural Radiance Fields (NeRF) technology in transcending the boundaries of physical museums and transporting their treasures into the metaverse. While classical computer vision has seen substantial progress, a developing intersection exists between NeRF and cultural heritage preservation. This study bridges this gap by introducing an approach that amalgamates NeRF techniques with the rich cultural wealth of museums. The conventional museum experience is extended into the metaverse through a novel methodology that leverages NeRF’s capabilities. The core objective is to enable individuals to explore digitized museum artifacts with unparalleled realism. NeRF technology captures intricate visual details and enables immersive interactions by rendering scenes with volumetric precision, transforming how cultural artifacts are experienced and understood. This dissertation delves into the technical intricacies of integrating NeRF technology into the metaverse. The implementation involves the reconstruction of 3D artifact models. The results underscore the potential of NeRF to reshape the cultural heritage landscape by bridging the gap between traditional museums and the boundless possibilities of the metaverse.
An investigation into the sound insulation performance of common construction materials in urban environments
This study investigates the sound insulation performance of common construction materials in urban environments and explores the physical properties that influence this performance. Relevant literature on noise pollution and construction materials was reviewed, and a questionnaire was designed and distributed to examine public attitudes towards noise pollution and perceptions of the insulation performance of common materials. In addition, an experiment was conducted to compare the sound insulation performance of four materials—wood panel, concrete, foam board, and plastic-by measuring their sound attenuation under controlled conditions. The results indicate that noise pollution has a noticeable negative impact on people’s daily lives. Among the materials tested, wood panel and concrete showed stronger sound insulation performance than foam board and plastic. The findings further suggest that density, hardness, and structural strength are important factors influencing sound insulation. Overall, the study highlights the practical importance of selecting suitable construction materials for reducing urban noise exposure and suggests that future research should explore composite materials that combine multiple beneficial physical properties.
Finding the Stable Point of Game: A Quick Solution to Nash Equilibrium
This essay will focus on the efficient solution of Nash Equilibrium and the analysis of strategies’ stability, aiming to provide completely information static games with a systematic and efficient framework for solving Nash Equilibrium and a risk assessment method. Traditional game theory models rely on the assumption of complete rationality and the its solution process is quite complex. During the real time application, there might be some challenges. The “fast solution method” processed in this essay simplifies the complex process through two-step procedure: First, apply line-drawing method to efficiently recognise the pure strategy Nash Equilibrium. If none exists, establish an equation based “Indifference Principle”. This method not only locates the stable state of the game, but also establishes a complete evaluation system from deterministic payoff to probabilistic risks through the analysis of “optimal response”, revealing the potential benefits and inherent risks of strategies. To further verify the effectiveness and explanatory power of the method, this essay simulates the example of Gomoku Game with the opposing styles of “aggressive vs conservative”. This research provides a rapid solution path for Nash equilibrium from a methodological perspective and deepens the understanding of strategy interaction, risk trade-offs, and the convergence process of equilibrium through case simulation in practical applications, which has reference value for the application of game theory in teaching, analysis, and strategy formulation.
risk and payoff evaluation interative optimization
Research on System-level Design Challenges and Solutions for 3D Chiplet Integration
With the slowdown of Moore’s Law and the exponential increase in the cost of advanced manufacturing processes, heterogeneous integration technology based on chiplets has become the key path for the continuation of the development of the integrated circuit industry. This technology achieves an optimal balance of system performance, cost and flexibility by densely stacking chip wafers of different process nodes and functions in a threedimensional space. However, from the perspective of system-level design, three-dimensional chiplet integration brings unprecedented challenges in aspects such as architecture partitioning, interconnection standards, physical integration, and design methodologies. This article systematically reviews the core challenges in the design process of three-dimensional chiplet systems, discusses the solutions from system architecture exploration to physical implementation, and looks forward to the future design automation tools and collaborative optimization methods for the chiplet ecosystem.
Application of Multimodal AI in CS:GO Match Analysis: From Data Parsing to Strategy Recommendation
The application of multimodal AI in analyzing Counter-Strike: Global Offensive (CS:GO) matches represents an emerging intersection of computer vision, natural language processing, time-series modeling, and reinforcement learning within esports analytics. This paper proposes a comprehensive multimodal framework that integrates heterogeneous data sources - gameplay videos, voice communications, and structured statistics - to achieve efficient parsing, feature fusion, tactical pattern recognition, and intelligent strategy recommendation. By fusing multiple modalities, the system aims to automate and optimize tactical decision-making for professional teams, significantly improving the efficiency and accuracy of traditional manual analysis.
Designing card holders using Faraday cage principles to block hacking and protect data from theft.
With the growing use of contactless payment methods, such as credit cards that allow users to make payments by simply swiping, security concerns have increased. One of the major issues is “card-not-present fraud,” where criminals use NFC readers to steal money without the cardholder’s knowledge. Since victims often do not realize the fraud until they check their transaction records, improving protective measures is essential. While many studies have explored payment security, few have considered the connection between Faraday Cage technology and cardholder protection. Our research integrates the Faraday Cage principles into card bag design to reduce the risk of data theft and unauthorized transactions. Two distinct experiments are demonstrated in this paper, which are using a specific electromagnetic wave transmitter and receiver to calculate the shielding effectiveness of Faraday Cages with various materials, and using pings received to display the relationship between sizes of mesh holes of the cage and their shielding effectiveness. This paper provides several dimensions for the producers of card bags to optimize the design of card bags based on Faraday Cage.
The Evolution and Challenges of Materials in Ancient Book Restoration: Which is More Important for Long-Term Preservation of Documents, Traditional or Modern Restoration Materials?
The restoration of ancient books plays a very important part of the preservation of cultural heritage. The main idea of it is to preserve historical authenticity, Long material life and cultural continuity. This article arranges the development of restoration materials of ancient books, mainly discussing the applications and evaluations of traditional and modern materials. Traditional materials like Chinese traditional paper, Japanese traditional paper, fish glue and starch paste. These materials have high reversibility, good compatibility, and culture consistency, so they have been used in preserving the original appearance of books and carrying the craft tradition for centuries. With the development of scientific technology, modern materials such as synthetic paper, acid-free paper, polymer adhesives, nanomaterials, and fiber-reinforced composites have gradually emerged. These materials are better at improving the stability of the structure and durability. This article will analyse the pros and cons of both traditional and modern materials across multiple dimensions, encompassing performance comparison, applicable scenarios, and ethical considerations, among others. Combining some real examples, this article will emphasize that choosing proper restoration materials should depend on some factors like the materials of the books, the aim of the restoration and the damage level. This article aim to provide an overall theoretical support and practical approach for culture heritage conservators. Also helps to promote the preservation work to me scientific, systematic and sustainable. This study proposes a “reversible base + local high-strength reinforcement” layered conservation strategy, emphasizing that material selection should be based on the document’s condition and preservation goals, balancing structural durability with cultural authenticity under ethical restoration principles.
Research on Multi-Robot Collaboration Methods under Unstructured Environments
Recent technological development has made multirobot collaboration a promising approach for tasks in unstructured and dynamically changeable environments. However, challenges still occur especially in reliability, efficiency and system integration. This review systematically examines former research and experiments, with focus on robust perception, collaborative planning and hybrid architectures. It poses that there requires advancement in communication-control co-design, lightweight collaboration models, and standardized tests. The study concludes that future progress should depend on adaptable and cost-effective systems capable of establishing positive human-robot relationship, which requires combination of robotics, AI and edge computing.
The comparison between the WBG semiconductors
Silicon carbide (SiC) MOSFETs and gallium nitride (GaN) HEMTs, as representative wide-bandgap (WBG) power devices, are accelerating the shift beyond conventional silicon technology by enabling higher efficiency, higher power density, and operation at elevated switching frequencies. This paper provides a comparative assessment of SiC MOSFETs and GaN HEMTs using a set of core performance metrics that are most relevant to practical converter design, including thermal robustness, shortcircuit tolerance, switching speed, and the resulting implications for efficiency and reliability. Drawing on published research and experimental reports from 2022– 2024, the study shows that SiC MOSFETs offer clear advantages in high-temperature stability and short-circuit ruggedness, making them a strong candidate for harsh, high-power operating conditions. In contrast, GaN HEMTs demonstrate superior high-frequency switching capability, supporting compact passive components and high-density converter layouts, but they typically encounter greater reliability challenges under severe electrical and thermal stress. Therefore, device selection should be driven by application requirements: SiC is generally preferable for high-power, high-temperature, and reliability-critical systems, whereas GaN is more suitable for high-frequency, compact, and fast-dynamics power conversion.
Garbage Classification Based on ShuffleNet and Edge Detection Preprocessing
With the rapid urbanization, the problem of municipal solid waste has become increasingly severe, and waste classification has become a key measure to achieve sustainable development. However, traditional manual sorting is inefficient and expensive, and the existing automatic identification methods based on deep learning have different limitations. In order to solve these problems, this paper proposes a waste classification scheme that combines Canny edge detection pretreatment with the lightweight ShuffleNet v2 network. First, denoise the image, and then use Canny edge detection to extract the waste profile to enhance the target characteristics and suppress background interference. Finally, enter the processed images into the ShuffleNet v2 network for classification. Experiments conducted on the kitchen garbage subset of Huawei’s garbage classification data set show that the proposed method achieves superior overall performance than SSD, YOLOv3 and unprocessed ShuffleNet v2. While maintaining the advantages of lightweight architecture, the method significantly improves the identification accuracy, thus expanding the technical path of garbage classification and accelerating its intelligent development.
Visible Light Transmittance Optimization of a Multi-Layer Glass Structure Based on the Fish Swarm Algorithm
This paper proposes a three-layer glass thickness optimization method based on the fish swarm algorithm to address the problem of high air conditioning cooling load caused by solar radiation in southern summer buildings, to minimize solar transmission energy in the 300-2000nm wavelength range. Firstly, a transmittance model is constructed based on the optical properties of glass, and a method for calculating the total transmittance energy is derived. Secondly, with the thickness of the three-layer glass (L1, L2, L3) as the optimization variable, a fish swarm algorithm is used to design the optimization process. The experimental results show that the fish swarm algorithm converges around the 80th generation, and the optimized three-layer glass thickness combination is L1=8.61mm, L2=3.64mm, L3=4.88mm. The total transmitted energy (relative value) decreased from the initial 1330.5 to 1325.7962, with a decrease of approximately 3.3%. The optimized transmittance in the visible light band (450-750nm) is 0.7755, and the transmittance in the near-infrared band (750-2000nm) is 0.7795, both significantly lower than the pre-optimization level. This method effectively improves the thermal insulation performance of glass through collaborative optimization of thickness parameters, providing a quantitative solution for building energy-saving design.
Attention-Centric YOLOv12 for Real-Time Fine-Grained Waste Detection in the TACO Dataset
Efficient waste detection is crucial for environmental sustainability, yet existing models struggle with finegrained objects in complex backgrounds, such as those in the TACO dataset. This paper proposes an attention-centric approach using YOLOv12n to balance detection accuracy and real-time performance. Experimental results on the TACO dataset demonstrate that the proposed YOLOv12n achieves a mean Average Precision (mAP50 ) of 0.376 with an end-to-end inference speed of 94.33 FPS on an NVIDIA RTX 5060 GPU. Ablation studies reveal that removing the Area-Attention ( A2 ) module leads to a significant performance drop, with mAP50 plummeting from 0.376 to 0.148. Furthermore, compared to the YOLOv8n model with a plug-in CBAM module (46.18 FPS, 0.310 mAP), the native attention-centric architecture of YOLOv12n provides a significant increase in inference speed and superior feature localization. This research confirms that a native attention-based design is more effective for realtime fine-grained waste detection than traditional modular additions.
Exploration of the method for extracting caffeine from tea
Caffeine is a widely consumed alkaloid with considerable relevance in both the food and pharmaceutical sectors, where efficient extraction methods are of great practical importance[1-5]. Among the various techniques available, the conventional Soxhlet extraction method is commonly used due to its straightforward operation, although there remains potential to improve its yield[7]. This study set out to explore strategies for enhancing caffeine yield from tea leaves by refining key parameters within the Soxhlet extraction process. The investigation examined the influence of several variables—such as extraction temperature, siphon cycle frequency, heating voltage[9], and the type of crystallization container—on the overall extraction efficiency. The results showed that adjustments to these factors led to measurable improvements in caffeine yield[6]. By comparing outcomes before and after optimization, the study further confirmed the beneficial effects of the process modifications. These findings offer practical insights for the efficient and cost-effective extraction of bioactive compounds from natural materials.
The underlying logic and innovative development path of artificial intelligence technology
Since the beginning of the 21st century, artificial intelligence technology has developed at an unprecedented speed, gradually permeating into every aspect of our lives, from voice assistants on smartphones to autonomous vehicles, from medical diagnosis to financial analysis. Artificial intelligence has become an important force driving social progress. Artificial intelligence may seem both familiar and mysterious. We use the conveniences it brings every day, but rarely delve into its underlying logic and innovative development path. In fact, the development of artificial intelligence is not achieved overnight, but is built upon a complex and stable technical system, simultaneously influenced by various factors such as market demand, policy guidance, and ethical constraints. A deep understanding of the underlying logic and development path of artificial intelligence not only helps us better adapt to future society but also stimulates our interest and contemplation in technological innovation. With the continuous evolution of technology, artificial intelligence is no longer just a concept in scientists’ laboratories, but has truly entered thousands of households and become an indispensable part of modern life. It has changed our learning methods, communication modes, and even ways of thinking, and its influence is continuously expanding.
Progress in Driver Fatigue Detection Technology Based on Image and State Fusion
Driver fatigue state detection represents one of the key technologies for enhancing road traffic safety. This paper systematically reviews the research progress, technical challenges, and development trends of driver fatigue detection methods based on the fusion of visual images and vehicle state information. First, it provides a detailed analysis of the theoretical foundations, implementation mechanisms, and performance characteristics of three categories of methods: those based on visual physiological features, driving behavior features, and multi-modal information fusion, tracing the technological evolution from traditional methods to deep learning models. Second, it delves into three core challenges currently faced by these systems in practical applications: environmental robustness, real-time constraints, and individual generalization ability. On this basis, the paper critically reviews the effectiveness and limitations of cutting-edge technical solutions such as lightweight network architectures, selfsupervised learning, and personalized federated learning. Finally, it outlines future research directions including multi-modal large models, vehicle-road cooperative perception, and neuromorphic computing, while also discussing opportunities and challenges related to technical standardization and system integration. This review aims to provide researchers and engineering practitioners with a systematic technical reference and insights for further development.
The Effects of ZnO Colloidal Particles on Photochemical Decomposition of DOM in Water Bodies
Dissolved organic matters, abbreviated as DOM, are indispensable parts in every water bodies, and are a main cause of most pollutions. In this research, UVVis spectrometry is used to measure the change in absorbance of the water samples collected from Sanhe Lake, Yunliang River and a pond(all in Nanjing) with different concentrations of ZnO colloids under the 300 W mercury light, and therefore use the absorbance calculated out to determine the rate and efficiency of photochemical decomposition to find out the extent of catalyzing effect of ZnO colloids on decomposing such DOM. After a series of experiments, we found out that ZnO works as a great catalyst in decomposing DOM. Its effect will differ a little bit depending on the type of water body. We think it can be taken as an effective way of tackling organic contamination issues.