Different methods for the threshold of epidemic on heterogeneous networks

AbstractThe study of the spread of epidemic on different social networks has attracted many attentions from researchers in different fields. One main topical problem is the threshold of transmission rate or the basic reproductive number on different social networks. Recently, several efficient methods on solving the threshold of epidemic on heterogeneous networks were proposed. In this paper, we summarize several methods and compare their advantages or disadvantages systematically

PL - 037 Effect of HiHiLo on autonomic nervous system and body functional status of excellent female rowers

Objective 12 female rowing athletes of Shanghai as research object of this study. 7 weeks of hypoxic experiment will be carried out on the study subjects. Monitoring of HRV and functional indexes of athletes during this period. To explore the effect of 3 weeks of Living High Training High Training Low（HiHiLo） training of female rowers ANS and functional status, and discussion on the relationship between ANS and functional status of athletes in HiHiLo. Methods 12 Shanghai elite female rowers for 3 weeks HiHiLo training. Simulated altitude from 2500m to 3200m, A total of seven weeks of HRV and biochemical function indexes were tested before and after hypoxia training. In addition, the HRV test of the athletes in a hypoxic exposure. According to the change characteristics of each index, analysis of the change of the athletes ANS in acute hypoxic exposure, and the evaluation of the effects of HiHiLo on ANS and functional status. Results 1. The results of HRV test showed that there was no significant difference in time domain and frequency domain between normal condition and low oxygen environment, But SDNN in hypoxia environment in higher than normal environment, RMSSD slightly lower than the normal environment, indicate that hypoxic environment for athletes of cardiovascular ANS regulation will change and PSNS tension decreased; TP decreased and LF/HF increased, but the change was not significant. 2. The detection of the three stages of the athletes found that there were no significant changes in the indicators of HRV. However, the SDNN、RMSSD and PNN50 indexes showed a certain change trend, that settled low oxygen, time domain index increased, and in hypoxia exposure within three weeks are maintained at high levels and hypoxia after the end of each indicator of the level of decline, as well as the domain indexes, the frequency domain indexes HF、LF and LF/HF also showed obvious change tendency. 3. After the beginning of the experiment, Hb、RBC continued to rise, and after three weeks of hypoxia reached the highest value, compared with before the experiment was increased by 7.7%, 5%, RBC and the experiment was significantly different (p<0.05), Hct increased 5.3% after 3 weeks of hypoxia. Hypoxia after the end of the experiment, RBC, Hb and Hct showed a downward trend, at the end of experiment were decreased by 5%, 3.4%, 3.5%(p>0.05); In this experiment, the BU, CK of the Shanghai women`s rowing athletes at each stage in the normal range, there was no significant difference, but there is a clear trend of change; There was no significant difference in the T of the athletes in the seven week test, but the change trend is obvious. The C was significantly decreased (p<0.05) in the second week after hypoxia exposure, and the follow-up period was significantly lower than that before the experiment(p<0.05) at second weeks. T/C value was significantly increased in the second week of hypoxia (p<0.05), the trend of change is roughly the same as T. The correlation analysis between biochemical function index and HRV was found that the correlation coefficient between PNN50 and T/C was 0.672(p<0.05), before hypoxia, LF/HF and T/C were negatively correlated with -0.825(p<0.01), LF/HF and T correlation coefficient -0.789(p<0.01); During the 3 week HiHiLo training, CK was significantly correlated with SDNN, HF and LF, respectively, and the correlation coefficients were -0.425(p<0.05), -0.43(p<0.05), -0.496(p<0.01), LF/HF and T were negatively correlated with -0.42(p<0.05); The tracking period athletes T were significantly positively correlated with SDNN, RMSSD, PNN50, HF in HRV index, correlation coefficients were 0.378(p<0.05), 0.443(p<0.01), 0.341(p<0.05), 0.371(p<0.05). In addition, the correlation coefficient between PNN50 and C was 0.411(p<0.05). Conclusions 1. The ANS of Shanghai female rowers will change in acute hypoxic exposure, SNS would be enhanced. 2. Three weeks of longer periods of hypoxia training will enable the athletes to enhance the PSNS activity of the ANS, and may make the ability of the regulating equilibrium state from SNS and PSNS, the changes of the ANS regulation of the athletes to the PSNS activity were enhanced, this may be the result of long time hypoxia stimulation and training, to a certain extent, it shows that the level of athletes` performance has been enhanced. 3. Functional status index of Shanghai women`s rowing athletes was well in 3 week HiHiLo training, Part of the improvement of the functional status indicators shows that the effect of the hypoxic training is obvious, The functional status of athletes showed a rising trend.   4. In the different stages of the experiment, there was a significant correlation between the HRV partial indexes and some biochemical indexes. This shows that there is a certain relationship between the ANS and functional status in the hypoxic training. Detection and evaluation of autonomic nervous function in hypoxic training can reflect the functional level of the body to a certain extent. This suggests that it is necessary to strengthen the research and application of ANS function evaluation in hypoxic training

PolyGET: Accelerating Polymer Simulations by Accurate and Generalizable Forcefield with Equivariant Transformer

Polymer simulation with both accuracy and efficiency is a challenging task. Machine learning (ML) forcefields have been developed to achieve both the accuracy of ab initio methods and the efficiency of empirical force fields. However, existing ML force fields are usually limited to single-molecule settings, and their simulations are not robust enough. In this paper, we present PolyGET, a new framework for Polymer Forcefields with Generalizable Equivariant Transformers. PolyGET is designed to capture complex quantum interactions between atoms and generalize across various polymer families, using a deep learning model called Equivariant Transformers. We propose a new training paradigm that focuses exclusively on optimizing forces, which is different from existing methods that jointly optimize forces and energy. This simple force-centric objective function avoids competing objectives between energy and forces, thereby allowing for learning a unified forcefield ML model over different polymer families. We evaluated PolyGET on a large-scale dataset of 24 distinct polymer types and demonstrated state-of-the-art performance in force accuracy and robust MD simulations. Furthermore, PolyGET can simulate large polymers with high fidelity to the reference ab initio DFT method while being able to generalize to unseen polymers

May the Force be with You: Unified Force-Centric Pre-Training for 3D Molecular Conformations

Recent works have shown the promise of learning pre-trained models for 3D molecular representation. However, existing pre-training models focus predominantly on equilibrium data and largely overlook off-equilibrium conformations. It is challenging to extend these methods to off-equilibrium data because their training objective relies on assumptions of conformations being the local energy minima. We address this gap by proposing a force-centric pretraining model for 3D molecular conformations covering both equilibrium and off-equilibrium data. For off-equilibrium data, our model learns directly from their atomic forces. For equilibrium data, we introduce zero-force regularization and forced-based denoising techniques to approximate near-equilibrium forces. We obtain a unified pre-trained model for 3D molecular representation with over 15 million diverse conformations. Experiments show that, with our pre-training objective, we increase forces accuracy by around 3 times compared to the un-pre-trained Equivariant Transformer model. By incorporating regularizations on equilibrium data, we solved the problem of unstable MD simulations in vanilla Equivariant Transformers, achieving state-of-the-art simulation performance with 2.45 times faster inference time than NequIP. As a powerful molecular encoder, our pre-trained model achieves on-par performance with state-of-the-art property prediction tasks

Diversities of disability caused by lung cancer in the 66 Belt and Road initiative countries: a secondary analysis from the Global Burden of Disease Study 2019

ObjectivesDue to the increase in life expectancy and the aging of the global population, the “Belt and Road” (“B&R”) countries are faced with varying degrees of lung cancer threat. The purpose of this study is to analyze the differences in the burden and trend of lung cancer disability in the “B&R” countries from 1990 to 2019 so as to provide an analytical strategic basis to build a healthy “B&R”.MethodsData were derived from the Global Burden of Disease 2019 (GBD 2019). Incidence, mortality, prevalence, the years lived with disability (YLDs), and disability-adjusted life years (DALYs) of lung cancer and those attributable to different risk factors were measured from 1990 to 2019. Trends of disease burden were estimated by using the average annual percent change (AAPC), and the 95% uncertainty interval (UI) was reported.ResultsChina, India, and the Russian Federation were the three countries with the highest burden of lung cancer in 2019. From 1990 to 2019, the AAPC of incidence, prevalence, mortality, and DALYs generally showed a downward trend in Central Asia (except Georgia) and Eastern Europe, while in China, South Asia (except Bangladesh), most countries in North Africa, and the Middle East, the trend was mainly upward. The AAPC of age-standardized incidence was 1.33% (1.15%–1.50%); the AAPC of prevalence, mortality, and DALYs from lung cancer in China increased by 24% (2.10%–2.38%), 0.94% (0.74%–1.14%), and 0.42% (0.25%–0.59%), respectively. A downward trend of the AAPC values of age-standardized YLD rate in men was shown in the vast majority of “B&R” countries, but for women, most countries had an upward trend. For adults aged 75 years or older, the age-standardized YLD rate showed an increasing trend in most of the “B&R” countries. Except for the DALY rate of lung cancer attributable to metabolic risks, a downward trend of the DALY rate attributable to all risk factors, behavioral risks, and environmental/occupational risks was shown in the vast majority of “B&R” countries.ConclusionThe burden of lung cancer in “B&R” countries varied significantly between regions, genders, and risk factors. Strengthening health cooperation among the “B&R” countries will help to jointly build a community with a shared future for mankind

Physiological, Anthropometric, and Motor Characteristics of Elite Chinese Youth Athletes From Six Different Sports

Several talent selection programs in elite sport schools are based on motor diagnostics for the purpose of recommending or transferring promising talents to general groups of sports; game sports, combat sports or endurance sports, and to more concrete sports such as gymnastics, skiing, or tennis. However, the predictive value of such testing is unclear. This study evaluated the concurrent validity of physiological performance prerequisites, body dimensions, as well as specific motor performances. The sample consisted of N = 97 youth athletes from all ninth grade classes of a Shanghai Elite Sport school belonging to six different sports including basketball (n = 7), fencing (n = 23), judo (n = 20), swimming (n = 10), table tennis (n = 15), and volleyball (n = 22). The performance diagnosis took place between September 2016 and March 2017, and comprised five physiological measurements of the heart rate at rest, vital capacity, systolic and diastolic blood pressure, and hemoglobin concentration in the blood, eighteen anthropometric parameters, and two motor tests on back strength and complex reaction speed. The aim of the study was to investigate whether U15 age group athletes participating in six different sports already at this age show a sport specific anthropometric, motor performance, and physiological profile which is in line with the specific requirements of each of the sports. A discriminant analysis and a Neural Network (Multilayer Perceptron) were used to test whether it is possible to discriminate between athletes of the six sports and to assign each individual of the Under-15 athletes to his own sport on the basis of a unique profile of the morphological, motor, and physiological prerequisites. All diagnostic methods exhibited medium to high validity to discriminate between the six different sports. The relevance of the eighteen body dimensions, five physiological measures, and two motor tests for talent identification was confirmed

Unbalanced development characteristics and driving mechanisms of regional urban spatial form: a case study of Jiangsu Province, China

Unbalanced regional development is widespread, and the imbalance of regional development in developing countries with rapid urbanization is increasingly apparent. This threatens the sustainable development of the region. Promoting the coordinated development of the region has become a hot spot of scientific research and a major practical need. Taking 99 counties of Jiangsu Province China, a typical coastal plain region, as the basic research unit, this paper explores the unbalanced development characteristics of the regional urban spatial form using three indicators: urban spatial expansion size, development intensity, and distribution aggregation degree. Then, their driving mechanisms were evaluated using spatial autocorrelation analysis, Pearson correlation analysis, linear regression, and geographically weighted regression. Our results found that the areas with larger urban spatial expansion size and development intensity were mainly concentrated in southern Jiangsu, where there was a positive spatial correlation between them. We found no agglomeration phenomenon in urban spatial distribution aggregation degree. From the perspective of driving factors: economics was the main driving factor of urban spatial expansion size; urbanization level and urbanization quality were the main driving factors of urban spatial development intensity. Natural landform and urbanization level are the main driving factors of urban spatial distribution aggregation degree. Finally, we discussed the optimization strategy of regional coordinated development. The quality of urbanization development and regional integration should be promoted in Southern Jiangsu. The level of urbanization development should be improved relying on rapid transportation to develop along the axis in central Jiangsu. The economic size should be increased, focusing on the expansion of the urban agglomeration in northern Jiangsu. This study will enrich the perspective of research on the characteristics and mechanisms of regional urban spatial imbalance, and helps to optimize and regulate the imbalance of regional urban development from multiple perspectives

Distinct miRNAs associated with various clinical presentations of SARS-CoV-2 infection.

MicroRNAs (miRNAs) have been shown to play important roles in viral infections, but their associations with SARS-CoV-2 infection remain poorly understood. Here, we detected 85 differentially expressed miRNAs (DE-miRNAs) from 2,336 known and 361 novel miRNAs that were identified in 233 plasma samples from 61 healthy controls and 116 patients with COVID-19 using the high-throughput sequencing and computational analysis. These DE-miRNAs were associated with SASR-CoV-2 infection, disease severity, and viral persistence in the patients with COVID-19, respectively. Gene ontology and KEGG pathway analyses of the DE-miRNAs revealed their connections to viral infections, immune responses, and lung diseases. Finally, we established a machine learning model using the DE-miRNAs between various groups for classification of COVID-19 cases with different clinical presentations. Our findings may help understand the contribution of miRNAs to the pathogenesis of COVID-19 and identify potential biomarkers and molecular targets for diagnosis and treatment of SARS-CoV-2 infection

Non-Parametric Change-Point Method for Differential Gene Expression Detection

We proposed a non-parametric method, named Non-Parametric Change Point Statistic (NPCPS for short), by using a single equation for detecting differential gene expression (DGE) in microarray data. NPCPS is based on the change point theory to provide effective DGE detecting ability.NPCPS used the data distribution of the normal samples as input, and detects DGE in the cancer samples by locating the change point of gene expression profile. An estimate of the change point position generated by NPCPS enables the identification of the samples containing DGE. Monte Carlo simulation and ROC study were applied to examine the detecting accuracy of NPCPS, and the experiment on real microarray data of breast cancer was carried out to compare NPCPS with other methods.Simulation study indicated that NPCPS was more effective for detecting DGE in cancer subset compared with five parametric methods and one non-parametric method. When there were more than 8 cancer samples containing DGE, the type I error of NPCPS was below 0.01. Experiment results showed both good accuracy and reliability of NPCPS. Out of the 30 top genes ranked by using NPCPS, 16 genes were reported as relevant to cancer. Correlations between the detecting result of NPCPS and the compared methods were less than 0.05, while between the other methods the values were from 0.20 to 0.84. This indicates that NPCPS is working on different features and thus provides DGE identification from a distinct perspective comparing with the other mean or median based methods