Exploring Science Academic Conference Series
The Proceedings Series publishes peer-reviewed papers presented at the Exploring Science conferences. These proceedings are a valuable resource for the scientific community, providing access to the latest research findings, innovative methodologies, and interdisciplinary studies.
Design and Development of Robotic Arms: Structural Innovation, Intelligent Control, and Application Expansion
Robotic arms, as core executive components of industrial automation and intelligent robotics, are widely applied in industrial manufacturing, agricultural picking, medical rehabilitation, aerospace, and other fields. This paper systematically reviews the development history and current research status of robotic arms, focusing on structural design innovations, including rigid -flexible switching, bionic configurations, and lightweight materials, as well as intelligent control technologies, such as adaptive c ontrol, machine vision fusion, and human-machine interaction. The key technical bottlenecks that restrict the development of robotic arms are analyzed, including the trade -off between lightweight design and high load capacity, accuracy errors due to flexible deformation, poor adaptability in unstructured environments, and high operational costs. Finally, the future development trends of robotic arms are predicted to center on bionic integration, intelligent collaboration, modular customization, and green, energy-saving technologies, thereby providing a theoretical reference and technical support for subsequent research and engineering applications.
robotic arm, structural design, intelligent control, bionic robotics, industrial automation
Copyright (c) 2026 Qiyu Dong (Author) https://creativecommons.org/licenses/by/4.0
Applications of Single-Electron Devices for Nanoscale Quantum Precision Measurement
Single-electron devices with the Coulomb blockade effect and single -electron tunneling effect are able to accurately control the quantum state of an electron. This paper systematically investigates its application in this field as the core carrier to overcome the limitations of traditional measurement technology and realize nanoscale quantum precision measurement. The paper conducts a deep analysis about its technical principle, typical device structure, and performance optimization mechanism. Firstly elaborating the core physics behind single-electron phenomena and key features of devices; secondly taking devices including Single -Electron Transistors (SETs), and single -electron boxes as examples detailing their applications in regulating quantum states, detecting nanoscale magnetic/electric fields, and characterizing single -molecule charges. Emphasize the novel designs and measurement performances of new devices like twisted bilayer graphene quantum dot SETs and room -temperature silicon -based SETs. Las tly discuss existing device -related issues regarding stability, integration, and environmental interference, and look forward to future developments in quantum sensing, quantum computing, and biomedicine. Our research shows that through precise control of quantum effects, single -electron devices enable ultra -high sensitivity measurements of physical quantities at the nanoscale, which is a revolutionary solution for atomic -level detection and brings great scientific value and engineering applications.
single-electron devices, precisely manipulate, stability, integration, engineering application prospects
Copyright (c) 2026 Yanbo Wang (Author) https://creativecommons.org/licenses/by/4.0
Research on the Application of Machine Vision in Industrial Robots
With the rapid development of intelligent manufacturing and Industry 4.0, industrial robots have been widely applied in modern manufacturing processes. However, traditional industrial robots often rely on pre - programmed instructions and fixed trajectories, which limit their flexibility and adaptability in complex environments. Machine vision technology enables industrial robots to perceive, identify, and analyse surrounding objects through image acquisition and processing. This paper systematically studies the application of machine vision in industrial robots. First, the basic concepts, components, working principles, and image processing technologies of machine vision are introduced. The structure and operating principles of industrial robot systems are then analysed. Furthermore, several typical applications of machine vision in industrial robots are discussed, including workpiece identification and positioning, visual guidance in welding and assembly, product quality inspection, and automatic sorting systems. In addition, the current challenges in machine vision technology, including environmental interference, target occlusion, high hardware costs, and real-time processing requirements, are analysed. Finally, future development trends are explored, including the integration of artificial intelligence, multi -sensor fusion, digital twins, and intelligent manufacturing systems. The study shows that machine vision plays an important role in improving the accuracy, efficiency, and automation level of industrial robots and will continue to promote the intelligent development of modern manufacturing.
machine vision, industrial robots, visual guidance, intelligent manufacturing, automation technology
Copyright (c) 2026 Zeda Li (Author) https://creativecommons.org/licenses/by/4.0
Research Progress on Magnetic Wheel Transmission with Magnetic Coupling Speed Regulation
Fluid electromechanical equipment, such as fans and water pumps, accounts for a large proportion of total energy consumption in China. Throttle speed regulation results in substantial energy loss, while variable - frequency speed regulation is prone to elect romagnetic interference and thus limited in application scenarios. A magnetic wheel transmission based on magnetic coupling transfers power via non -contact magnetic fields, featuring soft start, vibration reduction, energy savings, and overload protection. This paper summarizes the structures and speed regulation mechanisms of various magnetic couplers, including cylindrical, disc, and conical types. It systematically analyzes the performance characteristics of permanent magnet materials, magnetic conductive materials, insulating materials, and supporting structural materials for magnetic wheel transmission. It compares the loss characteristics and adaptability to working conditions of electrical steel, soft magnetic composites, and cobalt -based alloys. The significance of insulat ion coating for suppressing eddy - current losses in soft magnetic composites is clarified. Moreover, the research progress in structural optimization, electromagnetic simulation models, and eddy -current heat -dissipation design for magnetic couplers is reviewed. Engineering cases show that when this transmission device is applied to equipment in thermal power, municipal engineering, petrochemical, coal mining, and other industries, the power-saving rate ranges from 11% to 34.62%, and it can effectively reduce vibration and operational & maintenance pressure. At present, existing research still has deficiencies, such as insufficient comparison of multiple speed-regulation schemes and room for improvement in high -frequency losses and torque density. Finally, the future research directions, including high-temperature superconducting magnetic materials, novel electromagnetic calculation algorithms, and adaptive magnetic circuit regulation systems, are prospected. This study provides theoretical support for the ener gy-saving transformation of fluid load equipment and for the engineering application of magnetic transmission equipment.
magnetic coupling, magnetic wheel transmission, permanent magnet materials, structural optimization, energy-saving transformation
Copyright (c) 2026 Haoyang Chen (Author) https://creativecommons.org/licenses/by/4.0
Flexible Conductive Composites for Electronic Skin Applications: A Review
Research into electronic skin, or e-skin, has evolved into a fast-moving field. Researchers aim to build artificial systems with sensing performance matching human skin. Robotics, wearable electronics, and healthcare monitoring tools are all seeing rapid p rogress. This has generated strong demand for flexible sensors that fit curved surfaces and detect signals such as pressure, strain, and temperature. Many material systems are currently being tested for e-skin devices, among which flexible conductive composites deliver clear advantages. These materials combine conductive properties, stretchability, and sound mechanical resilience, making them highly practical for e -skin construction. This review surveys the latest progress in conductive composite materials for e-skin across five dimensions —material systems, conduction mechanisms, sensing principles, structural design strategies, and practical deployment hurdles. It examines representative conductive fillers (carbon nanotubes, graphene, MXene, silver nanowires, and conductive hydrogels) alongside their polymer hosts, compares charge -transport behaviors and sensing modalities across different composite families, and analyzes how micro - and nano -scale structural engineering boosts sensitivity, f lexibility, and durability. Mainstream fabrication routes, real -world application scenarios, and persistent technical obstacles are also discussed, along with emerging directions such as self-healing materials and self-powered e-skin architectures. By trac ing the links among material choice, sensing mechanism, device architecture, and application requirements, this paper clarifies what existing conductive composite systems can and cannot deliver, and offers a forward-looking perspective on where intelligent e-skin sensing systems may head next.
electronic skin, flexible conductive composites, tactile sensing, conductive hydrogels, wearable electronics
Copyright (c) 2026 Xiaotian Han (Author) https://creativecommons.org/licenses/by/4.0
Flexible Electronic Devices Based on Two-Dimensional Material/Polymer Composites
The new generation of electronic devices is incorporating mechanical flexibility into their design, a trend that demands large-area, ultra-thin functional materials that are both energy-efficient and economically viable. The emergence of two-dimensional materials has ushered in a new era of integrated, flexible technology, surpassing the capabilities of traditional semiconductors. Furthermore, 2D materials are highly valuable for advancing a wide range of emerging fields, including wireless health monitorin g systems, flexible bioelectronics, and origami-inspired unconventional device architectures, all of which are suitable for challenging applications. This review examines the technological progress and fundamental aspects of 2D material -based flexible devices. This article will systematically summarize the applications of these devices in various areas. Subsequently, this paper focuses on elaborating the applications of such devices from three core perspectives: flexible sensors, flexible displays, and bio-integrated soft electronics. These devices offer promising prospects in fields such as health monitoring, human -machine interaction, and medical diagnosis. Finally, the paper discusses current challenges and their solutions.
flexible electronics, two-dimensional material, polymer composites
Copyright (c) 2026 Yinuo Du (Author) https://creativecommons.org/licenses/by/4.0
Application and Recycling of Lithium-ion Batteries
In recent years, the large -scale utilization of renewable energy sources, along with clean and low -carbon conventional energy, has emerged as a fundamental trend shaping the future of global energy development. As a critical enabling technology, lithium -ion batteries are increasingly important in advancing renewable energy integration across multiple sectors. This paper provides a comprehensive overview of lithium -ion battery applications, focusing on their use in energy storage systems for power grids and wind power generation, which are vital for balancing supply and demand and enhancing system stability. Furthermore, the paper highlights the growing importance of lithium -ion battery recycling and recovery technologies, addressing environmental sustainability and resource-efficiency challenges associated with battery lifecycles. By exploring these aspects, the study aims to contribute valuable insights into the sustainable deployment and management of lithium-ion batteries within the evolving energy landscape.
lithium-ion battery, recycling, power systems
Copyright (c) 2026 Junhan Zhang (Author) https://creativecommons.org/licenses/by/4.0
Advances in Thin-Film Lithium Niobate High-Speed Electro-Optic Modulators
The thin-film lithium niobate (TFLN) platform, with high refractive-index contrast and a strong linear electro- optic effect, offers a viable pathway to overcoming the performance limitations of conventional bulk-material electro-optic modulators. This paper systematically reviews key technological advances in TFLN high -speed electro-optic modulators. In terms of synergistic optimization of modulation efficiency and electro -optic bandwidth, three technical routes are summarized: microstructured electrode design, waveguide mode engineering, and velocity -matching strategies, encompassing periodically capacitively loaded T -electrodes, slow-wave electrodes, buried dual-capacitor structures, slot waveguides, and high-permittivity cladding. These approaches have reduced the half -wave voltage-length product (VπL) to 1 –2.5 V· cm and pushed the 3 dB electro-optic bandwidth beyond 140 GHz. In terms of functional expansion and heterogeneous integration, polarization-independent modulation, Si/SiN, and chalcogenide glass heterogeneous integration technologies are reviewed, along with application -specific designs for ultrashort pulse generation, laser ranging, and fully packaged devices. Different technical routes exhibit distinct performance trade -offs: microstructured electrodes and optical mode engineering can significantly enhance modulation efficiency but at the cost of increased fabrication complexity, higher coupling loss, and enhanced high -frequency dispersion; heterogeneous integration offers advantages in bandw idth extension and functional convergence, yet faces challenges in thermal management, interfacial defects, and material compatibility. Currently, the development of TFLN modulators is transitioning from single-parameter performance enhancement toward comprehensive optimization of efficiency, bandwidth, loss, and manufacturability. Multi -objective co -design and optoelectronic co-packaging will represent important future directions.
thin-film lithium niobate, electro -optic modulator, Mach –Zehnder interferometer, half -wave voltage -length, product
Copyright (c) 2026 Peiyao Gu (Author) https://creativecommons.org/licenses/by/4.0
Optimization of Lithography Process Parameters for Improving Photodetector Array Performance
Photodetectors are widely used in environmental monitoring, optical communication, industrial inspection, and imaging systems. As photodetector devices advance toward higher resolution, smaller pixel sizes, and larger array integration, lithography has bec ome a key fabrication process that affects electrode accuracy, active-region geometry, and device consistency. This paper investigates the influence of lithography process parameters on the fabrication quality and photoelectric performance of photodetector arrays. Focusing on silicon-based and InP substrates, the study analyzes the effects of exposure dose, development time, baking temperature, and alignment accuracy on line width uniformity, electrode spacing, dark current, responsivity, and array yield. The results show that optimized step-and-repeat lithography can effectively reduce line width deviation, improve multilayer alignment accuracy, and enhance device uniformity. In particular, an appropriate exposure dose helps maintain well-defined photoresist patterns, reduce edge distortion, and improve electrode consistency. These process improvements contribute to lower dark current, higher responsivity, and improved production yield in array photodetectors. This stud y demonstrates that systematic lithography parameter optimization can enhance photodetector performance without introducing major changes to existing fabrication equipment, providing a practical process reference for small - and medium -scale optoelectronic device manufacturing.
photodetector array, lithography process, exposure dose, line width uniformity, alignment accuracy
Copyright (c) 2026 Yanxu Ji (Author) https://creativecommons.org/licenses/by/4.0
Hybrid and Time/Frequency-Domain Approaches for Low-Power High-Performance ADCs/DACs: Recent Advances and Perspectives
The continuous advancement of modern communication systems and sensing technologies has urgently demanded low -power, high -performance Analog -to-Digital Converters (ADCs) and Digital -to-Analog Converters (DACs). To address this need, this paper presents a s ystematic review of current optimization strategies, employing literature analysis and architectural comparison to evaluate approaches that aim to balance power efficiency and performance while highlighting their limitations. This review concludes that hybrid architectures and time/frequency -domain methods offer novel perspectives for achieving low -power and high -performance ADC/DACs, with NS -SAR ADCs and TDC -based ADCs identified as particularly promising candidates. Despite numerous proposals to mitigate noise, complete solutions have yet to be realized. Analysis using the Schreier Figure of Merit ( FoM) further confirms that high performance and low power consumption remain inherently conflicting objectives. While existing methods have achieved significant improvements in either power efficiency or performance, the development of an ADC/DAC that simultaneously optimizes both metrics remains an open challenge. The insights presented in this review are expected to guide future research on the design of energy -efficient data converters, ultimately supporting the advancement of communication systems, sensors, and other electronic technologies, and contributing to more intelligent and convenient applications in modern society.
ADC/DAC, low-power, high-performance, hybrid architecture, time/frequency domain
Copyright (c) 2026 Yikang Zheng (Author) https://creativecommons.org/licenses/by/4.0
The Impact of Clearance in the Front -wheel Steering Mechanism on Response Delay and Trajectory Deviation
Single Pilot Operation (SPO) imposes stringent safety requirements on aircraft ground taxiing. However, the quantitative impact of mechanical clearance in the nose -wheel steering mechanism on response delay, trajectory deviation, and pilot workload remains insufficiently explored. In this study, a multi-body kinematic model with varying clearances was established using ADAMS to investigate this mechanism. By integrating a bicycle kinematic model, the strut steering angles were translated into aircraft taxiing trajectories under both open-loop and closed -loop (proportional control) conditions. The results demonstrate a non -linear positive correlation between clearance size and response delay. Crucially, automatic control exhibits an inherent compensation boundary, failing to eliminate the initial lag caused by the mechanical dead zone. Trajectory deviations, including lateral offset and heading angle errors, expand significantly with larger clearances and are further amplified at higher taxiing speeds. Workloa d assessments indicate that the 0.5 mm clearance (defined maintenance threshold in this paper) already induces a high monitoring workload for single pilots. Consequently, this paper recommends stricter maintenance thresholds, feedforward compensation strat egies, and predictive heading indicators to ensure taxiing safety and alleviate pilot workload in SPO mode.
front-wheel steering mechanism, response delay, single-pilot operation, workload, ADAMS simulation
Copyright (c) 2026 Mingzhen Lv (Author) https://creativecommons.org/licenses/by/4.0
Research Progress and Development Trends in Energy- Field-Assisted Laser Additive Manufacturing of Titanium Alloys
Titanium alloys are known for their high specific strength, excellent corrosion resistance, and good high - temperature mechanical properties. They have extensive applications in fields such as aerospace, high -end equipment, and biomedicine. However, during the laser additive manufacturing of titanium alloys, rapid melting and solidification behavior, combined with complex thermal cycling, tend to induce coarse columnar grain structures, residual stress accumulation, and defects such as porosity and cracks. I t constrains further improvement in the comprehensive performance of the components. In recent years, energy -field-assisted technologies have emerged as a crucial approach to enhancing the quality and performance of laser additive manufacturing of titanium alloys. By introducing external fields, such as ultrasonic, thermal, plastic deformation, and electromagnetic fields, during the forming process, these technologies enable effective control over molten pool flow, heat and mass transfer, and the evolution of solidified microstructures. This paper provides a comprehensive review of research progress on laser additive manufacturing of titanium alloys assisted by single and multi -energy fields. It focuses on summarizing the process characteristics, microstructure control mechanisms, and performance enhancement principles associated with various energy fields, while elucidating the underlying mechanisms by which these fields influence molten pool evolution, grain refinement, defect suppression, and residual stress regulation. Finally, the future development directions of energy-field-assisted laser additive manufacturing of titanium alloys are outlined. This paper provides a theoretical reference for the development and engineering application of additive manufac turing technology for titanium alloys.
laser additive manufacturing, titanium alloys, energy field assistance, microstructure and property control
Copyright (c) 2026 Lixiang Ma (Author) https://creativecommons.org/licenses/by/4.0
Analysis of Biochar Adsorption of Heavy Metal Ions in Water
At present, heavy metal ion pollution in water bodies has become a major challenge in global water environment governance. Although conventional treatment technologies such as chemical precipitation, membrane separation, ion exchange, and electrochemical m ethods are widely applied, they are often constrained by high operational costs, secondary pollution risks, and complex processing procedures. Against this background, biochar has attracted increasing attention as a promising material for water pollution remediation. This paper compares the physicochemical differences between plant -based biochar and solid waste-based biochar, with a focus on their implications for adsorption performance in different environmental conditions. The results indicate that the adsorption of heavy metal ions by biochar is governed by the combined effects of physical adsorption, chemical interactions, and ion exchange processes. These mechanisms together provide a more integrated explanation of the adsorption behavior of biochar in aquatic environments.
biochar, heavy metal adsorption, adsorption mechanisms
Copyright (c) 2026 Xuming Zhang (Author) https://creativecommons.org/licenses/by/4.0
Research on Combustion and Emission Characteristics and Performance Optimization Technology of Hydrogen Internal Combustion Engines
Against the backdrop of the “Dual Carbon” goals and energy transition, hydrogen internal combustion engines have become an important development direction for hydrogen power by virtue of mature industrial chains and low-cost advantages. Nevertheless, backfire, pre-ignition, high NOₓ emissions and insufficient thermal efficiency remain bottlenecks restricting their large-scale promotion. Experiments show that NOₓ emissions are significantly regulated by the excess air coefficient and reach the peak in the mo derate lean-burn range; under cold start conditions, NOₓ emissions hit the maximum at λ=1.41, with an emission reduction rate of 84.4% when λ drops to 0.72. The adoption of direct in -cylinder injection can fundamentally avoid intake mixture premixing and suppress backfire and pre -ignition. Matching lean combustion, optimized ignition and hydrogen injection strategies as well as eliminating throttle pumping loss can greatly improve in-cylinder combustion quality and thermal efficiency. Based on domestic and overseas research, this paper reviews relevant technical routes, clarifies key optimization methods and technical deficiencies, and offers theoretical references for the engineering calibration and clean, efficient development of hydrogen internal combustion engines.
hydrogen internal combustion engine, excess air coefficient, nitrogen oxide emission, direct in -cylinder, injection, thermal efficiency
Copyright (c) 2026 Jianxiang Huang (Author) https://creativecommons.org/licenses/by/4.0
Thermal Management of Photovoltaic Modules: Material Strategies and Structural Optimization
The industrialization of TOPCon and perovskite-silicon tandem solar cells has shifted photovoltaic thermal management from a one-size-fits-all cooling approach to customized strategies that target specific degradation mechanisms. In these advanced cells, high temperatures induce irrever sible degradation —such as surface passivation degradation in TOPCon and halide ion migration in perovskite tandems—that cannot be reversed by simple temperature reduction. This review synthesizes current understanding of these degradation pathways and evaluates the design principles and durability of radiative cooling coa tings, phase-change materials, and spectrally selective encapsulants. It further examines structural measures —including fractal fins, heat pipes, and array spacing optimization—that enhance heat dissipation. A quantitative framework integrating thermal, electrical, thermodynamic, and economic metrics with levelized cost of electricity (LCOE) is proposed to enable objective comparisons across climates and technologies. We argue that coordinated material–structure design offers the most promising route to overcoming performance bottlenecks and bridging the gap between laboratory breakthroughs and industrial deployment.
photovoltaic thermal management, structural optimization, TOPCon solar cells, perovskite -silicon tandem, solar cells
Copyright (c) 2026 Tianhao Wen (Author) https://creativecommons.org/licenses/by/4.0
Advancements in Gel Polymer Electrolytes: From Structural Engineering to Functional Applications
Gel polymer electrolytes (GPEs) have emerged as a promising class of quasi -solid-state electrolytes that combine the liquid -like interfacial compatibility of conventional liquid electrolytes with the mechanical integrity and leakage resistance of solid -state systems. Despite these advantages, their deployment in high - energy-density lithium batteries is still constrained by insufficient room -temperature ionic conductivity, low lithium-ion transference number (t Li+), limited mechanical robustness, and unstable electrode/electrolyte interfaces. This review provides a mechanism -guided overview of recent advances in GPEs, with particular emphasis on the coupled regulation of ionic conductivity and t Li+. First, the compositional features, ion - transport mechanisms, and key electrochemical evaluation metrics of GPEs are summarized to establish a unified structure -property framework. Subsequently, three major modification strategies are critically discussed: polymer -matrix engineering for crystallinity suppression and pathway construction, single -ion- conducting and anion -regulating designs for enhancing t Li+, and functional filler incorporation for simultaneously improving mechanical strength, interfacial stability, and ion transport. Representative examples based on cross -linked networks, high -entropy gel systems, porous/aligned polymer frameworks, anion-anchored polymer electrolytes, boron -based anion receptors, inorganic nanofillers, metal -organic frameworks, and covalent organic frameworks are discussed in relation to their underlying mechanisms. Finally, the application prospects of GPEs in high -energy lithium batteries, flexible/wearable devices, and intelligent energy-storage systems are analyzed. Future research directions, including data -driven electrolyte design, scalable in situ manufacturing, and multifunctional integration, are proposed to guide the development of next-generation high-performance GPEs.
gel polymer electrolyte, lithium -ion battery, ionic conductivity, lithium -ion transference number, polymer, matrix, functional filler, single-ion conductor
Copyright (c) 2026 Kaichuan Hou (Author) https://creativecommons.org/licenses/by/4.0
A Driver Fatigue Detection Mechanism Based on a Lightweight RGB-IR Fusion Algorithm
To address the degradation of feature representation in a single RGB modality under low-light conditions, and the lack of texture and semantic information in a single IR modality, this paper proposes a lightweight fatigue detection method based on RGB-IR dual-modal fusion. This method realizes cross-modal information fusion at the feature layer by building a dual-stream feature extraction framework, and introduces a feature alignment mechanism to improve the semantic consistency of RGB and IR; At the same t ime, it combines lightweight network design and unidirectional feature aggregation strategy to reduce the complexity of model calculation, and improve the real-time performance of the system through asynchronous dual-stream inference mechanism. The experimental results show that the dual -flow model based on the dual lightweight strategy shows better detection robustness under extremely dark light conditions: mAP@0.5 is upgraded from 0.314 of the single - stream RGB model to 0.547, mAP@0.5:0.95 increased from 0.200 to 0.359; Compared with the dual -flow RGB IR baseline model, the number of parameters and FLOPs decreased by 37.45% and 24.57% respectively. Under the asynchronous inference mechanism, the effective frame rate of the system reaches 72.09 FPS. It can be seen that the dual lightweight strategy achieves a better balance between detection performance, model complexity and real-time performance, providing a feasible solution for in -vehicle driver fatigue detection in low-light environments.
driver fatigue detection, YOLO, RGB-IR, cross-modal fusion, intelligent transportation systems
Copyright (c) 2026 Weixuan Shao (Author) https://creativecommons.org/licenses/by/4.0
Convergence and Device Innovation: From Low- Dimensional/Lead-Free Perovskite Photovoltaics to Micro/Nano Light-Emitting Displays
Current optoelectronic technologies still face several limitations, including the efficiency ceiling of crystalline silicon, the instability of conventional perovskites, and transfer -related challenges in Micro -LED fabrication. This study centers on the cross -boundary integration of lead -free, low -dimensional perovskite photovoltaics and micro/nano light -emitting displays. Efficient control of carrier dynamics is critical for improving both photovoltaic conversion and light -emitting performance. Through lead -free substitution and dimensional reduction (i.e., the construction of low -dimensional superstructures), an intrinsic water -oxygen barrier is established to significantly enhance the chemical stability of the m aterials. In addition, quantum confinement modifies the density of states (DOS) distribution, thereby substantially boosting the radiative recombination efficiency. By leveraging fundamental physical strategies such as band engineering, this research may support the development of high -performance optoelectronic devices with improved stability and efficiency.
lead-free low -dimensional perovskites, micro/nano light -emitting displays, dimensionality modulation, optoelectronic integration
Copyright (c) 2026 Haotian Gao (Author) https://creativecommons.org/licenses/by/4.0
Analysis of Multi-Sensor Fusion Technology Applied in Autonomous Navigation
Aiming at the problems of perception blind zones, error accumulation, and poor environmental adaptability inherent in single -sensor autonomous navigation systems, this paper investigates multi -sensor fusion technology for autonomous navigation. By integrating LiDAR, vision, IMU, and GNSS/RTK sensors, a unified framework encompassing spatio -temporal registration, feature extraction, data fusion, and global optimization is constructed. Extended Kalman Filter (EKF) is employed to achieve tightly -coupled fusion, while graph optimization is utilized for SLAM correction. Path planning is realized based on the Dynamic Window Approach (DWA) and the Timed Elastic Band (TEB) algorithm. Experiments conducted in multiple scenarios demonstrate that the system achieves a positioning accuracy of 0.08 m in normal environments, better than 0.12 m in complex scenes, a tunnel trajectory deviation error of 0.064 m, and a lateral tracking error of ± 2.6 cm for agricultural machinery. The success rates for static and dynamic obstacle avoidance are 100% and 95.7%, respectively. This method can significantly improve navigation accuracy and robustness in complex environments, providing technical support for the autonomous navigation of intelligent equipment.
multi-sensor fusion, autonomous navigation, SLAM, pose estimation, path planning, Kalman filtering
Copyright (c) 2026 Shouzheng Li (Author) https://creativecommons.org/licenses/by/4.0
Technology for Facial Expression Recognition Across Different Scenes
This paper conducts a systematic review and analysis of the key technologies for facial expression recognition across different scenarios. As the facial expression recognition technology moves from the laboratory to diverse real -world scenarios such as remote healthcare, mental health , and intelligent cabins, ensuring the model maintains high performance in complex environments has become a core issue that needs to be urgently addressed. Firstly, this paper reviews three key technology systems focusing on environmental robustness, efficient deployment, and data scarcity and domain adaptation. It elaborates on representative methods such as attention mechanisms, lightweight networks, and domain adaptation, along with their progress. Based on this, it further analyzes the common challenge s faced in cross -scenario applications, including environmental interference, data distribution differences, and deployment constraints. The review results indicate that there is no universal optimal model. The technical solutions need to be deeply adapted to specific scene requirements. The integration of robustness, lightweighting, and domain adaptation technologies is the future development trend. This paper provides theoretical basis and practical references for the selection of facial expression recognition technologies for specific scenarios.
facial expression recognition, environmental robustness, lightweight, domain adaptation, cross-scene
Copyright (c) 2026 Hongrui Zhang (Author) https://creativecommons.org/licenses/by/4.0
Development of Non-Destructive Testing for Hydraulic Metal Structures and the Application of Phased Array Ultrasonic Technology
Against the background of increasingly complex operating conditions and the aging of early equipment in hydraulic metal structures, conducting preventive non-destructive testing is of great significance for ensuring the safe operation of water conser vancy and hydropower projects. Compared with traditional inspection methods, phased array ultrasonic technology effectively overcomes the limitations of conventional techniques, such as large inspection blind zones and radiation hazards. This technology has demonstrated high reliability and significant practical value in addressing engineering challenges including full -coverage scanning of complex welds, inspection of special materials in turbine runners, and detection of high -strength bolts. The widespread application of phased array ultrasonic technology not only effectively identifies defects in deep structural regions but also provides a more scientific and modern inspection approach for ensuring the safety of hydraulic metal structures.
hydraulic metal structures, non-destructive testing, phased array ultrasonic technology, welds
Copyright (c) 2026 Bolin Ji (Author) https://creativecommons.org/licenses/by/4.0
Multi-dimensional Drivers and Optimization Strategies of Turnover Intention for Grassroots Community Social Workers
High turnover of grassroots community social workers severely hinders the construction and steady operation of local social service systems in China. Frontline practitioners are responsible for daily case management, community activity organization and vulnerable group assistance. They are required to deliver diversified public services under tight bureaucratic schedules, so long-term work pressure easily causes occupational burnout and voluntary resignation. Existing empirical studies mostly adopt single-factor analysis and rarely construct integrated multi-layer analytical frameworks to interpret turnover intention; prior scholarship tends to focus on personal psychological traits, overlooking interactive influences from agency management and top-down governmental policies. This paper builds a three-layer analytical model based on Job Demands-Resources Theory, Occupational Embeddedness Theory and Organizational Identity Theory, to systematically explore individual, organizational and macro governance drivers of social workers’ turnover intention. The study collects and codes 37 qualified journal papers released between 2019 and 2026 via thematic analysis. Research findings confirm that excessive workload, insufficient organizational support and flawed governance mechanisms jointly amplify turnover risk: heavy job demands drain personal emotional energy, lacking workplace support lowers occupational embeddedness, and unreasonable governance arrangements weaken workers’ sense of belonging to their service organizations. Accordingly, this paper proposes multi-level optimization strategies involving administrative assessment adjustment, internal organizational system improvement and public financial resource reallocation. These policy suggestions can help authorities retain skilled frontline practitioners, consolidate stable community social service teams, and promote sustainable improvement of grassroots social governance across China.
grassroots social worker, turnover intention, job demands-resources theory, occupational embeddedness, governance optimization
Copyright (c) 2026 Wenxi Li (Author) https://creativecommons.org/licenses/by/4.0
Impact of Early Mobilization on Clinical Outcomes of Mechanically Ventilated Patients During Critical Care Rehabilitation and Related Nursing Practices
Objective To systematically review the effects of early mobilization in critical care rehabilitation on the key clinical outcomes of mechanically ventilated patients, and deeply explore the key points, challenges and countermeasures of nursing practice under the cur rent evidence-based background. Methods A systematic literature search was conducted in PubMed, CINAHL, the Cochrane Library, CNKI, and Wanfang Database. Covering clinical practice guidelines, systematic evaluation, randomized controlled trials and high -quality reviews. According to predefined inclusion and exclusion criteria, the retrieved literature is screened, and thematic analysis method is used for induction, integration and critical analysis. Results The existing current evidence shows that early mobilization can significantly improve the prognosis of mechanically ventilated patients, which is mainly reflected in shortening mechanical ventilation time and ICU length of stay, reducing the incidence of I CU acquired weakness (ICU -AW) and delirium, and promoting long -term functional recovery. The core links of relevant nursing practice include: patient assessment and risk stratification based on standardized processes, the construction and coordination of multidisciplinary teams, individualized progressive mobilization plans coordinated with sedation and analgesic strategies, safety monitoring a nd risk prevention throughout the whole process, and identification and response to implementation obstacles. Conclusion Early mobilization is a key evidence -based measure to improve the prognosis of patients with mechanical ventilation. Nurses play an indispensable core role in the implementation of early mobilization. Through a systematic discussion of nursing practice, it helps to transform scientific evidence into clinical practice more safely and effectively, and provides a theoretical basis and practical direction for the construction of a localized early mobilization nursing program, so as to maximize the benefits of patient rehabilitation.
mechanical ventilation, early mobilization, critical care rehabilitation, clinical outcomes, nursing practice
Copyright (c) 2026 Lianghao Zhao (Author) https://creativecommons.org/licenses/by/4.0
Research Progress and Clinical Challenges of Precision Targeted Therapy for Autoimmune Diseases
The treatment of autoimmune diseases is undergoing a paradigm shift from “broad -spectrum immunosuppression” toward “precision targeted intervention.” Although conventional synthetic disease - modifying antirheumatic drugs (such as methotrexate) remain the cornerstone of therapy, their efficacy ceiling and cumulative toxicity limit long-term use, and clinical practice still has safety gaps, such as inadequate folic acid supplementation. The advent of targeted biologic agents (e.g., TNF -α inhibitors, IL-6R antagonists) and JAK inhibitors has enabled precise blockade of specific inflammatory pathways. However, studies such as ORAL Surveillance have revealed a “safety paradox” of JAK inhibitors regarding cardiovascular and thrombotic risks, highlighting the need for a careful balance between efficacy and risk in clinical practice. To address the clinical challenge of secondary loss of response, precision -switching strategies grounded in immunogenicity theory and therapeutic drug monitoring —including same-target cycling and cross -pathway switching—have emerged as core approaches to optimize efficacy. Meanwhile, bispecific antibodies and CAR-T cell therapies have demonstrated potential breakthrough value in refractory autoimmune diseases; however, their long -term safety, suitability for specific patient populations, and accessibility require further validation through larger-scale clinical studies.
targeted therapy, autoimmune diseases, JAK inhibitors, immunogenicity, CAR-T therapy, precision medicine
Copyright (c) 2026 Mengyang He (Author) https://creativecommons.org/licenses/by/4.0
Study on the Mechanism and Application Prospect of Guizhi Fuling Wan in Improving Insulin Resistance in Polycystic Ovary Syndrome
Polycystic ovary syndrome (PCOS) represents a prevalent endocrine and metabolic disorder among reproductive-aged women, with insulin resistance (IR) serving as a pivotal factor in its pathophysiology. Current Western medical approaches primarily target sym ptomatic relief; however, they are often associated with notable adverse effects, high recurrence rates, and drug dependency. Guizhi Fuling Wan, a classical traditional Chinese medicinal formula known for its blood -activating and stasis -resolving propertie s, has recently demonstrated considerable therapeutic promise in managing gynecological conditions. This review systematically synthesizes available theoretical insights and literature to delineate the mechanistic actions, pharmacodynamic constituents, and clinical application prospects of Guizhi Fuling Wan in ameliorating IR associated with PCOS. Accumulating evidence suggests that this formula may enhance insulin sensitivity and mitigate PCOS-related metabolic disturbances through multifaceted mechanisms, including modulation of the PI3K/Akt/mTOR signaling cascade, suppression of autophagy in ovarian granulosa cells, and attenuation of inflammatory responses and oxidative stress. Nevertheless, the current body of evidence predominantly derives from animal studies, with a conspicuous paucity of robust clinical data. Future investigations should prioritize high-quality clinical trials to validate its therapeutic efficacy, elucidate its pharmacodynamic underpinnings, and assess its synergistic potential when c o-administered with conventional drugs, thereby offering novel perspectives for integrated traditional Chinese and Western medicine strategies in PCOS management.
Guizhi Fuling Wan, polycystic ovary syndrome, insulin resistance, classic prescription, mechanism of action, clinical application
Copyright (c) 2026 Yiduo Zheng (Author) https://creativecommons.org/licenses/by/4.0
Recent Advances in Biosensors for Ovum Maturity Detection: Technologies, Challenges, and Future Perspectives
Biosensors are advanced medical detection tools with pivotal applications in ovum maturity detection, providing accurate clinical experimental data and professional condition assessment. This paper deliberates three main types of biosensors in this field: electrochemical sensors, which measure electronic signal changes via nano-modified electrodes to detect estradiol levels in follicular fluid, thereby assessing ovum maturity; optical sensors, which test the intensity of fluorescent biomarkers to evaluate t he dynamic change in mRNA; and piezoelectric sensors, which measure the changes in mass associated with ovum maturity.
biosensors, ovum detection, electochemical sensors, optical sensors, piezoelectric sensors
Copyright (c) 2026 Yuping Zhao (Author) https://creativecommons.org/licenses/by/4.0
An Integrated Analysis of Cardiac Output and Muscle Oxidative Capacity on Exercise Performance in Adolescents
The cardiovascular and muscular developing systems during adolescence are considered to be a critical period in the physiological basis of the long -term exercise capacity and health. This research seeks to examine how cardiac output and muscle oxidative capacity work together to influence exercise performance in teenagers in a systems approach. It claims that performance in exercise is not governed by one limiting factor, but is the interaction between oxygen delivery and oxygen utilization systems. The stu dy shows that the performance limitation can alternatively be between central and peripheral system based on their relative developmental level through theoretical analysis and case examples through the conceptual illustrations. In case of inadequate cardiac output, oxygen delivery makes the limiting factor that limits aerobic performance in spite of muscular capacity. On the other hand, in cases where the delivery of oxygen is normal and the oxidative capacity of the muscle is small, inefficient use of oxygen causes premature fatigue and low endurance. The analysis also points out that the combined development of the systems and their coordinated operation is a way to reach optimal performance. Despite having a well -organized conceptual framework, the study is constrained by lack of empirical validation. Future studies need to be experimental and longitudinal to test and refine further this combined framework in adolescence population.
cardiac output, muscle oxidative capacity, adolescent exercise performance, oxygen transport system, aerobic, capacity
Copyright (c) 2026 Zhanshuo Zhang (Author) https://creativecommons.org/licenses/by/4.0
The Role of GenSAS, BLAST, and UniProt in Bioinformatics for Gene Research
The rapid expansion of genomic and proteomic data has intensified the need for robust bioinformatics tools capable of transforming raw sequences into meaningful biological insights. This review highlights the roles of three foundational platforms—GenSAS, BLAST, and UniProt—in gene research workflows. GenSAS offers comprehensive genome annotation capabilities, particularly for non -model organisms; BLAST enables efficient sequence alignment and homology detection; and UniProt serves as a rich repository of cu rated protein information. This research analyzes their individual functions, integration potential, and applications across structural annotation, functional prediction, and comparative genomics. Case studies demonstrate their use in diverse research cont exts, including plant genome annotation, evolutionary analysis, and protein function characterization. We also discuss future directions, emphasizing the importance of machine learning integration, multi -omics interoperability, and enhanced user accessibil ity. Together, these tools provide a synergistic framework that continues to drive advances in gene discovery and bioinformatics.
bioinformatics, gene function annotation, GenSAS, BLAST, bioinformatics proteomics
Copyright (c) 2026 Rumo Bian (Author) https://creativecommons.org/licenses/by/4.0
A Review of Brain-Computer Interfaces in Neurorehabilitation and Nursing Care for Patients with Paraplegia
Paraplegia, most commonly caused by spinal cord injury (SCI), results in motor, sensory, and autonomic dysfunction below the level of injury. Traditional rehabilitation primarily relies on passive training, which has limited effects on central neural remod eling. As a cutting-edge neuromodulation technology, brain-computer interfaces (BCIs) can bypass the damaged spinal cord and directly translate brain signals into commands for external devices, offering a new pathway for functional reconstruction. Focusing on the neurorehabilitation and nursing perspectives of patients with paraplegia, this review systematically summarizes the definition, principles, classification, and clinical value of non -invasive EEG‑BCI and invasive implantable BCI. It outlines stratif ied rehabilitation strategies for patients with different injury severities and constructs a comprehensive nursing model that includes pre -rehabilitation assessment, intra -training monitoring, complication prevention, psychological intervention, and home -based continuing care. Current evidence indicates that BCIs can effectively activate neuroplasticity, relieve spasticity, and improve motor intention and activities of daily living. Professional nursing is critical for ensuring safety, adherence, and long-term outcomes. This review also discusses current research limitations and proposes future directions to inform clinical practice and academic research.
brain-computer interface, paraplegia, spinal cord injury, neurorehabilitation, rehabilitation nursing
Copyright (c) 2026 Yuxi Peng (Author) https://creativecommons.org/licenses/by/4.0
The Safety and Effectiveness of mRNA Vaccines in Large-scale Vaccination: A Systematic Review Based on COVID-19 and Flu Vaccines
The COVID -19 pandemic has driven the large -scale deployment of mRNA vaccines. Despite the positive outcomes observed in initial clinical trials, in-depth, comprehensive assessments of the safety and efficacy of these vaccines across different populations r emain necessary following mass vaccination. This systematic review focuses on mRNA vaccines against COVID -19 and influenza, evaluating vaccine safety by analyzing post-vaccination adverse events and assessing efficacy by examining immunogenicity dynamics and protective effects against clinical endpoints. The findings indicate that these vaccines have high initial efficacy but wane over time, necessitating booster doses. The overall safety profile is favorable, with injection site reactions and systemic symptoms as the most common adverse reactions, and the incidence of rare adverse events shows age- and gender -related disparities. This study provides a reference for public health decision -making and vaccine development.
mRNA vaccines, COVID-19, flu vaccines, vaccine safety, vaccine effectiveness
Copyright (c) 2026 Jingni Tan (Author) https://creativecommons.org/licenses/by/4.0