bluuebunny/crossref_metadata_2025 huggingface dataset:
KAP ANALYSIS AMONG NURSES WORKING IN A TERTIARY CARE HOSPITAL REGARDING PATIENT SAFETY
Authors: ASAD . , SAMREEN S , YASMEEN T , AKHTAR S , BANO S
Published: January 2025

Patient safety is a critical aspect of healthcare quality, requiring healthcare professionals, particularly nurses, to possess adequate knowledge, maintain a positive attitude, and adhere to safe practices. This study evaluates the knowledge, attitudes, and practices of nurses regarding patient safety in a tertiary care setting. Objective: To assess the knowledge, attitudes, and practices of nurses regarding patient safety at a tertiary care hospital. Methods: A cross-sectional study was conducted in the Nursing Department of Nishtar Hospital, Multan from October 2023 to October 2024. A total of 100 nurses from all departments with at least one year of working experience and a bachelor’s degree were included in the study. A 42-item questionnaire containing four sections was employed to assess participants. Results: The mean knowledge score was 8.9 ± 1.43 among which 60% had good knowledge and 40% had poor knowledge about patient safety. The mean attitude score was 56.59 ± 10.23 among which 59% had a positive attitude and 41% had a negative attitude. The mean practice score was 5.71 ± 1.65 among which 60% had good practices and 40% had poor practices. Multiple regression analysis showed that knowledge score has no significant predictors. However, age and knowledge of patient safety during education were significantly associated with attitudes. Knowledge of patient safety during education was also significantly associated with practices. Conclusion: The knowledge, attitudes, and practices regarding patient safety were satisfactory in nurses working in tertiary care hospitals. However, improvements are required in hospital culture and policies to enhance patient care.
Análisis de la dirigencia deportiva en México - ¿La persona adecuada para el puesto adecuado?
Authors: Aguilera Rivera Alberto Rafael
Published: January 2025

Introducción: son múltiples las razones que revisten de  importancia al proceso de contar con directivos competentes y profesionales en las organizaciones deportivas de México; una de ellas es que la gestión efectiva de éstas depende en gran medida de la capacidad, habilidades, competencias  y conocimientos que éstos posean.  El objetivo del artículo es exponer el perfil de los encargados de dirigir las entidades deportivas del país en el sector público, privado y social, destacando dos elementos: estudios y experiencia en el área como perfil ideal. Materiales y método: en México no existe investigación académica que detalle el perfil de estos líderes,  lo poco que hay proviene de artículos periodísticos que tratan el tema. Este estudio pretende llenar ese vacío al analizar las hojas de vida y currículos de directivos del sector social, de los entes privados del futbol, beisbol y basquetbol y de los tres niveles de gobierno federal, estatal y  de la ciudad  de México considerada la más importante del país; este análisis empleo la técnica exploratoria de revisión documental digital de los currículos para realizar una descripción cualitativa y cuantitativa de la situación y obtuvo como respuesta bajos perfiles en el espacio público y privado y aceptables en el social. La discusión atraviesa la relación de una mala selección de directivos dados la falta de perfiles adecuados y su consecuencia, principalmente, en los logros organizacionales. Concluyendo en la necesidad de un desarrollo de perfiles acordes a los entes deportivos y a una selección más racional de los mismos.
Mecp2: An Important Role in the Pathogenesis of RETT Syndrome
Authors: Zhou Yujia
Published: January 2025

RETT syndrome is an X-chromosome-linked neurodevelopmental disorder mainly affecting female children, and its pathogenesis is mainly related to mutations in the Mecp2. In recent years, the role of Mecp2 in neurodevelopment and its relationship with RETT syndrome has become a hot research topic. Current research is focused on the effects of Mecp2 mutations on neuronal function and neural circuits, as well as exploring potential therapeutic approaches in animal models. Despite the results achieved, there are still gaps in the understanding of the precise molecular mechanisms of the Mecp2, gender specificity and the role of non-coding RNAs. This paper analyzed the role of Mecp2 in neurodevelopment and its relationship with Rett syndrome, and explored the molecular mechanisms and potential therapeutic strategies for Mecp2 mutations. It was found that Mecp2 mutations lead to neurological dysfunction by affecting neuronal differentiation and synaptic plasticity. In addition, this paper evaluates the current prospects for gene therapy, noting that adeno-associated viral vectors (AAV) have shown favorable therapeutic effects in animal experiments. This paper provides new insights into understanding the pathogenic mechanism of the Mecp2 in RETT syndrome and provides an important reference for future therapeutic strategies. However, the precise molecular mechanism of the Mecp2 and its gender-specific differences still need further investigation. Future studies could focus on developing safer and more effective gene therapies and exploring the role of non-coding RNAs in RETT syndrome with a view to achieving more comprehensive therapeutic strategies
The application value assessment of CRISPR in screening and optimizing bacteria for industrial production
Authors: Yuan Kangjun
Published: January 2025

CRISPR is a gene editing technology derived from bacteria and has been widely used in the current biological field. However, the use range of it is still mainly in laboratories. The industrial production field can rarely see its role, such as the screening and optimization of production strains. This article compares the advantages and disadvantages of CRISPR with traditional natural sampling or mutagenesis breeding combined with selective culture medium screening technology in actual production in technical and non-technical fields, emphasizing that CRISPR technology has great advantages in integrating excellent traits and improving breeding efficiency. However, it is still slightly inferior to traditional technology in terms of breeding costs, experimental conditions, and social acceptance. The significance of this study lies in a relatively comprehensive analysis of the various indicators worth comparing when CRISPR technology is actually applied to industrial breeding, which can provide a certain reference value for whether the technology should be officially put into industrial use. However, there are still many defects of CRISPR technology which is difficult to correct; although the direction of its improvement is fairly clear, its never easy to work, and the development will still need some time.
The feasibility of combining immune checkpoint inhibitors with cancer-related fibroblasts for the treatment of tumors
Authors: Liu Muyao
Published: January 2025

In tumor therapy, immune checkpoint inhibitors (ICIs) are widely utilized. However, in most cases, patients with colorectal cancer and breast cancer have a low response rate to ICIs monotherapy. By directly or indirectly inhibiting T cells, Cancer-associated fibroblasts (CAFs) impact the immune response against tumors and immune cells' sensitivity to immune checkpoints. At present, the research on targeted CAFs for tumor treatment has become a hot topic. This paper analyzed the mechanism of immune resistance to ICIs in some tumor patients, found that CAFs promoted the formation of immune resistance in patients, and analyzed two ways of targeting CAFs to inhibit tumor progression and found that the drug GKT137831 could restore the sensitivity of patients to ICIs by inhibiting CAFs. The combined treatment of ICIs and CAFs provides a reference for the clinical treatment of tumors. However, CAFs are a highly heterogeneous cell population, so it is necessary to find more precise CAFs targeting drugs to enhance tumor immunogenicity and improve tumor sensitivity to ICIs through combination therapy.
Global strategies against COVID-19: The role of public health measures, vaccination, and technology
Authors: Wang Kaixian
Published: January 2025

This essay describes the global response to the COVID-19 pandemic, focusing on its virus characteristic, public health strategies employed, and the role of vaccination and technology in the management of the crisis. Back in March 2020, the COVID-19 virus was declared a pandemic by the World Health Organization, which required the international community's collaboration to reduce the health impact of the virus. This essay exposes how SARS-CoV-2 spreads, the complications of asymptomatic transmission, and its mutations, which further complicate the efforts to contain it. The very basic early detection through testing, protection by social distancing and wearing masks, and wide vaccination were the fundamental strategies that had kept the pandemic in control. It was vaccination, with an emphasis on vaccines based on mRNA, that proved to be key in the fight against severe diseases and in lightening the load of health services. The essay identifies that the vaccines represent a big scientific milestone and show promise for the future treatments beyond infectious diseases. Besides, big data, tracking technology, international cooperation were all important technologies to help manage the crisis.
The Application of Stochastic Processes in Financial Mathematics
Authors: Yang Xibin
Published: January 2025

Stochastic processes are crucial in financial mathematics, providing a framework to model the inherent uncertainties of financial markets. This paper explores stochastic process application across various financial domains, such as option pricing, risk management, and financial engineering. Through case studies, literature review, and case analysis, the study demonstrates the practical effectiveness of stochastic processes in finance. The findings highlight the adaptability and robustness of these models in capturing market dynamics and optimizing financial strategies. This research particularly focuses on the implementation of Brownian motion and Its processes in derivative pricing, revealing significant improvements in accuracy compared to traditional methods. Additionally, we examine the integration of machine learning techniques with stochastic models to enhance predictive capabilities in risk assessment. This study also addresses the challenges and limitations of current stochastic approaches, proposing innovative solutions for practical implementation. These insights contribute to both theoretical understanding and practical applications in quantitative finance, offering valuable guidance for practitioners and researchers in the field
Exploring Public Health Strategies Related to Chronic Diseases: Taking Type 2 Diabetes as an Example
Authors: Pi Zechen
Published: January 2025

As life becomes better and food becomes more abundant, the number of people with some nutritional and chronic diseases is also rising. In order to enhance people's health status, China, the nation with the highest number of diabetics worldwide, needs to identify the best disease prevention and control procedure within the "prevention-health care-treatment-diagnosis-rehabilitation" cycle of the health management system. Population-based public health should dominate here. In today's era of big data, China has opened a smart health management system that is "combined with science and technology", gradually improving the informatization and intelligence level of chronic disease detection and management, so as to empower the health management cycle. In current studies, not enough attention has been paid to disease prevention and control. Taking type 2 diabetes mellitus as an example, this paper discusses the public health strategies related to chronic diseases based on the analysis of literature research survey data, summarizes the public health policies related to diseases at home and abroad, puts the policy methods and importance of disease prevention and control under the objective data test, analyzes its limitations, and helps to optimize the measures in the future.
Mechanism and Treatment of the Rotator Cuff Tear
Authors: Sui Xuansheng
Published: January 2025

Among all the joints in the human body, the shoulder has the highest degree of motion, but its stability is relatively limited. As the population ages more rapidly, rotator cuff tear has become the most affected muscle and joint pain lesions in middle-aged and elderly patients and the prevalence rate is increasing year by year. According to imaging studies, rotator cuff injuries affect 30% of asymptomatic adults over 60 and 65% of asymptomatic adults over 70. The rotator cuff tear made pain to the patients, reduced joint range of motion and stability, joint dysfunction. So, the people more and more attach importance to rotator cuff tear. This paper summarizes in recent years about risk factors, mechanism and the treatment of rotator cuff tear, which hope to accelerate the treatment of diseases, which can made partial or complete layer tears. Due to the diversity of rotator cuff tear classification, future studies should be carried out with specific tear size or tear degree.
Advancing Mathematical Optimization Methods: Applications, Challenges, and Future Directions
Authors: Zou Yiyang
Published: January 2025

Mathematical optimization methods have seen substantial advancements and applications in diverse fields, including industry, agriculture, commerce, and scientific research, due to advances in computer science and artificial intelligence. These methods improve production efficiency, resource allocation, and structural optimization. This paper reviews key optimization techniques such as gradient descent, Newtons method, and heuristic algorithms, discussing their advantages, limitations, and applicability. Although optimization methods offer powerful tools for solving complex equations and optimizing solutions, real-world scenarios often introduce challenges such as computational errors and model idealizations. The future of mathematical optimization lies in improving algorithm speed, usability, and accuracy, allowing broader accessibility and aligning solutions with practical realities. This exploration highlights both the current utility and the evolving potential of optimization techniques in addressing global challenges
Research on Advertising Prediction Based on Stacking Ensemble Algorithms
Authors: Fang Sirui
Published: January 2025

The purpose of advertising prediction is to analyze user behavior and features to forecast the effectiveness of ad placements, thereby achieving a higher return on investment. This paper employs a stacking-based ensemble learning method, integrating multiple machine learning algorithms to enhance predictive capabilities. To support this method, this article selected a dataset related to advertising click through rate (CTR). The paper constructs two models: Gradient Boosting Decision Tree (GBDT) and eXtreme Gradient Boosting (XGBoost). Then the paper utilizes Bayesian optimization to tune the model parameters to achieve optimal parameter combinations. The paper uses these two individual models as base learners in a stacking ensemble model, with a random forest model serving as the meta-learner for training. This paper evaluates the predictive performance of the models using two metrics: log loss value, and AUC value. After experimental evaluation, the AUC value of the Stack fusion model reached 0.9999, which is about 0.42%, 1.29%, and 10.99% higher than XGBoost (0.9956), Random Forest (0.9871), and GBDT (0.8904), respectively. In terms of logloss value, the Stack fusion model has a loss of 0.0101, significantly lower than XGBoost's 0.0595, a decrease of about 83.01%. Compared to the random forest's 0.1896 and GBDT's 0.1884, it decreased by approximately 94.67% and 94.64%, respectively. This result indicates that the ensemble model proposed in this paper demonstrates a significant improvement in click-through rate prediction when contrasted with individual models.
Inference of Behavioral Decision-Making Using AI and Statistical Data Analysis in the Big Data Environment
Authors: Wang Keying
Published: January 2025

Big data are of essence to enhance the accuracy of making decisions and in improving the ability to forecast. However, working with large and complicated datasets, the traditional methods of analyzing data tend to be grossly inadequate. It is at this point, amongst others, that artificial intelligence has now presented a feasible solution to such limitations, especially with the model called machine learning. Based on that, this research will look into the aspect of integration between artificial intelligence and statistical methods of analysis in inferring behavioral decisions from big data. This work considers a number of datasets related to marketing, health care, and finance, comparing the efficiency of the application of a range of artificial intelligence (AI) models, especially random forests, Long Short Term Memory (LSTM), and convolutional neural network (CNN) algorithms, against the classical statistical ones. Standard performance evaluation indicators apply: accuracy, precision, recall rate, F1 score are applied in the model. Results have shown that, though model interpretability and overfitting are challenges, the predictive accuracy of artificial intelligence models is somewhat better in comparison with conventional statistical methods. The present study underlines the transformative potential of AI in changing decision-making across many industries but also highlights key areas for further improvement on behalf of real-time processing abilities and ethical deployment consideration.
History and Future Development of Morphing-Wing Aircrafts
Authors: Zhu Hongchang
Published: January 2025

Morphing-wing aircraft can alter the shape of their wings to achieve different flight performances. Such changes are made to achieve the optimum aerodynamic profile for the current flight environment. The morphing wings greatly improve the flight efficiency and reduces the energy loss in different environments. Morphing designs can be categorized into three distinct types based on their fundamental mechanisms: rotation of specific segments or the entire wing, telescoping, and inflation of particular components or the entire wing. With the continuous technological innovation and practical applications, many famous type of morphing-wing aircrafts have left marks in humans aviation history. Although morphing-wing aircrafts have been shown to be mostly withdrawn from service, the research on morphing-wing aircraft has promoted the development of aviation technology and provided valuable reference for the design of modern fighter aircraft. In order to speculate on the future development of morphing-wing aircraft design, this article overviews the history of morphing-wing aircraft, analyses the reasons for the abandonment of morphing-wing design, and finally discusses the potential trend of morphing-wing aircraft. This article may offer a reference for the design of aircraft.
Impact of Aerodynamic Design on Vehicle Performance and Vortex Wake Flow
Authors: Fang Yucheng
Published: January 2025

This thesis examines vortex and wake formation mechanisms in automotive aerodynamics and their impact on vehicle performance, emphasizing strategies to mitigate adverse airflow effects through optimal design and computational techniques. It demonstrates that vortices and wake turbulence elevate drag, diminish fuel efficiency, and compromise high-speed vehicle stability. Streamlined body design, optimized rear-end shape, and underbody airflow management can effectively reduce wake turbulence and vortex intensity, enhancing aerodynamic performance. This paper also introduces a variety of computational techniques, including theoretical analysis, wind tunnel experiments and Computational Fluid Dynamics (CFD), and explores the application of these methods in the real-world design process. CFD simulation demonstrates its advantages in evaluating airflow characteristics and optimising design solutions, enabling engineers to carry out efficient iterative design. Future research directions include the application of active aerodynamic systems and the integration of intelligent design algorithms for more efficient airflow control and vehicle performance enhancement.
A Deep Dive into Black Hole Spin Measurement Using Continuum Fitting
Authors: Wang Qixuan
Published: January 2025

This paper explores the continuum fitting method for estimating the spin of stellar-mass black holes in X-ray binaries. By fitting the thermal emission created by the accretion disk to theoretical models, this method provides a precise and accessible way to estimate the spin of black holes. Key developments, including the use of KERRBB and SIMPL models, improve accuracy by accounting for disk structure and Compton scattering effects. This paper reviews recent applications of this technique and compare it to the X-ray reflection method, noting that continuum fitting is highly accurate for black holes with strong thermal emission. This paper also gives the new spin measurement of some black hole, especially the Cygnus X-1, that has the spin a_*>0.976, but also use it to prove that the continuum fitting method which relies heavily on knowing the black holes three parameters. Finally, this paper discusses both the advantages and challenges of this method, with an expectation of future improvements in modeling and observations that can expand its use.
Morse Theory, Discrete Morse Theory and Applications
Authors: Dong Zexuan
Published: January 2025

By employing a specific class of smooth functions to study a space, Morse theory establishes deep connections between analysis and topology. It is a classical subject of pure mathematics, originally pioneered by Marston Morse in the 1920s. In this article, we use Morse theory to present a proof of an interesting result on the knots, known as the Fry-Milnor theorem. We also discuss discrete Morse theory, a subject of applied mathematics developed by Robin Forman in the 1990s, and its application. We focus on elucidating especially the inherent similarity between classical Morse theory and discrete Morse theory
Progress of the Exercise Therapy on Chronic Ankle Instability
Authors: Ren Huaiyu
Published: January 2025

This research delves into the effectiveness of various exercise therapies for Chronic Ankle Instability (CAI), a condition that frequently develops when initial ankle sprains are not adequately treated. CAI is characterized by repetitive sprains, joint instability, and reduced mobility, which can severely impact an individual's daily activities and sports performance. Different methods of rehabilitation, including muscle strengthening exercises, proprioceptive training, and balance improvement, were evaluated. The study emphasizes the advantages of combining traditional approaches such as resistance band exercises and newer techniques like blood flow restriction (BFR) training. These methods help enhance both strength and functionality in patients with CAI. Additionally, integrating proprioceptive exercises that focus on improving balance through unstable surface training has shown significant progress in restoring postural stability. Further, novel therapeutic interventions, including motor imagery, transcranial direct current stimulation (tDCS), and exergaming, demonstrate promising results in complementing traditional treatments. Ultimately, this review suggests a comprehensive rehabilitation plan that merges conventional and modern therapies to improve functional outcomes for individuals with CAI, though further research is necessary to optimize the combination of these therapies for long-term efficacy.
Using Arduino Uno and EMG Electrodes for Electromyographic Signal Measurement and Servo Control
Authors: Liu Wenkai
Published: January 2025

This paper explores the integration of Arduino Uno with surface electromyography (sEMG) electrodes for measuring muscle electrical activity and controlling servo motors based on these signals. By analyzing electromyographic signals from various hand postures, such as opening and closing, signal variations were thoroughly evaluated. The study implements a servo control mechanism that adjusts the servo motors position based on computed root mean square (RMS) voltage values derived from EMG signals. The experimental results demonstrate that the servo control system effectively mirrors hand movements, providing a feasible solution for biomedical applications and human-machine interfaces. This research highlights the potential for using affordable hardware for sophisticated control systems and suggests future enhancements to improve system accuracy and applicability.
Combinational Equivalence Checking on AIGs
Authors: Tang Lehua
Published: January 2025

Combinational Equivalence Checking (CEC) is a critical process in digital circuit design, ensuring that two versions of a circuit are functionally equivalent. Functionally Reduced And-Inverter Graphs (FRAIGs) are a data structure extensively used in CEC, representing Boolean functions as directed acyclic graphs with AND gates and inverters. The main advantage of FRAIGs is their ability to integrate structural hashing with functional reduction, allowing for the elimination of functionally equivalent nodes during graph construction. However, conventional FRAIG approaches face challenges with scalability in complex circuits. To overcome these limitations, we propose three novel methods: improved sampling techniques that refine random simulation and SAT-based methods for early identification of equivalent nodes; advanced graph partitioning strategies that enable parallel processing and localized equivalence checking to accelerate computation; and support node analysis combined with probability distribution modeling to reduce unnecessary checks. Extensive experiments show the effectiveness and efficiency of our proposed methods
The Development and Application of Neuromorphic Silicon Neural Circuits
Authors: Zheng Yiheng
Published: January 2025

Silicon-based neuronal circuits, inspired by biomimetic principles, have garnered increasing scholarly interest and investigation. Building on the field of neuromorphic engineering, which focuses on designing and emulating circuits and systems that mimic the neural architecture of biological nervous systems, this study addresses high-speed modeling of large-scale neural systems and real-time applications of bio-inspired neural systems. The manuscript delineates the prevalent architectural components and methodologies for the fabrication of such circuits, offering a comprehensive survey of various neuromorphic silicon neurons (SiNs) that instantiate diverse computational paradigms. Additionally, the paper delves into the fundamental principles of competitive circuits, discussing and explaining their operational mechanisms and derivative applications. By comparing different design methodologies for basic circuits, it demonstrates how different fundamental circuits can be applied to implement spiking silicon neurons in various research fields. The study ultimately focuses on the sub-threshold operating region of these circuits and showcases the practical value of silicon neuron circuits through integrated circuits and vary-large-scale neural networks (VLSI) chip implementations. This approach highlights the potential of neuromorphic systems in achieving efficient and biologically plausible neural emulation
Solving Differential Equations with Physics-Informed Neural Networks
Authors: Dong Chenghao
Published: January 2025

Solving differential equations is an extensive topic in various fields, such as fluid mechanics and mathematical finance. The recent resurgence in deep neural networks has opened up a brand new track for numerically solving these equations, with the potential to better deal with nonlinear problems and overcome the curse of dimensionality. The Physics-Informed Neural Network (PINN) is one of the fundamental attempts to solve differential equations using deep learning techniques. This paper aims to briefly review the application of PINNs and their variants in solving differential equations through a few simple examples, and to provide practitioners interested in this direction with a quick introduction to the relevant topic
A Design Study on Polarized Beam Splitter for Visible Light
Authors: Yang Liuqing
Published: January 2025

This study employs the thin film design software TFCale to successfully design and realize a high-efficiency polarization beam splitter suitable for the visible light wavelength range of 400-700 nm, with incident angles between 40 and 50. The design objective was to achieve near 100% reflectance for S-polarized light and near 100% transmittance for P-polarized light. By optimizing the refractive index, thickness, and multilayer structure of the thin film materials, we achieved high-performance optical characteristics. During the design process, we conducted an in-depth investigation of the optical constants of various materials and combined the interference effects of multilayer films to ensure the desired polarization splitting effect within the specified range of incident angles. Simulation results indicate that the film exhibits high-efficiency polarization separation across the entire visible spectrum: the reflectance of S-polarized light remains above 80% within a certain angular range, and the transmittance of P-polarized light also remains above 80%. This high-efficiency polarization beam splitter has broad application prospects in optical instruments, laser systems, display technologies, and other fields requiring precise polarization control. Its superior performance not only enhances the efficiency and accuracy of optical systems but also provides valuable references for future optical thin film design. The study demonstrates that using TFCale for thin film design is an effective method to meet complex optical performance requirements and offers reliable solutions for practical applications
GLP-1 Therapy in Cancer and Its Mechanism
Authors: Zhang Baowen , Zhang Jingyi
Published: January 2025

L-advocating cells generate the hormone glucagon-like peptide-1 (GLP-1), which is important for weight loss and the management of type 2 diabetes mellitus (T2DM).Recent studies have shown that it also reduces the risk of cardiovascular disease, reduces high blood pressure and other effects. In addition, it also has the effect of improving fatty liver, polycystic ovary syndrome. But when it comes to cancer, there are still gaps in its biological effects and mechanisms of action. In order to determine the indirect inhibitory effect of GLP-1RA on cancer as well as the metabolic regulation mechanisms of the cancer microenvironment by directly acting on the PI3K/AKT and ERK/MARK pathways, this paper analyzed studies on GLP-1 and its receptor agonist (GLP-1RA) in lowering cancer prevalence and inhibiting cancer. In turn, it effectively inhibits prostate cancer (PCa), ovarian cancer (OC) and other cancers. This study provides a reference for the indirect and direct mechanisms of GLP-1 and GLP-1RA in reducing cancer prevalence and inhibiting cancer. However, there are still gaps in other synergistic mechanisms that cannot be solved. It is hoped that future studies can focus on the anticancer mechanisms of other GLP-1 drugs.
A Brief Introduction of Inkjet Printing Technology and Optimizations
Authors: Long Shiyang
Published: January 2025

Inkjet printing technology has developed for several years, and it has made a great difference in peoples lives. The inkjet printing technology can be divided into two types, which are Continuous Inkjet (CIJ) technology and Drop-on-Demand (DOD) inkjet technology. The Drop-on-Demand inkjet includes piezoelectric inkjet, thermal inkjet, electrostatic inkjet, and acoustic inkjet. These technologies have their own benefits and weaknesses. The Drop-on-Demand printer has better precision than Continuous Inkjet. Optimizations to the printing quality can be carried out from three factors, which are the ink, the substrate, and the coffee ring effect. The ink can be improved by controlling the temperature. The substrate can be improved by changing its structure. The coffee ring effect can be suppressed by using hydro-soluble polymer additives or controlling the temperature. Future advancements in inkjet printing technology are expected to focus on optimizing these factors through interdisciplinary approaches, including material science, fluid dynamics, and advanced manufacturing techniques
Research Developments in Cancer Hallmarks and Immune Checkpoints Based on Mechanisms of Tumour Microenvironment
Authors: Jin Chao
Published: January 2025

Cancer has been one of the most concerning diseases around the globe, and oncologists have been developing different insightful therapies in the last century. With the shifted focus on immunotherapy, analysing the tumour microenvironment (TME) is crucial for cancer hallmark identification and subsequent antibody-based inhibition. Currently, PD-1/PD-L1 and CTLA-4 immune checkpoints are studied intensively, and there are FDA-approved immune checkpoint inhibitors (ICIs) such as Ipilimumab for anti-CTLA-4. Also, the characteristics of TMEs are expanded to include genomic instability and epigenetic factors. However, the complexities of TMEs disallow oncologists to consider all aspects, and tackling immune checkpoints can lead to unintended consequences. Therefore, this review report aims to investigate the common biochemicals and immune responses within TMEs, and how different types of TMEs have different overexpressions. Based on the chemical interactions in TME, the targetable cancer hallmarks will be investigated, with an inclination toward the fast-growing immune checkpoint inhibitors. It is concluded that cytokine-induced inflammation in TME causes Treg responses and immune escape by tumour cells, which can be categorised into different types. Also, immune checkpoint inhibitors show promising results against solid or liquid tumours when used in the right conditions. Overall, this report emphasises the diversity and informs the key characteristics of TMEs; it reminds the medical field that immune checkpoint inhibitors may not always bring a better prognosis. A thorough understanding of TME is important for future research developments. In the future, there could be more focus on combination therapies on immune checkpoints
Genetic Mutation and Regulation in Pancreatic Ductal Adenocarcinoma Cancer: Developing Relevant Molecular Biomarkers
Authors: Ai Xiaomi
Published: January 2025

Pancreatic ductal adenocarcinoma (PDAC) is a highly invasive and highly lethal malignant tumor. Due to the difficulty in early diagnosis and limited treatment options, the 5-year survival rate is less than 10%. Traditional treatments such as surgery, chemotherapy, and radiotherapy have limited effects on PDAC, which is mainly attributed to its unique tumor microenvironment (TME), common gene mutations (such as KRAS, and TP53), and immunosuppressive properties. In recent years, with the advancement of molecular biology and genomics technologies, the molecular mechanisms of PDAC have been studied more deeply, revealing the gene mutations and regulatory networks associated with its pathogenesis. In particular, KRAS mutations have become an important research direction for targeted therapy. However, the effect of immunotherapy in PDAC is limited by the immune escape characteristics of TME. This article systematically summarizes the key gene mutations in PDAC and their regulatory mechanisms, including epigenetic regulation, microRNA, histone modification and other influencing factors. CRISPR-Cas9 shows great potential in correcting gene mutations and reshaping TME. In addition, combining immunotherapy with targeted drug delivery (such as nanotechnology) can improve the precision of treatment and reduce side effects. These advances provide a comprehensive reference for future personalized and effective treatment options for PDAC
The Impact of Mitochondria on Neurodegenerative Diseases
Authors: Liu Ruibo
Published: January 2025

Neurodegenerative diseases (NDDs) include Alzheimer's disease (AD), Parkinson's disease (PD) and Huntington's disease (HD), which are defined by the progressive deterioration of neurons in the central nervous system and functional decline. The pathogenesis of these diseases is complex and there is currently no effective treatment. For example, the failure rate of clinical trials for AD treatment strategies is as high as 99.5%. Research indicates that elements such mitochondrial malfunction, oxidative stress, excitotoxicity, inflammation, and apoptosis are closely related to the onset of NDDs, especially mitochondrial dysfunction, which is considered to be one of the core mechanisms of NDDs. Mitochondria are not only the main production site of ATP, but also participate in key processes such as metabolite synthesis and reactive oxygen generation. Due to the high energy demand of brain neurons and their high dependence on mitochondrial function, abnormal mitochondrial function may lead to serious neuronal structural and functional disorders. In addition, neurons also need to maintain local activities such as synaptic transmission and axonal transport through the precise transport and distribution of mitochondria. Therefore, abnormalities in mitochondrial dynamics and function may become early characteristics and potential pathogenic factors of NDDs. By reviewing the mechanism of mitochondrial abnormalities in AD, PD, and HD and their potential therapeutic strategies.This article seeks to investigate mitochondria as a prospective target for the prevention, early detection, and treatment of NDD
Shaping China's National Image Through Infrastructure: Business Communication Strategies under the Belt and Road Initiative
Authors: Duan Yihong
Published: January 2025

With the promotion of the Belt and Road Initiative, the global investment and construction activities of Chinese infrastructure enterprises such as China Construction and China Railway have significantly improved the national image and brand awareness. However, in this process, these enterprises face challenges such as cultural differences, information gaps, and local people's doubts about foreign investment. This study explores how Chinese infrastructure companies shape the country's image through effective business communication strategies in the context of the Belt and Road Initiative. Through literature review and case study, this study will focus on the communication strategies adopted by Chinese infrastructure enterprises in countries along the Belt and Road, and how these strategies affect local consumers' perception and trust in Chinese brands. The study reveals that successful communication cases not only enhance brand recognition, but also increase consumer trust in the quality and efficacy of the program. In addition, cultural communication strategies are essential in different markets, helping enterprises integrate into the local society and improve their brand image. This study provides a new perspective and ideas for the brand communication of Chinese infrastructure enterprises in the international market. I contribute theoretical support for future academic research in related fields.
Stock Market Interest Rate Fluctuation and Its Influencing Factors
Authors: Wang Yitong
Published: January 2025

The stock market is an indispensable part of the financial market, and the fluctuation of interest rate in the stock market is also a common and important phenomenon in the financial market, which is unpredictable, complex and elusive. This paper examines the impact of interest rate fluctuations on the stock market and its influencing factors. The research results are as follows: The impact of such interest rate fluctuations on the stock market can be reflected in indirect influencing factors such as corporate financing costs and investors' investment preferences. Changes in intermediate factors caused by interest rate fluctuations largely determine the rise and fall of stock prices, thus forming a closed loop and once again having the same or different impacts on stock market investors and all walks of life. As an important factor in the financial market, the change of interest rate is also affected by various indicators, such as interest rate policy and inflation.
Application of Active Components such as DC Generators and Operational Amplifiers in Mechanical Design
Authors: Song Yining
Published: January 2025

DC generators and operational amplifiers have become increasingly important as the need for automation and precise control in mechanical engineering continues to grow. Since their invention in the 19th century, DC generators have played an important role in power systems, especially in applications that require a stable DC power supply. Meanwhile, since the 1960s, operational amplifiers have played an important role in analog circuits, and their applications cover a wide range of fields such as audio processing, signal conditioning, data acquisition and control systems. This paper explores the multiple applications of DC motors and operational amplifiers in mechanical systems and their integration through a literature review approach. It is found that these components not only improve the efficiency and performance of mechanical systems, but also provide higher control accuracy in areas such as robotics and industrial automation. In addition, with the continuous advancement of technology, the combination of the two is expected to realize innovations and breakthroughs in more fields. The research in this paper provides an important reference for the future innovation and development of mechanical engineering
The Application of Microcomputer Systems in Automatic Control Systems
Authors: Wang Hongyao
Published: January 2025

With the continuous advancement and innovation of computer system technologies, the performance of microcomputers has improved significantly. The enhanced computing power of microcomputer hardware provides greater flexibility for the development of various intelligent optimization algorithms. Integrating microcomputers into automatic control systems effectively addresses the systems demands for signal stability, sensitivity, response speed, and manufacturing cost, thereby significantly advancing the practical application of automatic control systems. This paper comprehensively explores the current state and challenges of applying microcomputers in automatic control systems, while providing an in-depth analysis of development trends in this field. It systematically explains the specific improvements microcomputers bring to control systems and how to select appropriate algorithms based on different types of automatic control systems. Moreover, the review highlights the impact of hardware performance limitations of microcomputers on algorithm implementation and discusses potential solutions and directions for future technological advancements. It also examines successful applications and existing issues in representative automatic control systems employing microcomputers. Finally, the study anticipates the development trends of intelligent optimization algorithms for microcomputers in automatic control systems, as well as the emerging challenges and research directions
The Analysis of Applications of Microcomputers in Information Engineering: From Automatic Control Electromechanical Systems to LSI Circuit Design
Authors: Guo Lidong
Published: January 2025

This paper explores the significant developments in computer technology within the field of information engineering, with a particular focus on the applications of microcomputers. The research delves into two key areas: automatic control electromechanical systems and large-scale integrated circuits (LSI). In recent years, the integration of microcomputers in these systems has transformed the way data is processed, improving system efficiency and precision. The literature review identifies advancements in microcomputer-based control systems, which enhance real-time responsiveness and system stability, alongside innovations in circuit design that contribute to higher integration density and reduced power consumption. Case studies further highlight practical applications in industrial automation and GPS receiver design, demonstrating how microcomputers optimize both functionality and energy efficiency. By synthesizing these findings, this paper underscores the critical role of microcomputers in advancing modern information engineering and offers recommendations for future research, especially in areas where artificial intelligence and edge computing are integrated into next-generation systems. This study contributes to the understanding of how microcomputers enhance technological efficiency and drive innovation in complex engineering environments
Progress in the Application of PtCo Alloy Catalysts in Oxygen Reduction Reactions for Fuel Cells
Authors: Chen Yusong
Published: January 2025

Proton Exchange Membrane Fuel Cells (PEMFCs) are considered an effective way to address energy shortages and environmental pollution due to their high efficiency, low-temperature operation, and environmental friendliness. However, the oxygen reduction reaction (ORR) at the cathode in PEMFCs is very slow and needs rare and expensive Pt-based catalysts, which limits their commercialization process. To reduce costs while maintaining efficient catalytic performance, researchers have developed various technological strategies, among which PtCo alloy catalysts have garnered widespread attention due to their excellent ORR catalytic performance. This article reviews the latest progress and current status of PtCo alloy catalysts in PEMFC oxygen reduction catalysis, discusses the impact of catalyst component control, particle size regulation, crystal face regulation, doping, and other regulatory strategies on the catalytic activity of fuel cells, and provides a detailed introduction to the most promising PtCo alloy structures, such as polyhedra, core-shell, nanoframes, and ordered intermetallic structures. At the same time, the research on catalyst supports is discussed, and the challenges and future prospects of PtCo alloy catalysts in their applications are pointed out.
Sustainable Synergies: Integrating Energy Efficiency and Eco-Economic Principles in Modern Construction
Authors: Yan Yi , He Wenchong , Liu Qian
Published: January 2025

The efficiency in building design and construction with energy economics, eco-economics, carbon-negative technologies, climate policy, sustainable construction and green building practice is explored. The aim is to analyse the interrelationships among different components of the secret sauce that makes the built environment more sustainable in terms of energy. The focus is on energy-efficient design and construction that reduces the carbon footprint of built environment. The relationship of the economic elements of building energy use with efficiency is discussed (e.g., cost-benefit analysis of eco-technologies and the economic incentives that are needed for adoption). The paper also considers eco-economics (i.e., how the environment is factored into economic planning in the built environment). The role of carbon-negative technologies in achieving net-zero emissions is covered, as well as the interplay of climate policies and regulations in building-related sustainability practices. The challenges and opportunities in getting these technologies and practices adopted are covered (e.g., technological, market and socio-economic). The overarching theme is how the three interconnected concepts of energy efficiency, eco-economics and sustainable construction can be harnessed to produce a built environment that is environmentally and economically sustainable, and that contributes to the broader global sustainable development agenda.