bluuebunny/crossref_metadata_2025_split huggingface dataset:
Causal associations between chronic obstructive pulmonary disease and cardiovascular diseases: a Mendelian randomization study
Authors: Yu Guangzan , Liu Lulu , Ma Qian , Han Fusheng , He Hua 
Published: January 2024

Abstract
Background
A large number of studies have demonstrated links between chronic obstructive pulmonary disease (COPD) and cardiovascular diseases (CVDs). Due to the presence of numerous shared risk factors, it is currently unknown whether there is an independent or reverse causal relationship between the two.
Methods
Exposure and outcome data from the largest available genome-wide association studies were extracted for Mendelian randomization (MR) studies. Univariate MR analysis was performed using IVW as the primary analysis methods, and multiple sensitivity analyses were used to enhance the robustness of the results. This was further followed by mediation MR analysis of positive results after excluding confounding factors with multivariable MR analysis.
Results
The MR estimation based on IVW method indicated a strong association between genetically determined COPD and HF (OR = 1.12, 95%CI: 1.07–1.17, p = 3.15E-06), CHD (OR = 1.00, 95% CI: 1.00–1.01, p = 4.03E-05), EH (OR = 1.01, 95%CI: 1.01–1.01, p = 3.48E-06) as well as Stroke (OR = 1.00, 95% CI: 1.00–1.00, p = 3.14E-05). The results of multivariable MR analysis revealed that COPD is not significantly associated with CHD after adjusting for IL-6 or LDL or total cholesterol (p > 0.05). Our findings indicated that BMI, smoking initiation, smoking status, obesity and FEV1 played a role in the causal effect of COPD on HF, EH and Stroke.
Conclusions
We found positive causal relationship between COPD and HF, EH, Stroke essentially unaffected by other confounding factors. The causal relationship exhibited between COPD and CHD was influenced by confounding factors. BMI, obesity, initiation of smoking, smoking status and FEV1 were the mediators between COPD and CVDs.
Improving Power by Conditioning on Less in Post-selection Inference for Changepoints
Authors: Carrington Rachel , Fearnhead Paul 
Published: January 2024

Abstract

Post-selection inference has recently been proposed as a way of quantifying uncertainty about detected changepoints. The idea is to run a changepoint detection algorithm, and then re-use the same data to perform a test for a change near each of the detected changes. By defining the p-value for the test appropriately, so that it is conditional on the information used to choose the test, this approach will produce valid p-values. We show how to improve the power of these procedures by conditioning on less information. This gives rise to an ideal post-selection p-value that is intractable but can be approximated by Monte Carlo. We show that for any Monte Carlo sample size, this procedure produces valid p-values, and empirically that noticeable increase in power is possible with only very modest Monte Carlo sample sizes. Our procedure is easy to implement given existing post-selection inference methods, as we just need to generate perturbations of the data set and re-apply the post-selection method to each of these. On genomic data consisting of human GC content, our procedure increases the number of significant changepoints that are detected when compared to the method of Jewell et al. (2022).
Viability of Lactic Acid Bacteria (L. Acidophilus) in Probiotic Ready to Drink Juices
Authors: Concepcion Remilyn V , Braga Jason D , Mojica Analyn A , Barcelon Eufemio G 
Published: January 2024

Probiotics are consumed in dairy based goods, however, given the rise in various diet types, non-dairy alternatives, such as inoculating fruit juices with probiotics were studied for substitute. Lactobacillus acidophilus is a probiotic strain exerting a number of human health benefits. Therefore, the objective of this study was to determine the viability of Lactobacillus acidophilus in different non-dairy substrate to produce a Probiotic Ready to drink (RTD) juice blend made of malunggay, pineapple and mango over 24 hours of fermentation and 21 days of refrigerated storage. The secondary objective was to determine the sensory parameters using 9-point Hedonic scale and physicochemical properties of probiotic RTD Juice Blend in terms of pH, TSS and total acidity. All of the probiotic RTD Juice Blend samples achieved a mean viable count of at least 106 CFU/mL during 24 hours of fermentation and 21 days of refrigerated storage. According to the sensory evaluation, which evaluated samples according to color, aroma, taste and overall acceptability, probiotic RTD juice blend with malunggay-pineapple-mango blend proved to have the highest score for all characteristics with pH of 4.62, TSS of 13.47OBx and total acidity of 0.47%. The pH and TSS decreases with time while acidity increases. This condition is good for the production of microbes because low pH can decrease the microbes’ production rate. This environment may enable LAB to successfully pass the pH of the stomach and bind in the gut of the host which is needed for successful colonization and propagation for expression of its health-promoting effects. Therefore, this study indicated a potential for probiotic fruit juices as a valid alternative to dairy based probiotic products.
Assessing the Impact of Internet Skills on Depressive Symptoms Among Chinese Middle-Aged and Older Adults: Cross-Sectional Instrumental Variables Analysis
Authors: Mu Aruhan , Liu Zhiyong 
Published: January 2024

Abstract

Background
The potential benefits of IT for the well-being of older adults have been widely anticipated. However, findings regarding the impact of internet use on depressive symptoms are inconsistent. As a result of IT’s exponential growth, internet skills have supplanted internet access as the source of the digital divide.

Objective
This study evaluates the effect of internet skills on depressive symptoms through an instrumental variables (IV) approach.

Methods
Data from the China Health and Retirement Longitudinal Study’s wave 4 (2018) were used. This included 16,949 community residents aged 45 years and older. To overcome the endogeneity issue, we used an IV approach.

Results
Our results reveal the emergence of a second-level digital divide, the disparity in internet skills, among Chinese middle-aged and older adults. Liner regression suggests that a 1% increase in internet skills is associated with a 0.037% decrease in depressive symptoms (β=−.037, SE 0.009), which underestimates the causal effect. As expected, internet skills are an endogenous variable (F test P value <.001). IV regressions indicate that a 1% increase in internet skills reduces 1.135% (SE 0.471) to 1.741% (SE 0.297) of depressive symptoms. These 2 IV are neither weak (F–1=16.7 and 28.5; both >10) nor endogenous (Wu-Hausman test P value of .10; >.05 or >.01).

Conclusions
Better mental health is predicted through improved and higher internet skills. Consequently, residents and policy makers in China should focus on bridging the digital divide in internet skills among middle-aged and older adults.
Motor Effects of Intervention With Transcranial Direct Current Stimulation for Physiotherapy Treatment in Children With Cerebral Palsy: Protocol for a Randomized Clinical Trial
Authors: Cangussu Anna Izabel , Lucarini Beatriz , Melo Igor de Freitas , Diniz Paula Araújo , Mancini Marisa , Viana Bernardo de Mattos , Romano-Silva Marco Aurélio , Miranda Débora Marques de 
Published: January 2024

Background
Children diagnosed with cerebral palsy (CP) often experience various limitations, particularly in gross motor function and activities of daily living. Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation technique that has been used to improve movement, gross motor function, and activities of daily living.

Objective
This study aims to evaluate the potential additional effects of physiotherapy combined with tDCS in children with CP in comparison with physiotherapy only.

Methods
This is a 2-arm randomized controlled trial that will compare the effects of tDCS as an adjunctive treatment during rehabilitation sessions to rehabilitation without tDCS. Children with CP classified by the Gross Motor Function Classification System as levels I and II will be randomly assigned to either the sham + rehabilitation group or the tDCS + rehabilitation group. The primary outcome will be the motor skills assessed using the Gross Motor Function Measure domain E scores, and the secondary outcome will be the measurement scores of the children’s quality of life. The intervention will consist of a 10-day stimulation protocol with tDCS spread over 2 weeks, with stimulation or sham tDCS administered for 20 minutes at a frequency of 1 Hz, in combination with physiotherapy. Physical therapy exercises will be conducted in a circuit based on each child’s baseline Gross Motor Function Measure results. The participants’ changes will be evaluated and compared in both groups. Intervenient features will be tested.

Results
Data collection is ongoing and is expected to be completed by January 2025. A homogeneous sample and clear outcomes may be a highlight of this protocol, which may allow us to understand the potential use of tDCS and for whom it should or should not be used.

Conclusions
A study with good evidence and clear outcomes in children with CP might open an avenue for the potential best use of neurostimulation.

Trial Registration
Brazilian Registry of Clinical Trials RBR-104h4s4y; https://tinyurl.com/47r3x2e4

International Registered Report Identifier (IRRID)
PRR1-10.2196/52922
Atomic partial charge model in chemistry: chemical accuracy of theoretical approaches for diatomic molecules
Authors: Uhliar Matej 
Published: January 2024

Abstract
Atomic partial charges cannot be physically measured but they play a significant role in many chemical theories and theoretical models. Therefore, they are, evaluated from experimentally acquired properties or calculated by quantum chemistry computational methods. This study is focused on determining chemical accuracy of various theoretical methods of computing atomic partial charges based on quantum chemistry. Values of gas-phase atomic partial charges were acquired by Mulliken (MUL) population analysis, natural bond analysis (NBO), Merz-Singh-Kollman (MSK) scheme, and atomic polar tensor (APT) charges computed considering Density Functional Theory and ab initio Møller-Plesset up to the second order levels. Correlations between the calculated values were determined by principal component analysis (PCA) and further confirmed by linear regression. The best agreement between experimentally evaluated atomic partial charges and theoretical values was obtained with the MSK scheme.
Research on the Synergistic Development of Ideological and Political Education of Non-public Enterprises and “Sanxin” Party Building in the Era of Artificial Intelligence
Authors: Yang Xue 
Published: January 2024

Abstract
Based on artificial intelligence technology, this paper integrates ideological and political education with “Sanxin” party building and uses mean density center estimation to get the correlation degree between user data metric words and educational documents. Combined with the fuzzy genetic algorithm to calculate the corresponding positional weights of various words, the information matching is realized through the similarity function, and the K-means clustering algorithm is used to effectively predict the learning behavior of party members. The highest number of course visits to the intelligent ideological and political education platform reached 880, and the highest number of readers of educational articles with party building reached 4,700. The integration of ideological and political education and the “Sanxin” party building enables the party members to establish the correct value of life and promotes the long-term development of new economic organizations, new social organizations, and new employment groups.
Using Principal Component Analysis to Explore the Influence of Civic Education on Students’ Mental Health in Colleges and Universities
Authors: Liu Feng 
Published: January 2024

Abstract
This paper first explored the implementation steps of principal component analysis, standardized the raw data, and calculated the correlation matrix, eigenvalues and variance contribution ratio. The principal components were identified, the principal component factors were thoroughly evaluated, and the comprehensive scores of the principal components were calculated. Then, the model of this paper was examined, and the principal component factors were extracted using the algorithm. Finally, the analysis of the correlation between Civic Education and Mental Health, as well as the predictive effect of Curriculum Civic Education on the level of cultural self-confidence and mental health were analyzed. The results show that the correlation coefficient between curriculum civic politics and happiness is 7.45. Curriculum civic politics is significantly positively correlated with all positive mental health indicators, r between 0.3-0.4, p<0.01, and with negative mental health indicators, r between −0.4-0.37, p<0.01. This study is important for the active promotion of curriculum civic politics and the enhancement of parenting effectiveness. Promoting the development of college students’ mental health is of great significance.
Innovation and Practice of Educational Management System in Colleges and Universities Based on the Concept of Data Analysis Education
Authors: Liu Jia 
Published: January 2024

Abstract
This paper proposes the evaluation method of college education management mode based on deep belief network (DBN), establishes the evaluation index of college education management mode, takes it as the input of the deep belief network, adopts the divergence algorithm and backpropagation algorithm to learn and optimize the parameters of the deep belief network, and establishes the evaluation model of the education management mode of universities. The evaluation method of the college education management model evaluation of the deep belief network is verified by evaluating the results and performing error analysis on 438 questionnaire test samples. The results show that the number of training steps of the adopted DBN model in the supervised tuning stage is 214, and the error fluctuation range is ±0.6, which achieves the expected effect, indicating that the adoption of the model has accuracy in the evaluation of college education management model. Under the concept of data analysis education, the evaluation method proposed in this paper has a positive significance for the innovation and practice of educational and teaching management systems.
Construction of Intelligent Practice System of Visual Arts Based on VR Technology in Information Age
Authors: Lv Pin 
Published: January 2024

Abstract
Taking visual art intelligence as an entry point, this paper describes the transformation brought by the information age to the expression of visual art. Based on VR technology to build a practice system of visual art intelligence, VR positioning technology is used to locate the three-dimensional coordinates of the operator in order to realize the independent positioning of multiple operators in a large space and avoid positioning interference. Through the eye movement multi-channel interaction algorithm based on head-eye synergy, the two-dimensional interaction task in flow field visualization is completed, and then gesture interaction is added to complete the three-dimensional interaction task. The constructed system was implemented in the teaching of art majors at College Z, and the data were analyzed. The results show that the total average scores of innovative theoretical ideas, interactive experience feeling, symbolic integration of creative content and infinite extension of the multidimensional spatial field are 82.42, 83.57, 80.84 and 80.28, respectively. The data show that teachers, students and parents recognize the intelligent system of visual arts and believe that it improves students’ innovative ability in art creation, enhances the interactive experience feeling of visual arts, and provides data support for the continuous research and exploration of contemporary visual arts.
Artificial Intelligence Technology Helps Spread Costume Design and Arts and Crafts Culture
Authors: Zhang Lei , Cao Chunnan , Ma Yun 
Published: January 2024

Abstract
This paper takes the integration development path of artificial intelligence technology and clothing design as the entry point, analyzes the influence of arts and crafts culture on clothing design, and gives the correlation between artificial intelligence, clothing design and arts and crafts culture. In order to make the style and color of clothing design more diversified, Fuzzy C-means is used to extract the color of the elements of arts and crafts culture, and adaptive optimization is used to compensate for the chromaticity of the color through artificial intelligence technology. A texture generation network is constructed based on the generative adversarial network to obtain the shape and texture style of the images of arts and crafts cultural elements in apparel design. To verify the effectiveness of the above method in spreading apparel design and arts and crafts culture, experimental validation analysis was conducted. The results show that the Fuzzy C-means algorithm improves PSNR by an average of 1.094 dB and SSIM by between 1.1% and 2.5% compared with the SVD-Means feature color extraction algorithm. The error before and after the adaptive optimization color compensation of artificial intelligence technology is only about 0.2%, and the MSE value of the texture generation network is between [1.5*10-3,3*10-3], and the error of its image generation quality is not more than 1‰. Based on artificial intelligence technology, it can fully obtain the elemental patterns and colors of arts and crafts culture and then innovate the style and shape of clothing design, which can also promote the dissemination and development of arts and crafts culture.
Analysis of the Impact of Carbon Finance on Digital Green Technology Innovation of Enterprises
Authors: Zhao Shuai , Hu Peiyao 
Published: January 2024

Abstract
Carbon finance, as a financial tool for adapting to and mitigating global climate change, can guide enterprises to help develop digital green technological innovation and ultimately realize the transition to a low-carbon economy. This paper selects relevant control variables and applies the spatial econometric model to analyze the impact of carbon financial trading policy on enterprises’ green technological innovation, and examines the different impacts of the policy on the number of green invention-based patent applications and the number of green utility model patent applications, respectively. To examine the heterogeneity of regions and enterprise size, the samples were further grouped. Finally, a gray correlation model is used to study the main drivers of the intrinsic interactions among the three systems of digital technology innovation, carbon finance, and industrial policy. Most of the gray correlations between technological innovation and carbon finance indicators are located between 0.5 and 0.7, and the average value of the correlations of all the indicators is higher than 0.60, with only four lower than 0.65, and the highest indicator is 0.666. It indicates that the correlation between carbon finance and digital green technological innovation among enterprises is high.
Research on Reinforcement Learning Algorithm-Based Practical Teaching and Reform Oriented to Enhancement of College Students’ Vocational Ability in Colleges and Universities
Authors: Hu Yuzi , Pan Jiajia 
Published: January 2024

Abstract
In this paper, we first explored the mathematical model of reinforcement learning - Markov decision-making process, solved the Bellman optimal solution by strategy iteration and strategy search method, and realized dynamic planning according to the Bellman optimal solution. Then, the students’ satisfaction with practical teaching and the level of students’ vocational ability cultivation were evaluated, and the influence of practical teaching on students’ vocational ability and vocational adaptability was analyzed. Finally, the reform path for practice teaching in colleges and universities was proposed using the reinforcement learning algorithm and impact analysis. The results show that the learning effect of students in the practice teaching environment is 3.8, the learning effect in the ordinary teaching environment is 3.25, and the effect of practice teaching is significant. The correlation coefficient between practice effect and students’ vocational ability is 0.537, which indicates that practice teaching affects students’ vocational ability. This study provides an important reference value for the construction of practical teaching in colleges and universities, as well as for the reform of the college education system.
The Construction of Online Interactive Teaching Mode of College English in the Background of Internet
Authors: Jiang Lijie 
Published: January 2024

Abstract
In this paper, the propagation law of online teaching knowledge is studied by constructing a learner online teaching interaction network to characterize the position of each learner in this social network. The SI model is used to portray the knowledge dissemination process in the online learning interactive network, fully considering the two types of nodes of teachers and learners as well as the different transfer rates of knowledge dissemination of the two types of nodes, the SI model is improved, and the kinetic equations of knowledge dissemination are constructed. Finally, with the help of Matlab software to simulate the knowledge propagation process in the online English learning of teachers and students, the model was examined, corrected and analyzed, respectively, so as to put forward the optimization strategy of online English teaching interaction mode in colleges and universities. The results show that the path process from t
0 to full dissemination is almost the same in the two online learning interaction networks with N
1 =2000 and N
2 =1000. The higher the degree of connection and participation among learners, the better the interactive learning effect. The optimization strategy for online English teaching interaction modes in colleges and universities proposed in this paper provides certain reference suggestions for improving learners’ interactive learning effectiveness.
Application of BIM technology in dynamic management and control of construction project costs
Authors: Liu Na , Yu Liying , Tong Guoyun 
Published: January 2024

Abstract
This paper analyzes and summarizes the difference between BIM technology and traditional methods in cost management, subdividing the cost index of construction projects into elemental price index, bill of quantities price index, index cost index, and calculating dynamic cost index of construction projects. Based on the cost performance index and schedule performance index, the schedule-cost two-dimensional model of BIM technology is formed to complete the assessment and control of cost performance in order to realize the value analysis of BIM technology in the dynamic cost management of the whole process of construction engineering. Analyze the dynamic cost management of BIM technology in the decision-making stage, design stage, and construction stage of construction projects with examples, focusing on the exploration of engineering cost problems in the construction stage, and analyze the project benefit rate of cost management with BIM technology. Through BIM modeling for collision and error checking and deepening the construction stage design, a total of 503 design collision and error problems are found in total, 15 design change orders are reduced, and about 1,629,480,000 yuan of economic benefits are generated.