Integrative analysis of high-throughput biological data: shrinkage correlation coefficient and comparative expression analysis

textThe focus for this research is to develop and apply statistical methods to analyze and interpret high-throughput biological data. We developed a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. This computational approach is not only applicable to DNA microarray analysis but is also applicable to proteomics data or any other high-throughput analysis methodology. The suppression of APY1 and APY2 in mutants expressing an inducible RNAi system resulted in plants with a dwarf phenotype and disrupted auxin distribution, and we used these mutants to discover what genes changed expression during growth suppression. We evaluated the gene expression changes of apyrase-suppressed RNAi mutants that had been grown in the light and in the darkness, using the NimbleGen Arabidopsis thaliana 4-Plex microarray, respectively. We compared the two sets of large-scale expression data and identified genes whose expression significantly changed after apyrase suppression in light and darkness, respectively. Our results allowed us to highlight some of the genes likely to play major roles in mediating the growth changes that happen when plants drastically reduce their production of APY1 and APY2, some more associated with growth promotion and others, such as stress-induced genes, more associated with growth inhibition. There is a strong rationale for ranking all these genes as prime candidates for mediating the inhibitory growth effects of suppressing apyrase expression, thus the NimbleGen data will serve as a catalyst and valuable guide to the subsequent physiological and molecular experiments that will be needed to clarify the network of gene expression changes that accompany growth inhibition.Institute for Cellular and Molecular Biolog

Mandarin's Impact on Poverty Alleviation: An Empirical Study Based on Economic and Social Interaction Dimensions

This paper studies the effect of Mandarin proficiency on poverty reduction and its mechanism. The China General Social Survey (CGSS) is taken as the data source. From the perspective of social integration, the poverty reduction effect of Putonghua and its mechanism are empirically studied from the perspective of social interaction, social fairness, and social trust. The findings showed that improving the ability to listen and speak Mandarin positively affects social interaction, social trust, and social fairness. It showed that Putonghua proficiency positively correlates with the suppression of economic poverty. After the occurrence of poverty, whether a sample of absolute poverty or relative poverty, the ability to listen and speak in Mandarin has a specific inhibitory effect on social interaction, social trust, and social fairness. After the occurrence of poverty, the frequency of social interaction, social trust, and social public since have been reduced to a certain extent. Specifically, the ability to express Mandarin has shown remarkable results in improving social interaction, and the ability to listen among ordinary people has shown remarkable results in enhancing social fairness. The results of this paper provide empirical evidence of poverty alleviation in China via Improving Mandarin Proficiency. This research is also of great significance for optimizing poverty alleviation paths through language in the post-poverty alleviation era

The Effect of Physical Activity on the Non-cognitive Ability of Adolescents: An Empirical Study on Big Five Personality Traits and Large Sample Data of CFPS 2020

Based on the Big Five personality trait dimensions of non-cognitive ability measures, the CFPS 2020 database was used as the basis, The self-answered questionnaires and messages were collected from the people under the age of 18. And information on physical activity were selected as the study sample from the total 28590 samples in this database, among which 1562 valid samples were used as the study subjects. And the corresponding options and answers were selected as the dependent variables related to the Big Five personality like responsibility, agreeableness, extraversion, and neuroticism. After constructing a model with logit regression and calculating the marginal effects, it empirically demonstrated that increasing the frequency of physical exercises (frequency) had positive effects on promoting or improving adolescents' sense of responsibility, agreeableness, extraversion, and neuroticism, the frequency of physical exercise (frequency) in the past 12 months was used as the dependent variable, the effects were different between urban and rural areas, age, and gender. There were differences between urban and rural areas, age and gender

Recent advances on fluid flow in porous media using digital core analysis technology

The scientific and engineering challenges of research on porous media have gained substantial attention in recent decades. These intricate issues span different disciplines and fields, manifesting in natural and industrial systems like soils, oil and gas reservoirs, tissues, plants, etc. Meanwhile, digital core analysis technology has rapidly developed, proving invaluable not just in oil and gas reservoirs development, but also in geothermal energy, carbon and hydrogen storage. The China InterPore Chapter and the Research Center of Multiphase Flow in Porous Media at China University of Petroleum (East China) have established a conference platform for global scholars to exchange ideas and research in porous media utilizing digital core analysis technology. The 6th International Conference on Digital Core Analysis & the 2023 China Interpore Conference on Porous Media was successfully held in Qingdao from July 5 to 7, 2023. The conference facilitated discussions among 150 participants, including over 20 invited experts from academia and industry, and the recent advances in research of fluid flow in porous media using digital core analysis technology were thoroughly presented.Document Type: EditorialCited as: Yang, Y., Horne, R. N., Cai, J., Yao, J. Recent advances on fluid flow in porous media using digital core analysis technology. Advances in Geo-Energy Research, 2023, 9(2): 71-75. https://doi.org/10.46690/ager.2023.08.0

Advances in porous media science and engineering from InterPore2020 perspective

    Natural, artificial, and biological porous media can be seen everywhere in our daily lives. Transport phenomena in porous media, such as flow, diffusion, reaction, adsorption and deformation, are encountered in a wide variety of practical applications and scientific interests over widely disparate length scales, from molecular, to pore, core, and field scales. However, determination of transport properties in porous media remains a challenging issue. During the 12th Annual Meeting of the International Society for Porous Media (InterPore), held online from August 31-September 4, 2020, advances on porous media science and engineering in very broad areas were presented. The meeting was attended by more than 750 participants from across the globe, and a significant milestone was achieved in the history of InterPore conferences due to its online interactive platform. Participants could access the pre-recorded talks, leave comments and questions, chat with each other, one week before the conference. Then, all the feedback related to a talk was discussed in the presence of the author during several Q&A sessions. Invited and Keynote talks were live, and were also recorded. Each Q&A session was moderated by two experts, who first reviewed the 8 contributions of their session and then summarized the questions for each talk. The author could further elaborate their work and answer the questions.Cited as: Cai, J., Hajibeygi, H., Yao, J., Hassanizadeh, S.M. Advances in porous media science and engineering from InterPore2020 perspective. Advances in Geo-Energy Research, 2020, 4(4): 352-355, doi: 10.46690/ager.2020.04.0

Advances in multiscale numerical and experimental approaches for multiphysics problems in porous media

Research on the scientific and engineering problems of porous media has drawn increasing attention in recent years. Digital core analysis technology has been rapidly developed in many fields, such as hydrocarbon exploration and development, hydrology, medicine, materials and subsurface geofluids. In summary, science and engineering research in porous media is a complex problem involving multiple fields. In order to encourage communication and collaboration in porous media research using digital core technology in different industries, the 5th International Conference on Digital Core Analysis & the Workshop on Multiscale Numerical and Experimental Approaches for Multiphysics Problems in Porous Media was held in Qingdao from April 18 to 20, 2021. The workshop was jointly organized by the China InterPore Chapter, the Research Center of Multiphase Flow in Porous Media at the China University of Petroleum (East China) and the University of Aberdeen with financial support from the National Sciences Foundation of China and the British Council. Due to the current pandemic, a hybrid meeting was held (participants in China met in Qingdao, while other participants joined the meeting online), attracting more than 150 participants from around the world, and the latest multi-scale simulation and experimental methods to study multi-field coupling problems in complex porous media were presented.Cited as: Yang, Y., Zhou, Y., Blunt, M. J., Yao, J., Cai, J. Advances in multiscale numerical and experimental approaches for multiphysics problems in porous media. Advances in Geo-Energy Research, 2021, 5(3): 233-238, doi: 10.46690/ager.2021.03.0

ASP: Automatic Selection of Proxy dataset for efficient AutoML

Deep neural networks have gained great success due to the increasing amounts of data, and diverse effective neural network designs. However, it also brings a heavy computing burden as the amount of training data is proportional to the training time. In addition, a well-behaved model requires repeated trials of different structure designs and hyper-parameters, which may take a large amount of time even with state-of-the-art (SOTA) hyper-parameter optimization (HPO) algorithms and neural architecture search (NAS) algorithms. In this paper, we propose an Automatic Selection of Proxy dataset framework (ASP) aimed to dynamically find the informative proxy subsets of training data at each epoch, reducing the training data size as well as saving the AutoML processing time. We verify the effectiveness and generalization of ASP on CIFAR10, CIFAR100, ImageNet16-120, and ImageNet-1k, across various public model benchmarks. The experiment results show that ASP can obtain better results than other data selection methods at all selection ratios. ASP can also enable much more efficient AutoML processing with a speedup of 2x-20x while obtaining better architectures and better hyper-parameters compared to utilizing the entire dataset.Comment: This paper was actually finished in 202

CUEING: a lightweight model to Capture hUman attEntion In driviNG

Discrepancies in decision-making between Autonomous Driving Systems (ADS) and human drivers underscore the need for intuitive human gaze predictors to bridge this gap, thereby improving user trust and experience. Existing gaze datasets, despite their value, suffer from noise that hampers effective training. Furthermore, current gaze prediction models exhibit inconsistency across diverse scenarios and demand substantial computational resources, restricting their on-board deployment in autonomous vehicles. We propose a novel adaptive cleansing technique for purging noise from existing gaze datasets, coupled with a robust, lightweight convolutional self-attention gaze prediction model. Our approach not only significantly enhances model generalizability and performance by up to 12.13% but also ensures a remarkable reduction in model complexity by up to 98.2% compared to the state-of-the art, making in-vehicle deployment feasible to augment ADS decision visualization and performance

Role of rumination and hope on negative life events and suicidal ideation under the background of normalization of pandemic prevention and control: A moderated mediation model

IntroductionThe study aimed to investigate the impact and mechanism of negative life events on college students' suicidal ideation during the COVID-19 pandemic and the buffering effect of hope under the background of normalization of pandemic.MethodsA total of 5211 participants took part in this study. Self-reported negative life events, rumination, hope and suicide ideation were measured using a range of questions and scales. Our research demonstrated that the incidence of suicidal ideation among college freshmen in the past week was higher during the COVID-19 pandemic than that before the pandemic. In this study, conditional process model 15 was used to verify the hypothetical model of rumination as a potential mediator and hope as a moderator.ResultsThe hypothesized moderated mediation model was verified significant (β = -0.047, 95% CI = [-0.061, -0.035]), and hope was found to moderate the direct effect of negative life events on suicidal ideation (β = -0.039, t = -2.937, 95% CI = [-0.065, -0.013]) as well as the indirect effect of through the mediator rumination (β = -0.134, t = -10.850, 95% CI = [-0.158, -0.110]).DiscussionWe found that rumination partially mediated the effect of negative life events on suicidal ideation, and hope buffered the direct and indirect effect of negative life events on suicidal ideation. The implications of the findings for clinical interventions are discussed, including the importance of hope arousal as a protective factor and rumination as a cognitive mechanism for emotion regulation under the background of normalization of pandemic

Lumbar posterior group muscle degeneration: Influencing factors of adjacent vertebral body re-fracture after percutaneous vertebroplasty

ObjectiveThe purpose of the study was to explore the influencing factors of adjacent vertebral re-fracture after percutaneous vertebroplasty (PVP) for osteoporosis vertebral compression fractures (OVCFs).MethodsWe retrospectively analyzed the clinical data of 55 patients with adjacent vertebral re-fracture after PVP operation for OVCFs in our hospital from January 2016 to June 2019, they were followed up for 1 year and included in the fracture group. According to the same inclusion and exclusion criteria, we collected the clinical data of 55 patients with OVCFs without adjacent vertebral re-fracture after PVP in the same period and included them in the non-fracture group. We performed univariate and multivariate logistic regression analysis on the influencing factors of adjacent vertebral re-fracture in patients with OVCFs after PVP.ResultsThere were significant differences in body mass index (BMI), bone mineral density (BMD) T-value, amount of bone cement injected, bone cement leakage, history of glucocorticoid use, cross-sectional area (CSA), cross-sectional area asymmetry (CSAA), fat infiltration rate (FIR), and fat infiltration rate asymmetry (FIRA) of lumbar posterior group muscles [multifidus (MF) and erector spinae (ES)] between the two groups (p < 0.05). There was no significant difference in sex, age, or time from the first fracture to operation, the CAS, CSAA, FIR, and FIRA of psoas major (PS) between the two groups (p > 0.05). Multivariate logistic regression showed that a higher dose of bone cement, greater CSAA and FIR of multifidus, and higher CSAA of erector spinae were independent risk factors for recurrent fractures of adjacent vertebrae after PVP.ConclusionThere are many risk factors for recurrent vertebral fracture after PVP in patients with OVCFs, and degeneration of paraspinal muscles (especially posterior lumbar muscles) may be one of the risks