Major Technology Research Articles

Effects of structural design, interface optimization, and processing on the performance of lithium battery anode silicon nanomaterials

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.

Construction of Key Technology System for Mine Ecological Restoration Under System Perspective

Mine ecological restoration has experienced a long-term development process in China, in which various technologies have been constantly developing and integrating. Based on the related theoretical research and field program, the technical system of mine ecological restoration was constructed, and the characteristics of key technologies were specifically grasped. In this research, the environment, including natural elements and the spatial environment, is the object of mine ecological restoration, which requires further long-term investigation and monitoring. Therefore, natural element restoration technology, space environment restoration technology, and environmental survey and restoration monitoring technology should be considered when establishing technical systems. The research showed that： ① In mine natural element restoration, where soil and water are important, traditional technologies like pollution abatement with physical, chemical, and biological methods have been extensively used. Meanwhile, artificial soil reconstruction and multi-technology joint remediation became the main study focus in soil restoration and artificial wetlands have been gradually constructed as a new method in water restoration, covering water system restoration and pollution control. ② The two tasks of space environment restoration were geological disaster prevention and vegetation re-greening. Major technologies of the former were applied to surface mine slope treatment and mining subsidence area control, the latter of which could be divided into three technical links： vegetation selection, construction, and maintenance. Although many technologies are valid, a few frontiers need to be further pursued. ③ The mine environmental investigation and restoration monitoring were based on 3S technologies, containing GIS, GPS, and RS, all of which are developing rapidly but still have a large space for integration and innovation.

China-UK Global Health Collaboration Project on Strengthening Public Health Capacity in Sierra Leone.

Since 2016, the Chinese Center for Disease Control and Prevention has continued to conduct project to assist Sierra Leone in improving its public health capacity and building a laboratory for bacteriological and parasitic diseases. Firstly, we can understand the epidemiological characteristics, etiological characteristics and drug resistance of important infectious diseases in Africa through this project, and provide services and guarantees for the construction of the Belt and Road Initiative. Secondly, the project is to carry out scientific research cooperation on the monitoring and detection capacity of major infectious diseases, biosecurity, and prevention and control technologies for important infectious diseases. Thirdly, in order to implement the concept of "building a community with a shared future for mankind", it is important to improve the capacity of Sierra Leone and West Africa to prevent and control infectious diseases, maintain global health security, and participate in global health governance. This article reviews the implementation of the project, and summarizes the experience and shortcomings, in order to help readers achieve better results in future project practice.

The Metaverse: The Essence, Research Streams, and Potential Applications in Marketing

Objective: The objective of this article is to identify the main research streams and research gaps relating to the metaverse in management sciences, particularly in the field of marketing. Research Design & Methods: The researchers employed a systematic analysis of the literature to achieve their objective. They reviewed and examined various sources to identify the essence of the metaverse and ascertain the areas and directions of research pertaining to this concept. Findings: The metaverse is envisioned as a virtual universe comprising numerous 3D virtual worlds where consumers, their avatars, and brands coexist and interact. Initially, the metaverse concept emerged in computer games set in complex, closed universes. However, in 2021, major technology companies like Facebook determined that the metaverse would be the next stage in virtual environment development, resulting in heightened interest from both practitioners and researchers. Despite being the subject of research across multiple scientific disciplines for years, the conceptualisation of fundamental metaverse concepts and its essence remains in an early stage, lacking a consensus. Implications / Recommendations: The findings of this study emphasise the need for further research and exploration in the field of management sciences, particularly within marketing, to comprehensively understand and define the metaverse. The evolving nature of the metaverse calls for collaborative efforts from both practitioners and scientists to unravel its potential implications for businesses and consumers. Contribution: This study contributes to the existing literature by presenting a systematic analysis of the metaverse concept within the context of management sciences, focusing on marketing. By identifying gaps and highlighting key areas of investigation, the research lays the groundwork for future studies in this rapidly evolving domain.

Stock Price Prediction System LSTM Based on Deep Learning

Stock price prediction is a highly complex task due to the inherent volatility and non-linear patterns of financial markets. Recent advancements in deep learning, particularly Long Short-Term Memory (LSTM) networks, have yielded promising results in time series forecasting. This paper provides an in-depth analysis of LSTM models applied to the stock price prediction of major technology companies, including Apple (AAPL), Tesla (TSLA), Microsoft (MSFT), and Nvidia (NVDA). The study utilizes historical stock data to train and evaluate LSTM models, comparing their performance against various other regression models such as Linear Regression, Support Vector Regression (SVR), Decision Tree Regression, and Gradient Boosting Decision Trees (GBDT).The results demonstrate that the LSTM model outperforms traditional models, particularly in its ability to capture long-term dependencies and manage complex, volatile stock data. Among the companies analyzed, the LSTM model achieved the most accurate predictions for Apple, as indicated by the lowest Mean Squared Error (MSE). Tesla's predictions, while less accurate due to high volatility, still showed improvement compared to other models. In conclusion, the LSTM network proved to be the most effective method for stock price prediction in this study, particularly excelling in forecasting long-term trends and reducing prediction errors for volatile stocks.

On the Global Governance of Major Scientific and Technological Risks from the Perspective of the Chinese Path to Modernization

On the Global Governance of Major Scientific and Technological Risks from the Perspective of the Chinese Path to Modernization

Optimizing Mutual Fund Selection with Fuzzy Logic: A Case Study of Nasdaq Exchange

This study examines mutual fund performance through advanced methodologies, emphasizing fuzzy logic and the Fuzzy Sharpe Ratio. A thorough literature review highlights recent developments, such as the integration of machine learning techniques with fuzzy logic models. The research utilizes data from the Bombay Stock Exchange spanning January 1, 2024, to October 31, 2024, applying the Fuzzy Risk-Adjusted Return method. Moreover, an analysis of major technology companies reveals Alphabet Inc as the top-ranked firm, demonstrating its robust performance metrics and establishing it as a premier investment choice. Conversely, Tesla Inc ranked lowest, reflecting comparatively weaker performance. These results illustrate the competitive dynamics and varied performance levels among leading tech companies, influenced by market strategy, innovation, and financial stability. This analysis underscores the value of fuzzy logic in enhancing mutual fund evaluations and positions Alphabet Inc as a strong candidate for investor consideration.

Analysis of High-Voltage Holding Capability for CRAFT NNBI Negative Ion Source with 400 kV

CRAFT (Comprehensive Research Facility for Fusion Technology) is a large scientific device that is preferentially deployed for the construction of major national science and technology infrastructures. A negative ion–based neutral beam injection system with a beam energy of 400 keV, a beam power of 2 MW, and a beam duration of 100 s, it was designed to deliver an energetic neutral beam for fusion research. Among the crucial components of this system, the high-power negative ion source stands out, and the voltage holding capability of its accelerator with double-stage is a commonly encountered issue. To address this concern, a comprehensive investigation has been conducted that focused on the gaps between the acceleration grids and grid supports in terms of voltage holding capability utilizing empirical formulas. The results of this investigation revealed that an acceleration gap of 81 mm and a grid support gap of 65 mm can be achieved through the implementation of empirical formulas, which aligns with the requirement of 200 kV for each stage. In addition, the preliminary experimental results showed that the voltage holding capability of the adjacent grids can reach up to 200 kV when the gap between the adjacent grids was designed to be 90 mm. These findings provide a foundation for the subsequent design of a high-power ion source characterized by both high energy and a large area.

The urban-tech feedback loop: A surveillance and development data-walk in South Lake Union

In this research article, we employed an autoethnographic data-walk methodology to explore the complex relationship between urban spaces and digital data collection, using the South Lake Union neighborhood as a case study. We examined how major technology companies like Amazon, Microsoft, and various property developers leverage the dual forces of urbanization and data gathering to shape urban environments in ways that serve their interests. Our key contribution lies in uncovering the power dynamics at play, where tech companies exert significant influence over urban planning and governance, reshaping cities into spaces designed for surveillance and commodification. In areas like South Lake Union, the redevelopment into numerous small storefronts enables the granular tracking of consumer behavior, turning everyday activities into data that fuels targeted advertising and capital accumulation. We identify two central insights. First, data-walks offer a way to “story” the influence of tech corporations on urban spaces from the perspective of everyday experiences. While digital data collection is integral to capital accumulation, the process is uneven and must be viewed from various angles—including from the perspective of everyday life—to fully understand the emerging inequalities. Second, we argue that the transformation of urban environments under tech capitalism exacerbates existing social and spatial inequalities while generating new ones. The commodified surveillance of daily activities and consumption not only drives data accumulation but also reshapes the physical and social fabric of the city. This work serves as an initial step in challenging these unequal processes of surveillance-driven urban development.

A Quasi-Solid-State Polymer Lithium-Metal Battery with Minimal Excess Lithium, Ultrathin Separator, and High-Mass Loading NMC811 Cathode.

Solid-state batteries with lithium metal anodes are considered the next major technology leap with respect to today's lithium-ion batteries, as they promise a significant increase in energy density. Expectations for solid-state batteries from the automotive and aviation sectors are high, but their implementation in industrial production remains challenging. Here, we report a solid-state lithium-metal battery enabled by a polymer electrolyte consisting of a poly(DMADAFSI) cationic polymer and LiFSI in Pyr13FSI as plasticizer. The polymer electrolyte is infiltrated and solidified in the pores of a commercial LiNi0.8Mn0.1Co0.1O2 (NMC811) cathode with up to 2.8 mAh cm-2 nominal areal capacity and in the pores of a 25 μm thin commercial polypropylene separator. Cathode and separator are finally laminated into a cell in combination with a commercial 20 μm thin lithium metal anode. Our demonstration of a solid-state polymer battery cycling at full nominal capacity employing exclusively commercially available components available at industrial scale represents a critical step forward toward the commercialization of a competitive all-solid-state battery technology.

Multi-object tracking using score-driven hierarchical association strategy between predicted tracklets and objects

Machine vision is one of the major technologies to guarantee intelligent robots’ human-centered embodied intelligence. Especially in the complex dynamic scene involving multi-person, Multi-Object Tracking (MOT), which can accurately identify and track specific targets, significantly influences intelligent robots’ performance regarding behavior perception and monitoring, autonomous decision-making, and providing personalized humanoid services. In order to solve the problem of targets lost and identity switches caused by the scale variations of objects and frequent overlaps during the tracking process, this paper presents a multi-object tracking method using score-driven hierarchical association strategy between predicted tracklets and objects (ScoreMOT). Firstly, a motion prediction of occluded objects based on bounding box variation (MPOBV) is proposed to estimate the position of occluded objects. MPOBV models the motion state of the object using the bounding box and confidence score. Then, a score-driven hierarchical association strategy between predicted tracklets and objects (SHAS) is proposed to correctly associate them in frequently overlapping scenarios. SHAS associates the predicted tracklets and detected objects with different confidence in different stages. The comparison results with 16 state-of-the-art methods on Multiple Object Tracking Benchmark 20 (MOT20) and DanceTrack datasets are conducted, and ScoreMOT outperforms the compared methods.

Environmental life-cycle analysis of hydrogen technology pathways in the United States

Hydrogen is a zero-carbon energy carrier with potential to decarbonize industrial and transportation sectors, but its life-cycle greenhouse gas (GHG) emissions depend on its energy supply chain and carbon management measures (e.g., carbon capture and storage). Global support for clean hydrogen production and use has recently intensified. In the United States, Congress passed several laws that incentivize the production and use of renewable and low-carbon hydrogen, such as the Bipartisan Infrastructure Law (BIL) in 2021 and the Inflation Reduction Act (IRA) in 2022, which provides tax credits of up to $3/kg depending on the carbon intensity of the produced hydrogen. A comprehensive life-cycle accounting of GHG emissions associated with hydrogen production is needed to determine the carbon intensity of hydrogen throughout its value chain. In the United States, Argonne’s R&D GREET® (Greenhouse Gases, Regulated emissions, and Energy use in Technologies) model has been widely used for hydrogen carbon intensity calculations. This paper describes the major hydrogen technology pathways considered in the United States and provides data sources and carbon intensity results for each of the hydrogen production and delivery pathways using consistent system boundaries and most recent technology performance and supply chain data.

IoT Integrated Smart Parking Zone and Website with Stand-alone System and Wireless Technology

The research project works to digitalize the full parking management system, transform the manual parking methods, solve traffic and road congestion problem and show live updates of the designated parking slots. It is ecofriendly and eliminates human interaction. It also offers personal and corporate business earnings. In the project, anyone can book time slots for parking following their convenient schedule, pay bills via the online payment system, control the entrance while entering and exit gate in the parking area with the vehicle using the website system. Users do not have to use any extra identity instrument, like- RFID Cards, QR Codes etc. The system will verify them by online credentials. Moreover, people can see the live slot updates for better security. The project collaborated with 3 major technology parts which are practical hardware, software and database system. NodeMCU, Ultrasonic Sensors, Servo motors, and other technical components are used in the hardware part. PHP, HTML, JavaScript, CSS etc. codes are implemented for the website development. Firebase Realtime Database and MySQL are integrated for the cloud and local database management with the hardware and software parts for building the IoT technology environment and infrastructure.

Development characteristics, problems and countermeasures of major scientific and technological infrastructures in the field of life sciences

The major science and technology infrastructure in the field of life science is an indispensable and important content in the large-science facility landscape. It encompasses cutting-edge, strategic, and fundamental aspects. This field differs from traditional facilities such as particle physics, astronomy and nuclear energy. Moreover, it represents a relatively underdeveloped area in China's facility landscape. Unique characteristics are observed in terms of capital investment, physical form, facility lifespan, digitization degree, organizational structure, project risk, and development effect when compared to traditional facilities. Despite its importance, challenges persist in project establishment, investment, management, and construction. Therefore, it is necessary to strengthen the condensing mechanism for addressing major scientific issues in the life science field, improve the strategic investment layout, facilitate the localization of technical equipment based on original scientific ideas, and strengthen the differentiated management capacity of life science facilities.

Analyzing the innovation ecosystem of China's major science and technology projects: From the ecological and systems science perspective

The National Major Science and Technology Projects in China are characterized by government leadership, interdisciplinary collaboration, and international cooperation. However, challenges such as insufficient innovation capacity and inadequate commercialization of scientific achievements are becoming increasingly prominent. This paper adopts the conceptual framework of natural ecology to examine these projects. By utilizing theories and methods from ecology and systems science, we draw an analogy between the innovation ecosystem of China's national major science and technology projects and the structure of ecological systems, analyzing the interrelationships among the components of the innovation ecosystem and establishing the four-level model. The findings indicate that collaboration and policy guidance among the enterprise, research, and auxiliary innovation layers promote scientific output and innovation, while the external environmental layer provides robust support and safeguards, collectively driving the development of the innovation ecosystem. We study the operational mechanisms of the innovation ecosystem in depth, identifying mechanisms of competitive symbiosis, coordination, and sharing. These mechanisms work together throughout the project management process, offering new insights for enhancing the scientific and effective management of these projects. The national innovation ecosystem and high-quality development mutually reinforce and complement each other. As a critical pathway to high-quality development, our study provides new approaches to addressing the challenges of insufficient innovation capacity and the difficulty in translating scientific achievements into practice, contributing to the optimization of resource allocation, and the deep integration of technological innovation with economic and social development.

Efficacy of a real-time intelligent quality-control system for the detection of early upper gastrointestinal neoplasms: a multicentre, single-blinded, randomised controlled trial

Oesophagogastroduodenoscopy (OGD) quality and identification of the early upper gastrointestinal (UGI) neoplasm play an important role in detecting the UGI neoplasm. However, the optimal method for quality control in daily OGD procedures is currently lacking. We aimed to evaluate the efficacy of a real-time intelligent quality-control system (IQCS), which combines OGD quality control with lesion detection of early UGI neoplasms. We performed a multicentre, single-blinded, randomised controlled trial at 6 hospitals in China. Patients aged 40-80 years old who underwent painless OGD were screened for enrolment in this study. Patients with a history of advanced UGI cancer, stenosis, or obstruction in UGI tract were excluded. Eligible subjects were randomly assigned (1:1) to either the routine or IQCS group to undergo standard OGD examination and OGD examination aided by IQCS, respectively. Patients were masked to the randomisation status. The primary outcome was the detection of early UGI neoplasms. All analyses were done on a per-protocol basis. This trial is registered with ClinicalTrials.gov, NCT04720924. Between January 16, 2021 and December 23, 2022, 1840 patients were randomised (IQCS group: 919, routine group: 921). The full analysis set consisted of 914 in the IQCS group and 915 in the routine group. The early UGI neoplasms detection rate in the IQCS group (6.1%, 56/914) was significantly higher than in the routine group (2.3%, 21/915; P=0.0001). The IQCS group had fewer blind spots (2.3 vs. 6.2, P<0.0001). The IQCS group had higher stomach cleanliness on cardia or fundus (99.5% vs. 87.9%, P<0.0001), body (98.9% vs. 88.0%, P<0.0001), angulus (99.8% vs. 88.4%, P<0.0001) and antrum or pylorus (100.0% vs. 87.4%, P<0.0001). The inspection time (576.2 vs. 574.5s, P=0.91) and biopsy rate (57.2% vs. 56.6%, P=0.83) were not different between the groups. The early UGI neoplasms detection rate in the IQCS group increased in both non-academic centres (RR=3.319, 95% CI 1.277-9.176; P=0.0094) and academic centres (RR=2.416, 95% CI 1.301-4.568; P=0.0034). The same improvements were observed for both less-experienced endoscopists (RR=2.650, 95% CI 1.330-5.410; P=0.0034) and experienced endoscopists (RR=2.710, 95% CI 1.226-6.205; P=0.010). No adverse events or serious adverse events were reported in the two groups. The IQCS improved the OGD quality and increased early UGI neoplasm detection in different hospital types and endoscopist experiences. IQCS could play an important role in primary basic hospitals and non-expert endoscopists to improve the diagnostic accuracy of early UGI neoplasms. The effectiveness of IQCS in real-world clinical settings needs a larger population validation. Key R&D Program of Shandong Province, China (Major Scientific and Technological Innovation Project), National Natural Science Foundation of China, the Taishan Scholars Program of Shandong Province, the National Key Research and Development Program of China, and the Shandong Provincial Natural Science Foundation.

PRODIGY+: a robust progressive upgrade approach for elastic optical networks

Elastic optical networks (EONs) operating in the C-band have been widely deployed worldwide. However, two major technologies—multiband elastic optical networks (MB-EONs) and space division multiplexed elastic optical networks (SDM-EONs)—can significantly increase network capacity beyond traditional EONs. A one-time greenfield deployment of these flexible-grid technologies may not be practical, as existing investments in flexible-grid EONs need to be preserved and ongoing services must face minimal disruption. Therefore, we envision the coexistence of flexible-grid, multiband, and multicore technologies during the brownfield migration. Each technology represents a tradeoff between higher capacity and greater deployment overhead, directly impacting network performance. Moreover, as traffic demands continue rising, capacity exhaustion becomes inevitable. Considering the different characteristics of these technologies, we propose a robust network planning solution called Progressive Optics Deployment and Integration for Growing Yields (PRODIGY+) to gradually migrate current C-band EONs. PRODIGY+ employs proactive measures inspired by the Swiss Cheese Model, making the network robust to traffic peaks while meeting service level agreements. The upgrade strategy enables a gradual transition to minimize migration costs while continuously supporting increasing traffic demands. We provide a detailed comparison of our proposed PRODIGY+ strategy against baseline strategies, demonstrating its superior performance.

RF technology in wireless communications:From transceiver architecture to subsystem specifications

Radiofrequency (RF) technology is essential to wireless communication.The demand for RF technology research is growing as mobile, satellite, radar, and other fields advance. In recent years, the development of 5G and 6G technologies has raised the bar for in-depth RF technology research, requiring greater frequency and data transmission efficiency, among other things. In addition to providing a brief overview of the transceiver's components, the signal chain, and an introduction to the major RF technologies, this paper will concentrate on the architecture of RF transceivers in RF systems and the specification of sub-systems. It will also include references for the RF sub-system specifications and integration techniques. The comprehensive study of communication technology will benefit greatly from an in-depth grasp of the transceiver's capabilities. Lastly, an overview of the layout and features of RF transceivers is provided, along with a prediction of the future application-focused path of RF technology.

Estimating the value of expired and active patents: A renewal model approach

ABSTRACT This study proposes an updated renewal model to estimate active patent value and technical depreciation in five major Indian technology fields. According to a study of 27,000 patents issued by the Indian Patent Office between 1998 and 2018, Indian patents have a lower value than foreign patents. This suggests that India's patenting and R&D qualities differ from those of more advanced countries. Technology-specific factors are important because technology fields depreciate at different rates. The top 5% of patents accounted for most international and domestic patent values. A genetic algorithm is used to optimise the renewal model accuracy. This study has significant implications for Indian policymakers, patent holders, international investors, and technology market participants. This model allows startups and new businesses who want to value their IP at the very early stage to negotiate with their counterpart when licensing or selling the patents.

Benchmark and Roadmap for Low Temperature Water Electrolysis for Green H2 Production and Applications

Water electrolysis has attracted world-wide attention due to its ability to produce green hydrogen when coupled with renewable electricity. Green hydrogen is a viable solution to decarbonizing a variety of industries including fertilizer, metal production, petrochemical, and synthetic fuels. There are three major low temperature water electrolysis technologies, alkaline water electrolyzer (AWE), proton exchange membrane water electrolyzer (PEMWE), and anion exchange membrane water electrolyzer (AEMWE). This work will first provide the status of these three technologies in terms of operating conditions, lifetime, and capital cost. Subsequently, the challenges and constraints for these technologies will be discussed in the scenarios of large-scale manufacturing and integration with intermittent renewables. More efforts will be made to illustrate the trajectory of the next-gen water electrolysis technologies, which feature at ultralow PGM or PGM-free catalysts, thin membranes with reduced hydrogen crossover, high-current high-power operation, long lifetime, and remarkable cost reduction. The work will also address the challenges of automated MEA fabrication and stack manufacturing at scale. Finally, a real example of renewable wind turbine integrated with water electrolyzer to produce green hydrogen and subsequently green ammonia will be demonstrated.