Excellent Environment Research Articles

Neuroendocrine tumors of the stomach and pancreas. Possibilities of application of radiomics. Problems and solutions.

Background. Radiomics is promising tool contributing to the diagnosis and treatment of neuroendocrine neoplasms of various localizations. This method is often used for differential diagnosis of gastrointestinal neoplasms from other neoplasms of this localization.Aim. To demonstrate difficulties in imaging of gastrointestinal neuroendocrine tumors, as well as possibilities of radiomics in differential diagnosis.Materials and methods. Data of 12 patients with morphologically confirmed gastric neoplasms (6 - with neuroendocrine tumor, 6 - with adenocarcinoma) and data of 22 patients with morphologically confirmed pancreatic neoplasms (11 - with neuroendocrine tumor, 11 - with adenocarcinoma) who underwent CT examination of abdominal cavity organs with intravenous contrast before treatment at the Russian Scientific Center of Roentgenoradiology were used in this study. Radiomic features were extracted from the area of manually segmented gastric and pancreatic tumors in the native phase of the CT scans. Processing of the features and statistical analysis were performed using Microsoft Office Excel and free open-source software development environment for the R programming language - R-Studio.Results. Typical and atypical imaging features of gastric and pancreatic neuroendocrine tumors, peculiarities of contrast, localization and structure of neoplasms were demonstrated on the examples of CT scans. There were 15 radiomic features that were statistically significantly different in patients with neuroendocrine tumors and gastric adenocarcinomas. In the group of patients with neuroendocrine tumors and pancreatic adenocarcinomas, statistically significant differences were observed in 14 radiomic features.Conclusion. Neuroendocrine tumors of the stomach and pancreas are rare neoplasms that are not only clinically silent in most cases, but also difficult to visualize due to their small size and poor contrast characteristics. Texture analysis is a promising tool for the differential diagnosis of gastrointestinal neoplasms from other neoplasms of this localization, especially considering the difficulties of biopsy.

Research on Vocational Regional to Development by Vocational Education

Zhejiang province of China has a large economic aggregate, optimized industrial structure, balanced regional development pattern, transformation and upgrading of industrial layout, along with excellent business environment and urban-rural integrated development. For decades, through the training of technical talents which directly meets the needs of regional economic development; deepens the cooperation between schools and enterprises, provides skilled personnel support for economic and social development, and promotes regional cooperation and foreign cooperation. Taking Zhejiang Province as an example, this paper discusses how vocational education promotes the regional economy, and analyzes the existing problems and future prospects.

Silver Nanoparticle-Decorated Cellulose Nanocrystal Reinforced Ionic Polymer Hydrogel With High Conductivity and Environmental Tolerance for Multifunctional Sensing and Emergency Alarm System.

Conductive hydrogels hold great promise for flexible electronics. However, the simultaneous achievement of satisfactory mechanical strength, outstanding environmental tolerance, high sensitivity, and multiple sensing applications in a single conductive hydrogel remains a significant challenge. Herein, ionic polymer-based hydrogels with a double conductive network consisting of [2-(methacryloyloxy)ethyl] trimethyl ammonium chloride (DMC), 2-hydroxyethyl acrylate (HEA) and silver nanoparticle decorated cellulose nanocrystal (CNC@Ag) are prepared by a facile one-pot method. The resultant hydrogel (CDH) exhibits high stretchability, satisfactory self-adhesion, excellent environment tolerance (from -60 to 60°C), long-term stability (60 days), effective UV-shielding, and strong antibacterial properties. Significantly, the CDH hydrogel displays high conductivity and rapid response due to its double conductive network of ionic polymer and CNC@Ag. Therefore, the CDH-assembled sensor can accurately detect signals from both strain and pressure deformations, exhibiting outstanding sensitivity and reliability for human motion detection, signal transmission, object recognition, and tactile sensing. More interestingly, collaborating with a development board, the CDH-based sensor can be developed as an emergency alarm to realize prompt alarms in dangerous situations. Overall, this work presents a strategy for the fabrication of conductive hydrogel with remarkable properties, making it possible for multifunctional sensing applications in wearable electronics.

Systematic analysis of search strategies for Lμ − Lτ gauge bosons at Belle II

Extensions of the Standard Model with masses at or below the GeV scale are motivated by searches for dark matter and precision measurements in the quark and lepton flavour sectors, including that of the muon anomalous magnetic moment. An excellent experimental environment to test such light new physics is given by the Belle II experiment, which foresees to take up to 50 ab−1 of data. Here we consider a model with an additional gauged U1Lμ−Lτ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \ extrm{U}{(1)}_{L_{\\mu }-{L}_{\ au }} $$\\end{document} symmetry that introduces a neutral gauge boson, a Dark Photon, with possibly large couplings to muon- and tau-flavored leptons, including neutrinos. Dark Photon mixing with the Standard Model photon is loop induced, allowing it to couple to electrically charged fermions other than muons and taus. We systematically investigate the possible search strategies for Dark Photons with four fermion final states. We identified search channels with muons as the most promising ones, and we analyse the kinematic distributions to obtain cuts that optimise the sensitivity of Belle II searches for the Dark Photon. Summarising the sensitivities from the most promising search channels we provide a comprehensive overview of future searches at Belle II.

Optimisation of Box Girder Design of Overhead Cranes

The subject of the research presented in this article is the dimensional optimisation of the box structure of the main girder for overhead cranes, with the aim to reduce the main girder’s own weight. Described are the applied optimisation methods and also the problems arising during the optimisation process. Loss of shape stability is analysed in more detail, as well as the methods determined for a constructional proposal of the girder cross-section. The developed optimisation procedure is a combination of the calculations, performed in the MS Excel environment, with the simulation of a parametrically modelled girder realised using Dassault Systèmes SolidWorks software v. 2023. Using the example of optimisation of an overhead crane girder with a lifting capacity of 50 tons, the effectiveness of the proposed optimisation procedure is declared, where the existing overhead crane box girder is compared with the optimised cross-section of the box girder.

The Impact of Learning Experiences on Meeting Teacher Accreditation Standards: A Mixed-Methods Study

Professional Accreditation for teacher education programs is a quality assurance measure for normal universities. To clarify the factors affecting student teachers' learning and their mechanisms, a mixed-methods study was conducted on government-funded student teachers. The study found that learning experiences in areas such as clear goals, student support, appropriate assessment, teaching quality, and course organisation have varying degrees of influence on learning outcomes. The mechanisms of influence include: the combined effect of misaligned learning goals and simplified exam content hinders the improvement of learning quality; gaps in subject systems and structural shortages of teacher resources undermine the distinctive features of teacher education; and an imbalance between increasing learning challenges and insufficient student support obstructs the development of professional competencies. Therefore, universities should leverage participation in professional accreditation as an opportunity to reform teacher education curricula, build high-quality teaching teams, optimize the structure of teacher resources, and improve student support services to create an excellent training environment

Analytical procedure for determining the mass of a portfolio of bank deposits, based on the statistical synthesis of historical data at an established time interval

In the framework of this scientific research, an extensive analysis of the statistical and mathematical methods of step-by-step determination of the mass of a portfolio of bank deposits will be carried out, having a wide spectrum of historical data, which describe an evolution over time of the portfolio. This procedure includes several steps such as: obtaining historical data and conditionally extracting deposits from databases using SQL scripts and replacing the selected information in the Microsoft Excel environment to be analyzed later. Based on the data already statistically and graphically processed, mathematical models and algorithms will be used to determine the mass of the deposit portfolio, previously extracted from databases. Certainly, methods of automating the process detailed in this scientific article will also be described.

Model Building for Prediction of Valuation of Growth Stocks

It has been a great challenge for investors to evaluate growth stocks because these types of stocks are especially hard to forecast because of their inconsistencies and uncertainty. This paper establishes not only regression models, which include a regular Multivariable Linear Regression (MVLR) and a Fixed Effects (FE) Regression Model but also the application of a Panel Vector Autoregression (PVAR) Model on a dataset aiming to predict the Price-to-Sales Ratio (P/S) with several variables. Excel, Python, and Rstudio environments are used in the process of coding and model building. More specifically, Excel is used to conduct the MVLR model, Python is used for the FE model, and Rstudio is used for the PVAR model. By comparing different models of each type, the most optimized model was determined using a training set. After applying predictions with all types of models using another testing set, the best model is identified to be the best approach to the problem. Ultimately, all three models are compared. PVAR model and FE model are proved to be the more reliable ones out of the three models, because the R-squared for MVLR is 0.1859, lower than that of the FE model, 0.524, and the Mean Absolute Error (MAE) of for PVAR Model and FE model are respectfully 53.2139 and 55.1529. This project serves as a good starting point for future analysis and prediction of financial metrics like P/S ratio and is able to have great significance as it discovers some key points for the prediction of P/S value like its connection with time and entity despite the fact that the models themselves aren’t the best fit mainly caused by the limitations of data and variable access.

Durable hybrid metamaterial with hierarchically porous structure for efficient passive daytime radiative cooling

Passive daytime radiative cooling, which strongly emits heat while minimally absorbing sunlight, constitutes a promising strategy to address the energy density mismatch between solar irradiance and the low infrared radiation flux from material surfaces. However, nanoscale-precision manufacturing and the need for additional metal backing often result in low efficiency and limited applicability. Here, we present a durable hybrid metamaterial (DHM) comprising a randomly distributed inorganic dielectric particle–polymer composite with a hierarchically porous structure created via a simple phase separation method. Despite the absence of a metal backing, the DHM exhibits a broadband, high mid-infrared emissivity of 98.2 % and a high solar reflectivity of 98.0 %, enabling it to strongly radiate heat and scatter sunlight. Outdoor testing demonstrates that the DHM achieves an average cooling temperature of 9.0 °C under an average solar irradiance of 853.4 W·m−2, comparable to recently reported radiative coolers. The high electronegativity of C–F bonds in polyvinylidene fluoride–hexafluoropropylene (PVDF–HFP) and the high thermal and chemical stability of zirconium dioxide microparticles (ZrO2 MPs) endow the DHM with excellent environment durability. Moreover, the DHM provides effective and passive protection for ice and snow under sunlight exposure. Considering its outstanding cooling performance, environmental stability, and scalability, the DHM holds great promise for widespread applications in building and vehicle cooling, as well as glacier preservation efforts.

The Biocompatibility and the Effect of Titanium and PEKK on the Osseointegration of Customized Facial Implants.

The purpose of this study was to investigate the optimization of computer-aided design/computer-aided manufacturing (CAD/CAM) patient-specific implants for mandibular facial bone defects and compare the biocompatibility and osseointegration of machined titanium (Ma), Sandblasted/Large-grit/Acid-etched (SLA) titanium, and polyetherketoneketone (PEKK) facial implants. We hypothesized that the facial implants made of SLA titanium had superior osseointegration when applied to the gonial angle defect and prevented the senile atrophy of the bone. Histologic findings of the soft-tissue reaction, hard-tissue reaction, and bone-implant contact (BIC (%) of 24 Ma, SLA, and PEKK facial implants at 8 and 12 weeks were investigated. There was no statistical difference in the soft tissue reaction. Bone was formed below the periosteum in all facial implants at 12 weeks and the BIC values were significantly different at both 8 and 12 weeks (p < 0.05). Ma, SLA, and PEKK facial implants are biocompatible with osseointegration properties. SLA can enhance osseointegration and provoke minimal soft tissue reactions, making them the most suitable choice. They provide an excellent environment for bone regeneration and, over the long term, may prevent atrophy caused by an aging mandible. The bone formation between the lateral surface of the facial implant and periosteum may assist in osseointegration and stabilization.

Glucose-Water Synergy: An Organocatalytic System Driven synthesis of Benzimidazolo[2,3-b]quinazolinone and Benzothiazolo[2,3-b]quinazolinone Derivatives

Introduction: A simple and efficient one-pot synthesis of quinazolinone derivatives has been developed via a multicomponent reaction (MCR) involving the condensation of dimedone, benzaldehyde, and 2-aminobenzimidazole/2-aminobenzothiazole. Method: In this work, glucose water is used as a green, reusable, environmentally benign organocatalytic solvent system to synthesize desired products. Result: The main benefits of this one-pot method include its excellent yields, less time, cost-effectiveness, atom economy, environment benign, and easy workup. Conclusion: In conclusion, we successfully developed a green protocol for the environmentally benign synthesis of benzimidazo/benzothiazolo quinazolinones using glucose water as an organocatalytic medium.

To secure an e‐commerce system using epidemic mathematical modeling with neural network

SummarySecuring an e‐commerce system using epidemic mathematical modeling with neural networks involves adapting epidemiological principles to combat the spread of misinformation. Just like how epidemiologists track the spread of diseases through populations, we can track the dissemination of fake news through online platforms. By modeling how fake news spreads, we gain insights into its propagation patterns, enabling us to develop more effective countermeasures. Neural networks, with their ability to learn from data, play a crucial role in this process by analyzing vast amounts of information to identify and mitigate the impact of fake news. One potential disadvantage of using epidemic mathematical modeling with neural networks to secure e‐commerce systems is the complexity of the approach. The epidemic‐based recurrent long short‐term memory (E‐RLSTM) technique addresses the complexity and evolving nature of fake news propagation by leveraging the strengths of recurrent neural networks (RNNs), specifically long short‐term memory (LSTM) units, within an epidemic modeling framework. One advantage of using epidemic mathematical modeling with neural networks to secure e‐commerce systems is its proactive nature. One significant finding in employing this approach is the ability to uncover hidden connections and correlations within the data. E‐RLSTM stands out by capturing temporal dynamics and integrating epidemic parameters into its LSTM architecture, ensuring robustness and adaptability in detecting and combating fake news within e‐commerce systems, outperforming other techniques in accuracy and performance. Description of the NSL‐KDD dataset offers easy access to a valuable repository for benchmarking cyber security. Contained within are more than 120,000 authentic samples of cyber‐attacks across 41 distinct categories, providing an excellent environment for testing intrusion detection systems.

Drug-Loaded Bioscaffolds for Osteochondral Regeneration.

Osteochondral defect is a complex tissue loss disease caused by arthritis, high-energy trauma, and many other reasons. Due to the unique structural characteristics of osteochondral tissue, the repair process is sophisticated and involves the regeneration of both hyaline cartilage and subchondral bone. However, the current clinical treatments often fall short of achieving the desired outcomes. Tissue engineering bioscaffolds, especially those created via three-dimensional (3D) printing, offer promising solutions for osteochondral defects due to their precisely controllable 3D structures. The microstructure of 3D-printed bioscaffolds provides an excellent physical environment for cell adhesion and proliferation, as well as nutrient transport. Traditional 3D-printed bioscaffolds offer mere physical stimulation, while drug-loaded 3D bioscaffolds accelerate the tissue repair process by synergistically combining drug therapy with physical stimulation. In this review, the physiological characteristics of osteochondral tissue and current treatments of osteochondral defect were reviewed. Subsequently, the latest progress in drug-loaded bioscaffolds was discussed and highlighted in terms of classification, characteristics, and applications. The perspectives of scaffold design, drug control release, and biosafety were also discussed. We hope this article will serve as a valuable reference for the design and development of osteochondral regenerative bioscaffolds and pave the way for the use of drug-loaded bioscaffolds in clinical therapy.

How to drive heavily polluting companies to fulfill environmental responsibility? The synergy between environmental regulation and digital media coverage

This paper addresses the question of how environmental regulation and digital media coverage, as formal and informal external monitoring mechanisms, affect corporate environmental responsibility fulfillment. Using the data of Shanghai and Shenzhen A-share listed companies in China's heavily polluting industries, this study showed that both environmental regulation and digital media coverage significantly improve responsive and strategic environmental responsibility fulfillment. After distinguishing the media tone, it was found that positive digital media coverage promotes the fulfillment of both responsive and strategic environmental responsibilities. In contrast, negative digital media coverage only stimulates the fulfillment of responsive environmental responsibility, which reflected an asymmetrical effect of media tone. Further, the hierarchy of governance amplifies the role of environmental regulation in triggering the fulfillment of responsive environmental responsibility but weakens its value to strategic environmental responsibility. Inconsistent with our predictions, the relationship between digital media coverage and corporate environmental responsibility fulfillment could not be significantly moderated by Confucian culture. In addition, environmental regulation and digital media coverage only existed in companies with separate chairperson and manager positions, which indicated that an excellent internal governance environment is a prerequisite for external monitoring mechanisms to play a role in environmental governance. This study enriches the literature on how to drive responsive and strategic environmental responsibility by uncovering an external governance effect of environmental regulation and digital media coverage on the fulfillment of corporate environmental responsibility, and provides inspiration for multiple environmental governance actors to promote the construction of ecological civilization collaboratively.

MICROSERVICE ARCHITECTURE FOR CYBER-PHYSICAL SYSTEMS

Cyber-Physical Systems connect the physical and digital worlds. They are composed of hardware connected to the physical world, software, and potentially other types of systems. They are utilized across various industries, including robotics, healthcare, smart cities, automotive, industry, and space. These systems are very complex to design and implement. Cloud computing technologies provide an excellent environment for the Cyber-Physical Systems software and tools for maintaining and scaling the infrastructure. One of the main challenges is how to design cloud systems properly for Cyber-Physical Systems. Currently, microservice architecture is broadly used for software in the cloud. At its core, Microservices provide flexibility, availability, scalability, and independence of modules, as well as agile development and deployment processes. These advantages are well-aligned with the needs of Cyber-Physical Systems. However, many challenges still exist in implementing a microservice architecture for Cyber-Physical Systems. The challenges include complex distributed system networking, real-time data processing, microservice software architecture, microservice availability, and reliability of the system components. This paper provides a study whose primary goal is to give the main microservice architectural principles and patterns used, summarize the advantages and challenges, and improve the knowledge of the microservice architecture used for Cyber-Physical Systems. At first, a literature review of modern research papers was conducted. Then, each paper was analyzed. A summary of all selected research papers was produced. The results and conclusion sections deliver the summaries and give future research directions.

Preparation and luminescent properties research of fluoride phosphor K2NaInF6: Cr3+, Mn4+

A series of K2NaIn1-x-yF6 phosphors doped with x% Cr3+ and y% Mn4+ were synthesized using hydrothermal synthesis. The properties of K2NaInF6: Cr3+, Mn4+ phosphors were analyzed by X-ray diffraction, scanning electron microscopy, X-ray photoelectron spectroscopy, photoluminescence spectra, and other tests. The energy transfer efficiency between Cr3+ and Mn4+ is 55 % at an excitation wavelength of 470 nm. The optimal doping concentrations of Cr3+ and Mn4+ were 10 mol% and 2 mol%, respectively. The photoluminescence luminescence quantum efficiency of K2NaIn0·88F6: 0.1Cr3+, 0.02Mn4+ phosphor is 36.8 %. The concentration quenching mechanism of single-doped Cr3+ and Mn4+ is dipole-dipole interaction in K2NaInF6 phosphor. However, in the case of Cr3+-Mn4+ co-doping, the mechanism is quadrupole-quadrupole interaction. The thermal stability of the K2NaIn0·88F6: 0.1Cr3+, 0.02Mn4+ sample was examined, revealing that the luminescence intensity at 423 K remained at 75.53 % of that at 303 K. The activation energy was determined to be 0.28 eV, indicating that the sample has excellent thermal quenching property. The realization of red-light emission, from visible to near-infrared wavelengths, can be achieved through the interaction between Cr3+ and Mn4+. Red light of different wavelengths can better regulate the excellent environment required for plant growth, which is expected to be applied to plant growth.

AUV path planning in a three-dimensional marine environment based on a novel multiple swarm co-evolutionary algorithm

Autonomous underwater vehicles (AUVs) are rapidly advancing in ocean exploration. High-performance path planning techniques are essential for AUVs. Path planning for AUVs is a multi-faceted challenge, necessitating careful consideration of safety, energy consumption and the influence of sea currents to ensure the development of a high-quality trajectory that satisfies all operational criteria. Existing path planning algorithms have problems such as incomplete consideration of influencing factors, computational complexity and weak applicability. Therefore, we propose a swarm intelligence optimisation algorithm based on multiple swarm co-evolution (MCO) to address the issue of AUV path planning in a three-dimensional marine environment. First, a three-dimensional marine environment model and the corresponding path evaluation mechanism are established. Second, the MCO rule is established to ensure that the MCO has balanced exploration and exploitation capabilities. A shared dynamic optimal particle between populations is introduced to ensure information exchange between populations. In addition, the cross-integration mutation strategy has been proposed for promoting the fusion of two populations of superior genes to ensure the inheritance of superior paternal genes to the offspring. Finally, four comparison experiments are designed, and the experiments compare eight commonly used intelligent search algorithms and improved versions. The results of the experiments proved that the MCO has excellent three-dimensional marine environment path planning capability, with robustness and search capabilities superior to other swarm intelligence optimisation algorithms.

Developing carbon nitride with tailored defect structure for exceptional nonradical activation of peroxymonosulfate

The nonradical activation of peroxymonosulfate (PMS) over nonmetallic catalyst remains a significant scientific challenge. Herein, we proposed a facile stepwise calcination approach to prepare fragmented carbon nitride (CN) with three coordinate nitrogen (N3C) vacancies (VCN). The defective structure comprising vacant and disintegrated nanosheet synergistically conferred VCN abundant unpaired electrons, providing an exceptional catalytic behavior to evolve nonradical pathway in PMS activation. This featured system allowed generating nonradical reactive species with 100 % selectivity, namely, a major singlet oxygenation and a spot of VCN/PMS complex-triggered oxidation, which enabled a high effectiveness in the degradation of Acid Orange 7 (almost 100 % removal efficiency within 20 min). Impressively, the VCN was also featured with excellent environment serviceability, long-term operational performance, and desirable non-photocatalytic efficiency in the PMS-mediated nonradical oxidation. Overall, this study offers a facile strategy for tailoring CN architecture to achieve PMS nonradical activation and contributes to an efficient strategy for wastewater remediation.

BIO PROTECTIVE TREATMENT OF WOOD

The article covers issues related to biological protection of wood. It is shown that wood, especially chopped (dead) wood is exposed to both external natural factors and the action of various microorganisms. Natural factors, especially ultraviolet rays of solar radiation, change the chemical composition of wood and destroy lignin as the least stable part of wood. Wood is more intensively destroyed by various microorganisms ‒ bacteria and fungi. Wood contains many nutrients - starch, sugar, fats, compounds of nitrogen, phosphoric acid, sulfur, potassium, calcium and magnesium. All of them are an excellent environment for the settlement and reproduction of various microorganisms. It is noted that among hardwoods, beech wood is most negatively affected by microorganisms, especially in the warm period of the year. This wood is a valuable breed from which furniture, planed veneer and various parts and products in the construction industry are made. Therefore, it is very important to keep it intact and attractive for a long time by treating it with bioprotective agents. The purpose of the research is to determine the biostability of beech wood after its treatment with bioprotective agents. An analysis of the biological destruction of wood and the use of protective materials was conducted and it was established that the paucity of data to explain and describe the bioprotection process, the neglect of environmentally safe means leads to the biodestruction of wooden structures under the action of microorganisms. A bioprotective agent based on copper oxychloride, nickel sulfate and soda ash was used in a certain ratio of components. Control and treated samples of beech wood were placed in the prepared soil and after 60 days the weight loss of the samples was determined. Studies have shown that the biostability of beech wood treated with a bioprotective agent is 4.3 times higher than that of untreated samples. The idea of the reproduction of microorganisms in the material and their death has been revealed, which, accordingly, shows changes in the metabolic processes of the vital activity of microorganisms. It has been established that the use of treated surfaces oil-wax and azure reduces the biodegradation process by more than 8 times for untreated samples. Keywords: beech wood, bioprotective treatment, bioprotective agents, biostability determination method, mass loss, treatment efficiency.

Opening and Constructing Stable Lithium-ion Channels within Polymer Electrolytes.

Lithium-ion batteries play an integral role in various aspects of daily life, yet there is a pressing need to enhance their safety and cycling stability. In this study, we have successfully developed a highly secure and flexible solid-state polymer electrolyte (SPE) through the in situ polymerization of allyl acetoacetate (AAA) monomers. This SPE constructed an efficient Li+ transport channel inside and effectively improved the solid-solid interface contact of solid-state batteries to reduce interfacial impedance. Furthermore, it exhibited excellent thermal stability, an ionic conductivity of 3.82×10-4 S cm-1 at room temperature (RT), and a Li+ transport number (tLi+) of 0.66. The numerous oxygen vacancies on layered inorganic SiO2 created an excellent environment for TFSI- immobilization. Free Li+ migrated rapidly at the C=O equivalence site with the poly(allyl acetoacetate) (PAAA) matrix. Consequently, when cycled at 0.5C and RT, it displayed an initial discharge specific capacity of 140.6 mAh g-1 with a discharge specific capacity retention rate of 70 % even after 500 cycles. Similarly, when cycled at a higher rate of 5C, it demonstrated an initial discharge specific capacity of 132.3 mAh g-1 while maintaining excellent cycling stability.