Search

Background and purpose: The overexpression of carnitine palmitoyl transferase 1A (CPT1A) is related to the poor prognosis of breast cancer, and it can promote the utilization of fatty acids by mitochondria and maximize triphosphate (ATP) production. However, the role of CPT1A in breast cancer metastasis is still unclear. This study aimed to explore the mechanism that mitochondrial dysfunction and CPT1A/extracellular signal-regulated kinase (ERK) signaling pathway in breast cancer jointly regulate the malignant behavior of breast cancer. Methods: The lentivirus system and shRNA tools were used to overexpress or knock down CPT1A in human breast cancer cell lines MDA-MB-231 and MCF7, and the cells were divided into NC group, CPT1A group and shCPT1A group. The invasion ability of cells was detected by transwell assay, and the protein expressions of peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α), ERK1/2 and CPT1A were analyzed by Western blot. The mitochondrial morphology of MDA-MB-231 and MCF7 cell lines was analyzed using mitochondrial red staining, and mitochondrial respiratory capacity was analyzed by oxygen consumption rate. Results: Compared with cells expressing control vector, overexpression of CPT1A resulted in enhanced invasion abilities of MCF7 cells and MDA-MB-231 cells (P

The application of smart grids and other systems generates a large amount of data, which is of great value to the research in electric power. This paper analyzes and mines the electric power data in a smart grid through data mining technology to provide technical and data support for analyzing users’ electricity consumption behavior, grid load prediction, and power dispatch optimization. The user electricity feature selection algorithm is built using the mRMR criterion, and it is combined with the improved fuzzy C-mean algorithm to categorize and analyze the user’s electricity consumption behavior. The LSTM algorithm is used in this paper to forecast power load in the smart grid due to the ability of long and short-term memory networks to handle long-term dependencies. The objectives for optimizing the power system scheduling, such as minimizing pollution emissions, are selected, and the optimal solution is calculated using a genetic algorithm. The feature selection algorithm evaluates the user’s electricity consumption characteristics, combines the clustering algorithm to compare the internal metrics of the two feature selections, and classifies the user’s electricity consumption behavior into six categories according to the electricity consumption characteristics. The accuracy of the LSTM algorithm’s prediction of the grid load reaches 74.19% on the validation set, and the mean square error is 0.881. In the final optimal solution obtained for power dispatch optimization, the pollution emission is only 8.93 kgCO2/H, and customer satisfaction can reach 74.89%.

In order to ensure the stable transmission of electric power, it is an effective way to diagnose and maintain the operating status of electric power equipment from the operation data of electric power equipment. This paper uses a stacked sparse autoencoder to design a training model to realize the data function operation function in the fault detection model. After collecting and classifying the power system data, the line current is standardized and transformed. Then, the processed data is input into the stacked sparse autoencoder, and the model is trained layer by layer. On this basis, the long-term memory network model is introduced to establish a fault diagnosis model. To solve the double-sample situation of power data, the maximum mean difference method must be used. A preventive maintenance strategy is constructed based on failure prediction and remaining life to optimize the implementation path. Evaluate the model’s value in terms of its performance, reliability, and economic benefits of preventive O&M methods. However, judging from the fuzzy fault degree, the electrical components with a high probability of failure are T1, T3, L3, L9, and B1, and the fuzzy fault degrees are 0.3154, 0.2789, 0.0648, 0.2657, and 0.0678, respectively—fusion of multidimensional evidence. The components most likely to fail are T1, T3, and L9. From the perspective of operation and maintenance costs, when the MMC maintenance time of Dublin Fang Electric Farm is 17 times, the lowest operation and maintenance cost is 22.8615 million yuan.

In this paper, we preprocess the equipment data using by exponential smoothing method, fit the fault information by using the distribution model, and evaluate the fitting degree of the function with the help of the K-S test to derive the equipment fault information function. In accordance with the correlation mapping between the distribution network health index and the existence of faults, the health index of the distribution network equipment in the region before and after the self-healing of faults is comprehensively calculated, and the state assessment of the equipment is carried out. Before and after the fault self-healing of the IEEE33 node system, the system loss is reduced by 58.89%, as evidenced by the results. Before and after the fault self-healing, Condition 1: the line health index ranges from 1.317 to 3.777, and the transformer health index ranges from 2.011 to 4.646. Condition 2: the line health index ranges from 2.284 to 4.059, and the transformer health index ranges from 1.653 to 4.047, respectively. And Condition 3: the health indices all increase by varying from 0.711 to 2.067. Localized equipment degradation has a significant impact on the overall health of the network, with lines affecting the system to a greater extent than transformers. To summarize, the proposed health index state assessment method can effectively determine the health state of distribution networks before and after fault self-healing.

In this study, we evaluate the enhanced carrying capacity of the modified IEEE 33-node distribution system, which incorporates a high percentage of distributed resource (DR) integration, utilizing the whale optimization algorithm. The evaluation employs a fuzzy comprehensive evaluation (FCE) method, wherein we construct FCE indices for factors influencing the distribution network’s carrying capacity. These indices involve calculating weight coefficients and establishing an affiliation function, culminating in the output of the final fuzzy evaluation result vector. The analysis identifies three nodes—11, 18, and 31—within the IEEE 33-node system for decentralized DR installation. Based on initial scenario data, the maximum carrying capacity of the distribution network is determined to be 40.68 MW. The analysis further reveals that the utilization rate of distributed resources reaches 100% at specific times, specifically at 2:00 AM and 6:00 AM. During the 3:00 to 5:00 AM interval, both the system voltage excursion index and the composite score for distribution network losses are calculated to be low. These findings suggest the feasibility of integrating a single regional distribution network with other energy networks, thereby facilitating multi-regional resource interconnection and enhancing the flexibility of system operations. This approach offers significant implications for improving the robustness and efficiency of electrical distribution systems.

The modern world is characterized by dynamism, changing social, economic, and political realities. Migration is becoming one of the phenomena developing rapidly due to new forms of communication, digital ways of transmitting information and interaction. The result of migration processes is the creation of social groups of migrants in the host country, which perform the functions of ensuring the adaptation of their members in a new social space for them. In this regard, the theoretical study of migrants as a social group, the description of the functional characteristics of Chinese migrants as a social group is relevant. The purpose of the article is to identify in scientific concepts and social reality the main characteristics and functions of migrants as a social group, to highlight the system-forming features of the social group of Chinese migrants. In the article, social groups are considered as associations of people interacting with each other in the course of their life on the basis of traditional and innovative values, norms and rules of behavior, associations of people performing certain functions in society. As a result of the conducted research, the system-forming features of the social group of Chinese migrants are identified, including interaction, consideration of oneself as a member of this social group, development of norms and rules of behavior, common goals and objectives of activity, etc. The study showed that the social groups of Chinese migrants mean diasporas, social communities, enclaves. The theoretical analysis of the social group allows us to conclude that there is no unified understanding of the concept of “social group” in the scientific literature. This is determined by the dynamism of the social reality itself, which makes certain adjustments to the research of the social group, as well as by the constant change in the role of social groups in the space of their life activity.

Modern era is the era of human resources, intellectual capital as the main driving forces for the development of society, the goal of which was to achieve a decent quality of life, which in modern conditions is becoming a priority goal, the ideal of society development. The emergence of a new stage in the development of society (the era of post-industrialism, the Third Wave, the information society) became a prerequisite for the emergence of a new model of quality of life – “knowledge”, which determines the purpose of the study – to identify the subjects of the “knowledge model of quality of life” in the concepts of representatives of post-industrialism, who put forward the idea that a specifi c model of the quality of life, its formation and evolution are determined by the existing era. The article analyzes the concepts of the creators of post-industrialism. We revealed that each stage of the development of society has its own specifi c model of the quality of life. The bearer of the knowledge model of the quality of life is a social cluster that carries out its activities in professional and everyday life on the basis of knowledge, intellectual resources, inventions, new forms of organization, relationships with each other and the environment. The concepts of the quality of life by the representatives of post-industrialism J. Galbraith, D. Bell, E. Toffl er and M. Castells are the theoretical and methodological basis of the study. The authors used a comparative analysis of subjects, functionality, the need for the concepts of quality of life by the representatives of post-industrialism, which made it possible to identify different approaches to determining the subjects of the “knowledge model of quality of life”. The research materials can be used in assessing the trends in the development of a knowledge model of the quality of life, studying the prospects for the development of society and making forecasts for the future development of mankind.

Objective To compare the difference between the health literacy level of elderly in Guangzhou in 2021 and 2023, and thus to provide government and institutions with a scientific data for enhancing health literacy level. Methods Two surveys were conducted respectively in 2021 and 2023, and SPSS 19.0 was used for χ2 test and Logistic regression analysis. Results The level of elderly’s health literacy in Guangzhou in 2023 and 2021 are respectively 19.3% and 12.7%, but both of them are at a low level. Educational level and health state are the influencing factors for elderly’s health literacy. Conclusion Health literacy of elderly in Guangzhou is relatively low and needs improving, especially in health skills, prevention and control of infectious diseases literacy. The government, community and elderly’s family and elderly themselves should work together to improve the health literacy of elderly people.

Objective To understand the health literacy level and its influencing factors of elderly in Guangzhou, so as to provide scientific evidence for formulating effective intervention measures and policies. Methods Stratified cluster random sampling was used to conduct a survey on health literacy among elderly in Guangzhou in 2022. Logistic regression was used to analyse the influencing factors of their health literacy level. Results The total level of elderly’s health literacy in Guangzhou is 16.9%; From the three dimensions of health literacy, 13.6% of elderly have health knowledge and conceptual literacy, 23.7% of healthy lifestyle and behaviour, and 3.4% of health skills literacy. From high to low, the level of the six aspects of health literacy are scientific health concept literacy (37.3%), safety and emergency literacy (35.7%), health information literacy (28.9%), basic medical literacy (25.4%), chronic disease prevention and control literacy (15.3%), and infectious disease prevention and control literacy (11.9%). And there are significant differences among elderly of different ages, educational level, housing population and years of having diseases (P

The phenomenon of labor migration from the post-Soviet countries and, mainly, from the Central Asian republics to the territory of the Russian Federation is the subject of close attention of specialists, scientists from various fields of socio-humanitarian sciences. The expansion of the area of labor migration spreading within Siberia and the Far Eastern Federal District, as well as the quantitative increase in incoming migrants, actuali zes a number of issues, including aspects such as the adaptation of arriving migrants to changed socio-cultural conditions, analysis of the transformation of the ethno-cultural and ethno-religious space of the recipient region, the incorporation of migrant labor families, including their children, into social institutions of the host community. The purpose of this study is to identify the cognitive-motivational aspect of adaptation of the studied categories, which will allow to adjust the social policy strategy available at the regional level in relation to migrants and their families, and, accordingly, will create conditions for more effective management of migration processes. The problems of the research imply the use of theoretical and empirical methods. Consideration of the phenomenon of childhood in these aspects makes it possible to identify existing models and strategies for the adaptation of children who have left the usual cultural environment and migrated with their parents, and those born in migration based on the application of theoretical and methodological developments of acculturation of J. Berry and Yang Kim’s adaptation theories. The need for this kind of analysis is determined directly by the social agenda itself – an increase in the share of migrants among recipients of social services. As an empirical method, the focus group method is used, which helps to identify the difficulties and features of the adaptation process, as well as the goals and prospects of further socialization, which is a priority for migrant children, representatives of educational institutions ‒ preschool, school education.

Colorectal cancer (CRC) is one of the most frequently diagnosed cancers worldwide and stands among the leading causes of cancer-related deaths. Although deregulation of the microbiota in the gastrointestinal tract has been frequently described in CRC, very little is known about the precise molecular mechanisms by which bacteria and their toxins modulate the process of tumorigenesis and behavior of cancer cells. In this study, we produced recombinant Bacteroides fragilis enterotoxin-1 (rBFT1) and demonstrate that rBFT1 could promote cell proliferation in colorectal cancer cells and accelerate tumor growth in vivo. To identify the mechanisms, we further investigated CCL3/CCR5 and NF-κB pathway. We found that CCL3, CCR5, NF-κB, and TRAF-6 were dramatically upregulated after rBFT1 treatment, thus suggesting that the role of rBFT1 in CRC progression may be associated with CCL3/CCR5 and NF-κB pathways. Collectively, our results indicate that rBFT1 serves as a tumor promoter and plays a crucial role in inducing the proliferation of CRC via accelerating CCL3-related molecular pathway, thus giving insights into mechanistic underpinnings for the prevention and treatment of CRC.

Objective To investigate the relationship of tissue non-specific alkaline phosphatase (TNAP) with myocardial fibrosis in patients after myocardial infarction (MI). Methods Forty-six acute MI patients admitted to our hospital from March to November 2019 were enrolled in this study and assigned as the MI group, and another 41 patients with negative findings in coronary angiograms during the same period were collected as the control group. The serum TNAP activity was detected by alkaline phosphatase kit. The serum contents of procollagen type ⅠC-peptide (PⅠCP) and procollagen Ⅲ N-terminal peptide (PⅢNP) were detected by enzyme-linked immunosorbent assay (ELISA). Myocardial tissues from 5 patients who died of MI were collected. Collagen fiber area of heart was detected by Sirius red staining and the expression of TNAP was detected by immunohistochemistry. Ten 8-week-old male C57BL/6J mice were randomly divided into sham group and MI group (n=5). In 2 weeks after MI, all mice were sacrificed, and collagen fiber area of heart was detected by Masson staining and the expression of TNAP was detected by immunohistochemistry. Results Compared with the control group, the MI group had significantly increased serum TNAP activity (8.49±3.30 King U/100 mL, P

In order to compare the health literacy level of college students in Guangdong province in 2020 and 2022, so as to provide a scientific basis for targeted health literacy intervention and policy formulation for college students in Guangdong province, surveys were respectively conducted in 2020 and 2022. The data collation and analysis were performed using SPSS 19.0 statistical software. The χ2 test was used to compare different health literacy, and logistic regression was performed to analyse the factors influencing health literacy. The results show that the general health literacy level of college students in Guangdong province in 2022 is 46.5%, 6.3% higher than 40.2% in 2020, which difference is statistically significant. The three dimensions and six aspects of health literacy all have improved. The results of both years showed that health skills, basic medical literacy and health information literacy were at a low level. According to logistic regression analysis, the health literacy level of senior students is higher than that of junior students，and those who have taken health related courses have higher health literacy level. The most desirable type of health knowledge is prevention and treatment of infectious diseases, and the new media access is becoming more popular among students to gain health knowledge. In conclusion, Guangdong college students’ health literacy is relatively high, but still needs to be improved, especially in health skills, basic medical care and health information literacy. The government, colleges and universities should work together to improve college students’ health literacy.

Chinese banks have gradually expanded their financial services into overseas financial services and financial trade transactions. The financial services system is becoming more and more humanized and intelligent with the global economy's rapid development and progress. It improves the quality of banks' financial services and plays a vital role in its financial system construction and financial product innovation. As an internal driving force for the development of the financial industry, financial innovation has a vast and extensive impact on the economy. Because of the importance of monetary policy on national macroeconomic regulation and control, it is of great practical significance to study the impact of financial innovation on monetary policy effectiveness. This paper has conducted an in-depth analysis of the core concepts of internet finance, and suggestions and policy implications are given to improve China's monetary policy's effectiveness. Keywords: financial products, service innovation, monetary policy, effectiveness analysis JEL Classifications: G29, G14 DOI: https://doi.org/10.32479/ijefi.11007

A superhydrophobic conversion film on AA6061 aluminium alloy was prepared via ultrasonication-assistant chemical etching by FeCl3/HCl aqueous solution,KMnO4 passivation,and ultrasonic deposition of trichloro (1H,1H,2H,2H-heptadecafluorodecyl) silane. Field emission scanning electron microscopy (FESEM),contact angle test and Fourier transform infrared spectrometer (FTIR) were used to investigate the morphology,hydrophobicity,and chemical compositions of superhydrophobic conversion film, respectively. The results show that superhydrophobic surface exhibits a high contact angle of 153° and endows the Al matrix promising self-cleaning ability, resistance to acid or alkali erosion, anti-friction and anti-corrosion capability. Compared with the dipping method, ultrasonic preparation of superhydrophobic film on Al alloy surface can not only improve the homogeneity of self-assembly of PFCPS, but also enhance its bonding force with Al matrix and form a superhydrophobic film with good protective performance.

(3R)-4-[(4-methylphenylsulfonyl)]-1,4-thiazine-3-acyl-[(2R)-2-amino-4-methyl]-pentanoic acid isopropyl ester (ID:HD5-6) is a ligand of FK506 binding proteins (FKBPs), which we developed and had proprietary intellectual property rights for. The compound facilitates nerve regeneration, and can potentially developed in drugs for treatment of neurodegenerative diseases such as amyotrophic lateral sclerosis and stroke. In this study, one-dimensional (1D) and two-dimensional nuclear magnetic resonance (NMR) spectroscopy (including 1H NMR, 13C NMR, DEPT, 1D NOESY, 1H-1H COSY, 1H-13C HSQC and 1H-13C HMBC), combined with mass spectrometry (MS), ultraviolet spectroscopy (UV) and infrared spectroscopy (IR), were used to elucidate the structure of the compound. All 1H and 13C NMR signals were assigned.

In this paper, two polytetrafluoroethylene (PTFE)/Nomex hybrid fabric structures with different weaving methods under various working conditions were studied. A pin-on-disk tribometer was used to test the friction coefficient (COF), and a scanning electron microscope (SEM) was used to analyze the wear surface. The results showed that COF of the two fabric structures was significantly different under dry sliding but similar under water lubrication. The wear amount of the two fabric structures was also different. Fabric structure influences the COF and wear amount via affecting the surface topography and the bonding force between layers.

The clustering algorithm based on sparse feature vector for categorical attributes(CABOSFVC) is an efficient high-dimensional clustering method for categorical data. Sparse feature dissimilarity(SFD) is used to calculate the distance and sparse feature vector is used to achieve data compression. However,CABOSFVC algorithm is dependent upon SFD upper limit parameter for which there is no guidance for configuration. Aimed at solving the problem that CABOSFVC algorithm is sensitive to this parameter,a new heuristic hierarchical clustering algorithm of categorical data based on SFD(HABOS) was proposed in this paper. With the constraint of the upper limit number of clusters,this algorithm applied agglomerative hierarchical clustering and the new internal clustering validation index based on SFD(CVISFD) which was used to measure the results heuristically to achieve the best choice of the clustering level. Three UCI benchmark data sets were used to compare the improved algorithm with the traditional ones. The empirical tests show that HABOS increases the clustering accuracy and stability effectively.

FP-Growth algorithm is an association rule mining algorithm based on frequent pattern tree (FP-Tree), which doesn’t need to generate a large number of candidate sets. However, constructing FP-Tree requires two scansof the original transaction database and the recursive mining of FP-Tree to generate frequent itemsets. In addition, the algorithm can’t work effectively when the dataset is dense. To solve the problems of large memory usage and low time-effectiveness of data mining in this algorithm, this paper proposes an improved algorithm based on adjacency table using a hash table to store adjacency table, which considerably saves the finding time. The experimental results show that the improved algorithm has good performance especially for mining frequent itemsets in dense data sets.

Contribution: This study explores the elements engineering students perceive as important for developing their learner agency in the context of intercultural project-based learning (PBL) teams. Background: The concept of learner agency has recently gained prominence due to its relevance for student-centeredness, autonomy, self-regulation, and collaboration. Certain pedagogical approaches are known to specifically support the development of learner agency, including PBL, in which learners are provided with active, self-directed, and collaborative learning tasks. PBL practice is also increasingly diverse, emphasizing intercultural collaboration in teams. However, learner agency has received little research attention in PBL settings, and even less in intercultural PBL. This study contributes to the existing literature on the development of learner agency in intercultural PBL teams. Research Question: What elements do engineering students consider important for supporting their learner agency development in an intercultural PBL team context? Methodology: Theoretically, learner agency is framed within three interrelated dimensions, namely, intrapersonal, behavioral, and environmental. Based on this framework, a survey instrument with 31 items was constructed and responses were obtained from 310 engineering students. The survey used expert review, student piloting, exploratory factor analysis (EFA), and Cronbach's alpha to test content validity, construct validity, and reliability. The descriptive and demographic statistics were examined through t-test and the analysis of variance test. Findings: Five factors emerged from EFA: 1) interest and motivation; 2) self-efficacy; 3) self-regulated behaviors in teams; 4) team dynamics; and 5) external support. The statistical analysis shows that the interest and motivation factor was perceived by the engineering students as the most important. Furthermore, several demographic variables, including gender, nationality, year of study, and type of PBL learner based on their level of experience with PBL, were found to impact engineering students' agency development.