BACKGROUND:It has been reported that the incidence of Parkinson's disease (PD) in men is 1.5 times that of women, which is easily associated with the protective effect of estrogens on the dopaminergic system. However, the exact direction and magnitude of the effect of sex hormones on PD risk have not been clarified. This study aimed to evaluate the sex-specific association between PD and sex hormones and their related phenotypes using Mendelian randomization (MR). METHOD:We utilized summary statistics from seven sex-specific genome-wide association studies (GWAS), including the UK Biobank, FinnGen, the INTERVAL Study, and the International Parkinson's Disease Genomics Consortium. Using univariable MR (UVMR) and multivariable MR (MVMR), we investigated causal relationships between genetically predicted sex hormone levels and PD, as well as sex hormone-related traits. RESULT:We found a negative genetic correlation between PD and total testosterone levels (rg = -0.019, p = 0.046) and bioavailable testosterone levels (rg = -0.028, p = 0.019) among the entire population. UVMR results suggested that genetically predicted elevated bioavailable and total testosterone levels were associated with a reduced risk of PD in the entire population. When evaluating reverse causation, we found that genetically predicted female PD was associated with lower levels of sex hormone-binding globulin. Using MVMR, we further identified a suggestive association between genetically predicted total testosterone levels and a lower risk of PD. CONCLUSION:Based on our findings, we believe that there may be a potential association between genetically determined testosterone levels and the risk of PD.

Purpose: Human papillomavirus (HPV) infection is a prevalent sexually transmitted infection worldwide, with its persistence being a significant factor in the development of cervical cancer and precancerous lesions. Understanding the prevalence and genotypes distribution of HPV can aid in the implementation of more focused strategies for cervical cancer prevention and treatment. This study aimed to investigate the prevalence and genotype distribution of HPV infection among outpatient-based populations in Wuhan, China. Methods: Our study retrospectively analyzed the results of cervical HPV screening in 14,492 outpatient women. The cervicovaginal infection of 18 high-risk genotypes and 10 low-risk genotypes were analyzed by PCR and reverse dot hybridization techniques. Results: The overall prevalence of HPV infection in the outpatient female population was 15.33%, with a predominance of single infection and a predominance of dual infection among multiple infections. The top five genotypes in terms of prevalence of HR-HPV and LR-HPV were HPV-52 (3.77%), 53 (1.46%), 16 (1.31%), 58 (1.19%), 39 (1.18%) for HR-HPV, and HPV-54 (1.23%), 61 (1.08%), 81 (1.04%), 42 (0.87%), 44 (0.70%) for LR-HPV. Two peaks of HPV infection prevalence were observed among women under 25 years (22.88%) and over 56 years (24.26%). The prevalence and genotype distribution of HPV infection varied among different outpatient populations, with higher rates of HPV single infection, multiple infections, and infection across all ages observed in the gynecology outpatient population compared to the health check-up population. Conclusion: This study revealed the HPV prevalence and genotype distribution among different outpatient populations in Wuhan city, which may provide guidance for HPV vaccination and cervical cancer prevention strategies in the region.

The massive generation of time-series data by largescale Internet of Things (IoT) devices necessitates the exploration of more effective models for multivariate time-series forecasting. In previous models, there was a predominant use of the Channel Dependence (CD) strategy (where each channel represents a univariate sequence). Current state-of-the-art (SOTA) models primarily rely on the Channel Independence (CI) strategy. The CI strategy treats all channels as a single channel, expanding the dataset to improve generalization performance and avoiding inter-channel correlation that disrupts long-term features. However, the CI strategy faces the challenge of interchannel correlation forgetting. To address this issue, we propose an innovative Mixed Channels strategy, combining the data expansion advantages of the CI strategy with the ability to counteract inter-channel correlation forgetting. Based on this strategy, we introduce MCformer, a multivariate time-series forecasting model with mixed channel features. The model blends a specific number of channels, leveraging an attention mechanism to effectively capture inter-channel correlation information when modeling long-term features. Experimental results demonstrate that the Mixed Channels strategy outperforms pure CI strategy in multivariate time-series forecasting tasks.

Background: The incidence of cervical cancer in patients younger than 35 years old has recently increased in China. As a preventable disease, the risk of cervical cancer is associated with health behavior, i.e., the utilization of health services. The objective of this study was to determine risk factors in women aged 21–35 years old with cervical cancer from a health service utilization perspective in rural China.Methods: An unmatched case-control study was conducted with 140 women in the case group and 140 in the control group in 10 counties in Hunan Province from September 2020 to March 2021. Assumptions in the Behavioral Model of Health Services Utilization were considered to measure factors associated with cervical cancer. Risk factors were identified through binary logistic analysis and results were expressed as odds ratios (OR) and 95% confidence intervals (CI).Results: The mean age of the case group was 30.94 years with a Standard Deviation (SD) of 2.834 and the control group was 32.49 years (4.731) respectively. Parity (OR=3.861), disturbed sleep (OR=1.961), remembering (OR=1.746) and drowsy (OR=1.481) were risk factors of cervical cancer. Senior high school (OR=0.063), college degree or above (OR=0.041), peasantry (OR=0.040), enterprise staff (OR=0.074), higher monthly income, the nearest medical organization is a county-level public hospital (OR=0.089) and tangible support (OR=0.798) were found to be protective.Conclusions: Controllable factors such as accessibility to health services, social support and self-perceived symptoms were significantly associated with the risk of cervical cancer. Promoting health service utilization is a key way to prevent cervical cancer in resource-limited areas.

As many digital twin papers were devoted to simulation models capable of predicting system states given some parameters, this work-in-progress paper focuses on its inverse problem, Parameter Identification (PI), which aims to determine the optimal parameters of simulation models that produce states that best match the physical system. We handle the task of PI as a dynamic optimization problem and propose a gray-box evolutionary dynamic optimization (EDO) framework to track parameters when the states vary with time. The main idea is to enhance EDO by building an inverse data-driven model to predict the location of the optimal parameters. We also present a case study of nuclear reactor digital twin, to explain how to apply the proposed framework.

Background: China is facing with a crisis of the aging population.After the implementation of the latest fertility policy, the research on fertility related issues is urgent.Objective: The objective of this study is to explore the fertility values among women of childbearing age and the socio-demographic factors associated with it under the background of three-child policy, which is helpful to cope with the aging of the population.Methods: This study was conducted among 383 women of childbearing age who met the inclusion criteria using a general information questionnaire and the fertility values questionnaire from May to August 2021 in Hunan Province, China.Data were collected on the women's socio-demographic characteristics and fertility values.The descriptive statistics, t-test and analysis of variance were used for data analysis.Results: The total mean score of the positive values was 43.55 ± 10.10, and that of the negative values was 50.87 ± 13.85.There were significant differences in the scores of the overall positive and negative values, as well as scores of each dimension (p < 0.01).The item mean score of the overall negative values (3.38 ± 0.93) was higher than that of the overall positive values (2.90 ± 0.67).Among the positive values, "emotional value" (4.26 ± 0.93) scored the highest, while "worrying about life changes" (3.88 ± 1.10) scored the highest among the negative values.There were significant differences in both the positive and negative values in terms of age, marital status, and "only-child" women or not (p < 0.05).Conclusion: The fertility values among women of childbearing age in Hunan Province were relatively negative, especially, excessive worries about life change since having a child, which

Background Mindfulness-based interventions (MBIs) can improve the symptoms and psychological well-being of patients with breast cancer. However, standard MBIs are an 8-week program delivered face-to-face, which may be inconvenient for patients with cancer. Many attempts have been made to adapt MBIs to increase their accessibility for patients with cancer while maintaining their therapeutic components and efficacy. Objective This study aimed to investigate the effectiveness of a 4-week internet-delivered mindfulness-based cancer recovery (iMBCR) program in reducing symptom burden and enhancing the health-related quality of life (HRQoL) of patients with breast cancer. Methods A total of 103 postoperative patients with breast cancer (stages 0 to IV) were randomly assigned to an iMBCR group (4-week iMBCR; n=51, 49.5%) or a control group (usual care and 4-week program of health education information; n=52, 50.5%). The study outcomes included symptom burden and HRQoL, as measured by the MD Anderson Symptom Inventory and the Functional Assessment of Cancer Therapy-Breast scale. All data were collected at baseline (T0), after the intervention (T1), and at 1-month follow-up (T2). Data analysis followed the intention-to-treat principle. Linear mixed models were used to assess the effects over time of the iMBCR program. Results Participants in the iMBCR group had significantly larger decreases in symptom burden than those in the control group at T1 (mean difference –11.67, 95% CI –16.99 to –6.36), and the decreases were maintained at T2 (mean difference –11.83, 95% CI –18.19 to –5.46). The HRQoL score in the iMBCR group had significantly larger improvements than that in the control group at T1 and T2 (mean difference 6.66, 95% CI 3.43-9.90 and mean difference 11.94, 95% CI 7.56-16.32, respectively). Conclusions Our preliminary findings suggest that the iMBCR program effectively improved the symptom burden and HRQoL of patients with breast cancer, and the participants in the iMBCR group demonstrated good adherence and completion rates. These results indicate that the iMBCR intervention might be a promising way to reduce symptom burden and improve HRQoL of patients with cancer. Trial Registration Chinese Clinical Trial Registry ChiCTR2000038980; http://www.chictr.org.cn/showproj.aspx?proj=62659

目前,扩展有限状态机的测试问题为基于扩展有限机模型获取合适的迁移路径,然后根据这些路径导出测试数据.针对提高基于扩展有限状态机模型生成测试用例效率的目的,采用了将扩展有限状态机模型状态迁移图转换为状态迁移树的方法,通过对扩展有限状态机状态迁移树的分析,获取基于该树的测试路径,再根据扩展有限状态机模型的迁移信息表以及迁移路径的可行性,分析且构造测试用例,最终得出该方法有效减少了测试用例生成的复杂性,提高了基于扩展有限状态机模型的测试效率.

为了优化目前粒子群算法比较容易陷入局部最优、后期收敛过慢等的缺陷,在本文提出了一种改进惯性权重参数来优化算法的方法.其中结合了差分进化算法中的变异算子的操作来提升算法的自适应并且对算法的速度和搜索空间进行边界限制以防止粒子跳出所规定的搜索空间.选择相应的测试函数,使用Matlab软件将提出的改进算法与其他两种算法进行仿真实验对比,结果表明,本文所提出的算法在后期收敛速度以及取得适应度值的稳定性上有一定的提升.

Objective: To understand the evidence-based practice readiness of developing evidence application projects in a 3A-level general hospital in Beijing, to identify barriers to evidence-based practice and to promote the successful application of evidence.Methods: All the clinical nurses who were going to participate in the application units of the evidence-based practice project were selected as the survey objects, and the self-made "Basic Information Questionnaire" and "Clinical Readiness to Evidence-based Nursing Assessment (CREBNA)" were used to conduct the survey.The total amounts and subscales were calculated.The factors that influence the score of the total scale were scored and analyzed. Results:The CREBNA total score was (119.87±19.18), the evidence subscale score was (47.94±8.54), the organizational environmental subscale score was (36.09±6.11),and the facilitator subscale score was (35.83±7.56).Univariate analysis showed that the total score of the scale was related to years of work, scientific research experience, knowledge of evidence-based care, and participation in evidence-based practice. Conclusion:The current evidence-based practice preparation situation is good.It is feasible to carry out evidence-based practice activities in the hospital.The follow-up development plan should be made based on the corresponding obstacle factors.

测试用例的生成在软件测试中起到关键性的作用,然而在全路径覆盖这一准则中,往往会遇到极少数路径被遗忘等问题.针对此问题,文章提出了一种面向路径的测试用例生成方法,即贝叶斯网络与人工鱼群组合算法.首先,将表示各参数间的关系引入贝叶斯网络,达到路径覆盖准则的效果.然后,使用人工鱼群算法对近优的贝叶斯网络模型进行搜索获取测试用例集,进一步提高效率.实验结果表明:与已有的方法相比,在满足路径覆盖的同时,该方法在性能上有明显优势.

Network contains a large number of interaction between the individual and the individual system.In recent years, the scientists find a large number of power-law distribution phenomenon in the research of complex networks. The power-law distribution phenomenon exists not only in the page clicks, but also in the number of micro- blog access. In this paper, we use API technology of Sina micro-blog to capture the recent micro-blog data, make the data cleaning and statistic , by analysing the final statistical results,we find that the phenomenon of power-law distribution also exists in the number of forwards in Sina micro-blog. Only a few micro-blog, can be a hot micro-blog which has a large number of reading and forwarding,in contrast the vast majority of others have very few number of reading and forwarding.

A grading median filtering algorithm was proposed to offset the defect of adaptive median filter ( AMF) that it left some black plaque after filtering images corrupted by high density salt and pepper noises. Through twice filter to the noise image with small size win-dow,compared with bigger ones, it reduced the blur degree of result image. For the first time,it eliminated the salt noise by using median filter ( MF ) to noise pixels, and then wiped off the black plaque by replacing pepper noise pixels with the median of the noise free pixels in its 8-neighborhood. Lastly, the simulation result shows, our algorithm either has the good capability to filter the low density noises as well as AMF or has the ability to filter higher density salt and pepper noises in image.

Cognitive robot is so amazing and challengeable for its human-like behavior, especially for object recognition which goes through detection and recognition processes. Each part will be involved with the difficult technologies. In this paper a human-like object recognition system is built and three hypothesizes are proposed which based on cognitive psychology. This system aims to address objects which refers to detect, to recognize and to learn. In learning part, it could be trained based on learning algorithms. New category or new ascription will be added in this cognitive system through human-robot interaction. Additionally, three experiments were implemented to show the validity of our system. Target object is located from indoor complicate scene in the first experiment. Then, the second experiment aims to recognize given object through searching and matching from given image library. The third experiment shows how to find a special object with given class which performs very well in indoor scenario.

In this paper, we consider a HIV infection model with CTL-response delay and analyze the effect of time delay on stability of equilibria. We obtain the global stability of the infection-free equilibrium and give sufficient conditions for the local stability of the CTL-absent equilibrium and CTL-present equilibrium. By choosing the CTL-response delay τ as a bifurcation parameter, we prove that the CTL-present equilibrium is locally asymptotically stable in a range of delays and a Hopf bifurcation occurs as τ crosses a critical value. Numerical simulations are given to support the theoretical results.

This paper presents a modified method of the new edge-directed image interpolation algorithm. The basic idea is to first estimate the properties of the pixels to be interpolated and then calculate the unknown values based on different interpolation formulas. The improvement is that we propose a sample-points-selection from a statistical standpoint before interpolation to solve the problem of covariance mismatch in high frequency regions, and a special interpolation scheme on edge pixels based on Canny detector to avoid edge blurring. Experimental results show that our algorithm performs higher objective quality when applied to high-contrast image.

Redundant invariants increase processing time and memory consumption, which make serious effect on the application of invariants. The elimination of invariant redundancy is an important part in the invariant study. Now most methods of invariant redundancy elimination are based on optimization of invariants detecting tool which lack the principles analyse and system solutions of redundant invariants themselves. This paper first analyses the theory about classification and forming reasons of redundant invariant and then discusses the judgement of three kinds of invariant redundancy: equivalent redundancy, transitivity redundancy and implicating redundancy. Finally, the paper proposes the algorithms of eliminating invariant redundancy. The study has great value to the application of invariants which can significantly improves the efficiency by saving the time and space in processing.

According to the method of CPU chip application validation,this paper presents the test process and design of hardware platform used for SM8260 Cache application validation in write-through mode.It analyzes the initial process of SM8260 L1 Cache and L2 Cache,carries out benchmark tests and large array tests on write-through mode.Test results indicate that the use of L2 Cache can improve system performance in embedded system to some extent in the case of large array.

P2P storage systems have a lot of attractive advantages, such as self-organizing, scalability, robust and fault-tolerant. Unfortunately, there are some problems in real network conditions, especially, when considering asynchronous wide-area networks, where messages may be delayed indefinitely and nodes may fail. So, failure detector is one of basic components to build a reliable P2P storage systems. Considering the highly dynamic characteristics of distributed system, a novel dynamic failure detector, which can combine heartbeat strategy with unbiased grey prediction model, is designed to improve the failure detection quality of service (QoS) according to the application needs and network environment changes. The results show that, on the basis of the algorithm implementation failure detector has better performance. Compared to other failure detector, ours is much efficient and adaptive.

Dynamic likely program invariant detection technology is an available instrument for discovering contract from large program in non-formal description. It is of benefit to contract technology exerting more influence on program quality assurance. Since the research of invariant detection technology has just started that the rough detection usually use hypothesis verification approach which relies on the experience of the detector and his degree of understanding of the detected program so that there is serious lack of accuracy and efficiency. This paper tempts to divide the invariants into two kinds that one is called functional invariant and the other is non-functional type based on relational data theory before starting the invariant detection. The paper focuses on the approach of detecting functional likely invariant, which accomplish detecting existence of them by discovering functional dependence set of the program variable at first and then detecting the forms of the existent invariants after deducing the function dependence set. Experiments demonstrate that this approach not only solves the problems of blind detection to improve the efficiency but also reduces the possibility of missing important functional invariants compared with the traditional hypothesis verification approach such as Daikon.