Mature Technology Research Articles

ТЕХНОЛОГИЧЕСКИЙ АУДИТ ПРЕДПРИЯТИЙ В ПРОМЫШЛЕННЫХ КЛАСТЕРАХ

The subject of this study is issues related to the justification for the inclusion of various enterprises in an industrial cluster that has a multi-industry focus, including the use of wood chemical technologies for recycling waste from the forestry complex. The paper substantiates the need for mandatory technological audit of enterprises when they are included in an industrial cluster with a multi-industry focus. The existing methods of technological audit carried out at enterprises are considered, and several groups of methods for conducting technological audits that can be used at enterprises are identified. The methods of technological audit carried out at the enterprise where the levels of technology readiness are used, as well as the levels of technology maturity are investigated; methods of technological audit at the enterprise, which take into account both the external and internal environment of the business entity, taking into account their impact on the level of its technological development. Methods based on conducting a comprehensive audit of an enterprise are considered, including interrelated specialized audits: commercial audit; technical and technological audit; institutional audit; social audit; economic audit; risk audit; financial audit; technology audit methods, which are carried out only at a certain stage of the life cycle of an economic entity; technology audit techniques that determine the discrepancy between the functional and cost components in the activities of the enterprise. The result of the study was the development of strategic analysis matrices, which allows, based on the methodology of the level of technology readiness, to justify the decision to include an economic entity at a certain level of technological development in the industrial cluster of a multi-industry focus.

The Spatial Pattern of Polluting Enterprises and the Effects of Local Regulation in the Guanzhong Plain Urban Agglomeration

In the context of actively undertaking the transfer of domestic and foreign industries in the central and western regions of China, local regulatory behaviors influence the spatial distribution of polluting enterprises (PEs). This study examined the Guanzhong Plain urban agglomeration (GPUA), the largest urban agglomeration in the northwest region of China and one of the main regions that undertakes industrial transfer, using kernel density estimation and geographically and temporally weighted regression to explore the spatial pattern characteristics and evolution of PEs and reveal the effects of local regulatory behaviors, including environmental regulation (ER) and local protection (LP). The results indicate that (1) The distribution of the PEs tended towards energy and mineral resources and agglomerated along the development axes, aligning with the strategic positioning of the major function-oriented zones. Agglomerated areas gradually concentrate in key development zones. Major agricultural production zones exit high-density areas, and those adjacent to high-density areas often become secondary agglomeration core areas. Key ecological functional zones do not form high-density areas. (2) Both ER and LP have a positive impact on the distribution of PEs, and the dominant influence shifts from ER to LP. Counties with strict ER have increased the tendency of PEs to exhibit a certain layout due to better pollution treatment facilities and more mature pollution control technologies. The “pollution haven effect” has not yet formed within the GPUA. (3) The role of LP was more prominent in key development zones and major agricultural production zones, whereas the role of ER was more evident in key ecological functional zones. (4) RE and LP have mutually reinforcing effects on the distribution of PEs; the “innovation compensation effect” gradually manifests, but an increase in ER leads to a decrease in regional industrial clustering. This study provides a reference value for understanding the impact of government regulation on the distribution of PEs in underdeveloped areas.

Quantifying Flexibility for a Ship Power and Energy System Design

The pace of technology maturation and the uncertainty in magnitude and characteristics of future load types on Navy ships drive the need for robust power and energy system architectures that can adapt to future perturbations in requirements. The Naval design community needs a consistent method for evaluating ship system flexibility in the early design stages when informed decision making provides the greatest opportunity to influence the system’s performance and lifecycle cost. The research presented herein develops quantitative, measurable metrics and applies them to applicable case studies for Naval power and energy system flexibility: the capability of the system to accommodate change in response to perturbations in requirements.

The role of cryogenic carbon capture in future carbon-neutral societies

Utilizing CO2 capture technologies is an essential part of achieving a future carbon-neutral Society. So far, amine-based technologies, which are the most mature post-combustion CO2 capture technologies, have been predominantly applied in large-scale CO2 capture applications. However, the cryogenic process has also been proven to be a potential CO2 capture technology suitable for large-scale applications. Cryogenic carbon capture offers two potential advantages over amine-based technology. First, the efficiency is higher and thus the energy penalty is lower. Next, the flexibility of system integration is also higher, and thus the technology carries the potential of better balancing variable renewable electricity productions. By using the software tool EnergyPLAN and dedicated scenarios of achieving a carbon-neutral Denmark, this paper quantitatively estimates these benefits. It is observed that, from a system perspective, utilizing cryogenic technologies to capture 90 % of CO2 emissions in 2045 can reduce the demand for wind power by approximately 47 %, leading to a decrease in annual system costs by nearly 45 %.

Technology transfer model oriented to industry 4.0

Goal: This study aimed to propose a Technology Transfer Model oriented to Industry 4.0 (TTM4.0). Design/methodology/approach. Initially, a systematic literature review was conducted to identify existing gaps in Technology Transfer models: Another focus of the review was to determine the requirements for technological implementations in Industry 4.0. Thus, a specific TT model was built. Then, the model was validated through case studies in Brazilian companies (slaughterhouses). The methods employed to measure data and support decisions in the context of TT4.0 were AHP, Likert scale, and Fuzzy-TOPSIS. Results: Focusing on similar results between Companies A and B, thinking about adopting Industry 4.0, the central strategic needs were product quality, reducing human error, and reducing waste. Among the main factors inhibiting the maximum interest and availability of Industry 4.0 for both companies were high investment, lack of knowledge (procedures or in general), and uncertainties in results. Results indicate Big Data Analytics and artificial intelligence technologies. Originality/value: The Poultry Industry strengthens the economy and significantly impacts the country's socioeconomic indices. Despite this, the sector has a low level of technological maturity compared to others. Regarding the TTM4.0, while other models start by recognizing opportunities and then select technologies in the market, this model prioritizes phases of organizational self-knowledge for decision-making support. A primary difference between a maturity model and a Technology Transfer model is in their scope, with the latter being broader. It encompasses technology definition, implementation, and management, rather than being limited to diagnosis.

Feasibility study of a novel digital template-guided flapless extraction for maxillary palatal impacted teeth.

With the increasing maturity of 3D printing technology, the application of digital guide template in the extraction of impacted teeth has become more sophisticated. However, for maxillary palatal deeply impacted teeth, there still exist significant clinical challenges. This experiment introduces a novel digital guide template and innovatively employs a flapless technique to explore a minimally invasive approach for the extraction of palatal deeply impacted teeth. This experiment included 40 patients diagnosed with palatal completely impacted teeth, randomly divided into an experimental group and a control group. The experimental group used the new digital guide template for flapless extraction, while the control group employed the traditional freehand flap technique. The experimental group can significantly reduce the localization time of palatally impacted teeth (P < 0.001), with total surgery times of 18.15 ± 4.88min and 22.00 ± 7.71min for the experimental and control groups, respectively (P = 0.067). Although there were no significant statistical differences between the two groups in terms of intraoperative bleeding, adjacent tooth damage, infection, or damage to nearby important anatomical structures, the experimental group showed significant improvements in postoperative pain (P < 0.05), swelling (P < 0.001), and patient satisfaction (P < 0.001) compared to the control group. Compared to traditional freehand flap surgery, flapless extraction of palatally impacted teeth guided by digital templates significantly reduces the localization time of impacted teeth and demonstrates notable advantages in some postoperative complications. Future studies with larger sample sizes are needed to substantiate the feasibility of this technique.

A cross-chain access control mechanism based on blockchain and the threshold Paillier cryptosystem

With the continuous maturation of blockchain technology and the increasing demands for various industry applications, data sharing and interoperability among different blockchain networks face significant challenges. Research on cross-chain interoperability mechanisms has facilitated data collaboration across organizations and industries, enhancing the value and utility of data. When engaging in cross-chain data interactions, access control ensures the security and privacy of data while promoting collaboration and information exchange among multiple chains. Attribute-based access control can provide fine-grained authorization support, matching complex business scenarios. However, publicly disclosed policies and attributes in a transparent blockchain network may pose privacy and security issues. To address these issues, this paper proposes a cross-heterogeneous multichain data access control scheme based on attributes and threshold homomorphic encryption, achieving fine-grained and secure cross-domain access control in cross-chain networks. This scheme uses the threshold Paillier cryptosystem to encrypt and conceal user attributes and access policies. Through smart contracts, homomorphic differential computation is performed on the ciphertext of policies and attributes, to protect data privacy. This solution leverages private key decryption shares from multiple relay nodes in the cross-chain network to jointly decrypt the computation results, providing secure access control in complex cross-chain scenarios. Security analysis and experimental results demonstrate that the proposed scheme ensures security with reasonable computational overhead, to meet the access control requirements in cross-chain networks.

Modern issues of oncofertility and oncoreproduction

The problem of the occurrence of malignant neoplasms in women of reproductive age has not only medical, but also extremely important social significance, as it affects the demographic potential of the country as a whole.The article presents an analysis of the current state of the problem of fertility and preservation of reproductive function in cancer patients. Currently, there are a sufficient number of methods of assisted reproductive technologies aimed at preserving fertility in women with cancer. Among them are the following: cryopreservation of embryos and oocytes, ovarian tissue, in vitro maturation of eggs, obtaining oocytes obtained by removing the ovaries with their subsequent maturation. In addition, auxiliary methods are also distinguished, the main purpose of which is ovarian protection: the use of gonadotropin-releasing hormone agonists, ovarian transposition, gonadal screening. Each method has its advantages and disadvantages. It should be noted that the very fact of the presence of oncological pathology makes its own adjustments to the use of each specific technique. It has been shown that in vitro maturation technology is the most optimal for the preservation and realization of reproductive function in cancer patients. One of its few disadvantages is the high cost and complexity of laboratory control and cultivation of oocytes, which undoubtedly requires highly qualified specialists and relevant experience.

Low insertion loss interposer approach for RF applications based on commercial LTCC tape, alkaline-free glass and printed metallization

Materials with high RF performance are in increasing demand due to the needs of modern telecommunications. Glass and low-temperature co-fired ceramics (LTCCs) are both interesting candidates for the design of complex signal transmission systems. Glass can be processed in large panels, and has suitable structure dimensions for silicon processing, but its multilayer capability is limited. LTCC is a mature technology for complex multilayer assemblies, but the structure dimensions and conductor line resolution are restricted by the need to use screen printing technology. The approach presented here combines the advantages of both technological domains: a thin glass sheet is bonded with no additional material to a LTCC multilayer ceramic and sintered to form a tight joint. Metallization of the glass is created using printable pastes and electroplating. Two fabrication routes are compared: etching of printed thick film metal layers, and semi-additive structuring. The results of RF measurements show a low attenuation per unit length for both types of metallization, indicating that our approach is a promising one for the integration of heterogeneous systems of RF transmission modules.

Technology readiness level assessment of carbon capture and storage technologies

The global energy sector has experienced significant expansion in recent years, driven by rising demand and technological advancements. This growth has led to both opportunities and challenges, including global warming and the need to offset global carbon emissions. A wide range of technological maturity characterizes the current state of carbon capture and storage (CCS) technologies. To efficiently navigate and accelerate the implementation of these solutions, conducting an in-depth assessment of various CCS technologies is necessary. In the literature, maturity assessment-based study of CCS technologies exists only using expert surveys. This study aimed to conduct a technology readiness level (TRL) assessment of CCS technologies with the help of a multi-faceted approach comprising a literature review, technology identification, data collection, TRL mapping, expert survey, and comparative analysis. To achieve this, 79 CCS projects from the literature were analyzed to identify growing trends in the CCS industry. The analysis shows that both pre-combustion and post-combustion capture are mature technologies achieving TRL 9, while oxy-fuel capture is ranked at TRL 7. Similarly, carbon storage technologies achieved high ranking, enhanced oil recovery (EOR) and storage in saline aquifers are fully commercial and ranked at TRL 9. Enhanced coal bed methane (ECBM) extraction is trailing at TRL 3 in the research phase. In addition, a total of 21 experts were surveyed, and their statements corroborate the conclusions of the literature review. The research concludes that post-combustion capture and EOR are the most popular CCS technologies, respectively.

Technological Maturity of Aircraft-Based Methane Sensing for Greenhouse Gas Mitigation.

Methane is a major contributor to anthropogenic greenhouse gas emissions. Identifying large sources of methane, particularly from the oil and gas sectors, will be essential for mitigating climate change. Aircraft-based methane sensing platforms can rapidly detect and quantify methane point-source emissions across large geographic regions, and play an increasingly important role in industrial methane management and greenhouse gas inventory. We independently evaluate the performance of five major methane-sensing aircraft platforms: Carbon Mapper, GHGSat-AV, Insight M, MethaneAIR, and Scientific Aviation. Over a 6 week period, we released metered gas for over 700 single-blind measurements across all five platforms to evaluate their ability to detect and quantify emissions that range from 1 to over 1,500 kg(CH4)/h. Aircraft consistently quantified releases above 10 kg(CH4)/h, and GHGSat-AV and Insight M detected emissions below 5 kg(CH4)/h. Fully blinded quantification estimates for platforms using downward-facing imaging spectrometers have parity slopes ranging from 0.76 to 1.13, with R2 values of 0.61 to 0.93; the platform using continuous air sampling has a parity slope of 0.5 (R2 = 0.93). Results demonstrate that aircraft-based methane sensing has matured since previous studies and is ready for an increasingly important role in environmental policy and regulation.

Room-temperature telecom Si:Te PIN planar photodiodes: A study on optimizing device dimensions

The lack of efficient, cost-effective, room-temperature, and silicon-based photodetectors operating at the telecom bands has posed a persistent challenge in the realm of silicon photonics. One potential solution lies in introducing an impurity band within the silicon bandgap, offering a pathway to create a silicon-based photodetector that not only meets the requirements but also benefits from seamless integration with mature CMOS technology. Here, we report on enhancing device performance by introducing geometric modifications while retaining the doping concentration, device area, and operating conditions. The modified devices showcase improved responsivities, reaching approximately 3 × 10−2 A/W at 1300 nm (O band) and 1 × 10−2 A/W at 1500 nm (C band). These values significantly surpass prior work on Si:Te planar photodetectors, demonstrating an improvement of over 30 times. The noise equivalent power however was found to unavoidably increase by one order of magnitude to 10−6 (W /Hz).

Factors Influencing Utilization of Biometrics in Private Banks in Mombasa County

Purpose: The overall goal of the research was to analyze factors influencing utilization of biometrics in the private banks in Mombasa County. Methodology: The study adopted a descriptive research design because it provided a clear outcome and the characteristics associated with it at a specific point in time. The target population for the study was 120 respondents from 20 private registered banks in Mombasa County. The study adopted stratified sampling method to select the respondents from the population. The study obtained primary data through a structured questionnaire. Responses in the questionnaires were tabulated, coded and processed using a computer Statistical Package for Social Science program. The relationship between the dependent variable and the independent variables were tested using multiple linear regression models. The data was analyzed and conclusions drawn. Descriptive and inferential statistics were used whereby the data was presented through tables Findings: The findings of the study showed that legal systems holds a positive linear relationship (r=0.412; p&lt;0.01) and significant association with utilization of biometrics in private banks. Moreover, the results indicates a p-value of 0.003 which is less than 0.01 implying that the association is highly significant. Based on the research and analysis, the study concludes that legal systems, technology maturity, demographic factors, and staff competency have a significant effect on utilization of biometrics in private banks within Mombasa County. Unique Contribution to Theory, Practice and Policy: The research was anchored on technology acceptance model. To ensure efficient utilization of biometrics within private banks in Mombasa County, it is recommended that organizations follow established legislation. Subsequently, banks should update their staff on legislation surrounding biometrics use and security.

Real-Time Microgrid Energy Scheduling Using Meta-Reinforcement Learning

With the rapid development of renewable energy and the increasing maturity of energy storage technology, microgrids are quickly becoming popular worldwide. The stochastic scheduling problem of microgrids can increase operational costs and resource wastage. In order to reduce operational costs and optimize resource utilization efficiency, the real-time scheduling of microgrids becomes particularly important. After collecting extensive data, reinforcement learning (RL) can provide good strategies. However, it cannot make quick and rational decisions in different environments. As a method with generalization ability, meta-learning can compensate for this deficiency. Therefore, this paper introduces a microgrid scheduling strategy based on RL and meta-learning. This method can quickly adapt to different environments with a small amount of training data, enabling rapid energy scheduling policy generation in the early stages of microgrid operation. This paper first establishes a microgrid model, including components such as energy storage, load, and distributed generation (DG). Then, we use a meta-reinforcement learning framework to train the initial scheduling strategy, considering the various operational constraints of the microgrid. The experimental results show that the MAML-based RL strategy has advantages in improving energy utilization and reducing operational costs in the early stages of microgrid operation. This research provides a new intelligent solution for microgrids’ efficient, stable, and economical operation in their initial stages.

On the Copyright Analysis of Artificial Intelligence Products

With the gradual maturity of artificial intelligence technology, artificial intelligence products continue to emerge in the market, which poses new challenges to the current copyright law system. In particular, whether artificial intelligence products are copyrightable is a hot and difficult issue in the current theoretical and practical circles. Based on this, there are two mainstream viewpoints in the current theoretical circle, that is, the viewpoint that supports copyright protection for artificial intelligence products from the perspective of "reader-centered", and the viewpoint that opposes copyright protection for artificial intelligence products from the perspective of author-centered". However, the question of whether artificial intelligence products can be protected by copyright involves verifying the reasonableness and forward-looking nature of the "open" regulation of copyright objects in China on one hand. On the other hand, it is also relates to determining the future legislative direction of high-level artificial intelligence. Therefore, by comparing the similarities and differences in originality between the copyright law system and the copyright law system, the conclusion is drawn that artificial intelligence products should be protected by copyright. The evaluation criteria of subject-object separation established by "reader-centered doctrine" should be adopted.

Innovation in Cocoa Fermentation: Evidence from Patent Documents and Scientific Articles

This review aims to analyze the technological and scientific applications regarding cocoa fermentation through a prospective study of patent documents and research articles. The Espacenet database was used as a patent research tool by searching both the IPC code “A23G1” and the terms “cocoa” and “ferment*”. A total of 130 documents were found—49 were related to the subject. The Scopus database was also searched for scientific articles using the terms “cocoa” and “fermentation”. A total of 812 articles were found—517 were related to the subject. Cocoa fermentation has not yet reached technological maturity, despite the growth in patent documents and scientific research observed in the last two decades. The creation of the Cacao of Excellence Program (2009), among others, has incentivized sustainability and quality in cocoa-producing countries. Brazil, Colombia, and Indonesia are leading with scientific publications in the last 5 years, despite the lack of patents filed. The United Kingdom, France, China, Canada, and Germany, despite not being cocoa-producing countries, are the main holders of the technology. Patent documents analyzed relate to food science, biotechnology, engineering, and chemistry. Microbial biotechnology has gained attention as a key factor to produce a higher-quality cocoa bean. Saccharomyces is the most frequent genus of yeast used as a starter culture in patent documents. Some patent documents propose the addition of fruits during cocoa fermentation, but a few scientific studies have been found on the matter. Overall, technological applications and scientific studies have focused on improving cocoa quality. The cocoa market is expected to increase significantly in the next few years, representing an opportunity to develop high-quality cocoa using novel fermentation techniques.

Attaining Substantially Enhanced Oxygen Evolution Reaction Rates on Ni Foam Catalysts in a Gas Diffusion Electrode Setup

Water electrolysis plays a central role in the transition to a fossil‐free society, but there are significant challenges to overcome in order to increase its availability on a large scale. Alkaline water electrolysis is a mature and scalable technology, although it has several disadvantages compared to electrolyzers working in acidic environments. In particular, the use of highly alkaline aqueous electrolytes can lead to corrosion, and the achieved current densities are relatively low. This study addresses the latter limitation by introducing a gas diffusion electrode (GDE) setup as a novel development tool that bridges the gap between research and practical applications in commercial devices such as fuel cells and electrolyzers. A high surface area Ni foam catalyst that can sustain exceptional oxygen evolution reaction (OER) current densities of up to 4 A cm−2 in a quasi‐steady‐state within our GDE setup operating in an alkaline environment is presented. The high performance of this Ni‐based benchmark catalyst is attributed to its deposition onto a mesh‐like porous transport layer (PTL) via hydrogen‐templated electrodeposition. This forms a porous foam‐like structure that augments the mass transport of the gaseous reactants at the GDE.

Risk-averse electrolyser sizing in industrial parks: An efficient stochastic-robust approach

Hydrogen is called to be one of the most important energy vectors in future energy systems. Nowadays, its use in the industry sector is prominent, finding multiple applications in fertilizer production or oil refining. In this sense, some industry sectors demand a considerable amount of hydrogen for their processes. In many cases, hydrogen must be purchased externally, which supposes a challenge due to hydrogen transportation is costly and few efficient. In this context, local hydrogen production through mature electrolysis technology may suppose an attractive alternative in industrial parks. This paper focuses on this topic, in particular, a risk-averse electrolyser sizing methodology is developed. The new approach accounts for uncertainties in electricity prices as well as local renewable generation and demand through an original hybrid stochastic-robust model. The developed uncertainty modelling is integrated into a novel four-level optimization framework, whose main result is the optimal electrolyser rated power. To efficiently attain the solution, an original hybridization of the Benders' decomposition and the Column and Constraint Generation Algorithm is proposed. The developed methodology results efficient in an illustrative three-industry park, showing that installing local hydrogen generation may reduce the amount of hydrogen purchased externally (by 38%) and project costs by 2.5%. Furthermore, increasing the robustness level leads to increase the project cost by 8%, while assuming unfavourable realization of uncertainties. Moreover, the developed tool is further validated in larger parks, involving an increasing number of industries, showing that the proposed methodology scales well with the size of the park.

Microwave-assisted pyrolysis in biomass and waste valorisation: Insights into the life-cycle assessment (LCA) and techno-economic analysis (TEA)

Microwave-assisted pyrolysis (MAP) has been perceived as a promising technology for biomass and waste conversion due to its distinctive features, including fast, even, and precise heating. This results in higher energy efficiency when compared to conventional pyrolysis via thermal heating. However, the scaling up of MAP of biomass and waste poses challenges, with investigations ongoing to uncover not only the technological aspect, but also both the environmental impacts and economic feasibility associated with this process/technology. The possible environmental impacts associated with MAP processes can be analyzed through systematic life-cycle assessment (LCA), while the economic feasibility can be evaluated via techno-economic analysis (TEA). This paper presents an overview of the current research trend in MAP and the products produced, as well as the LCA and TEA of the pyrolysis technologies. The LCA study reported a 2.5 folds reduction in energy consumption and up to 62% reduction in global warming potential. TEA study revealed that conventional pyrolysis has a greater profit for long-term assessment due to a higher maturity and less complexity technology; however, MAP may be more economically feasible in the future owing to the increased maturity and more established technology. Finally, the challenges and future perspectives for LCA and TEA in MAP are elucidated.

Artificial intelligence and complex sustainability policy problems: translating promise into practice

Addressing sustainability policy challenges requires tools that can navigate complexity for better policy processes and outcomes. Attention on Artificial Intelligence (AI) tools and expectations for their use by governments have dramatically increased over the past decade. We conducted a narrative review of academic and grey literature to investigate how AI tools are being used and adapted for policy and public sector decision-making. We found that academics, governments, and consultants expressed positive expectations about AI, arguing that AI could or should be used to address a wide range of policy challenges. However, there is much less evidence of how public decision makers are actually using AI tools or detailed insight into the outcomes of use. From our findings we draw four lessons for translating the promise of AI into practice: 1) Document and evaluate AI’s application to sustainability policy problems in the real-world; 2) Focus on existing and mature AI technologies, not speculative promises or external pressures; 3) Start with the problem to be solved, not the technology to be applied; and 4) Anticipate and adapt to the complexity of sustainability policy problems.