We propose a skeletonization algorithm that is based on an iterative points contraction. We make an observation that the local center that is obtained via optimizing the sum of the distance to k nearest neighbors possesses good properties of robustness to noise and incomplete data. Based on such an observation, we devise a skeletonization algorithm that mainly consists of two stages: points contraction and skeleton nodes connection. Extensive experiments show that our method can work on raw scans of real-world objects and exhibits better robustness than the previous results in terms of extracting topology-preserving curve skeletons.
Hemodialysis is the main alternative therapy for patients with end-stage renal disease; most of the hemodialysis centers in China are not designed together with the inpatient ward. During the hospitalization period, hemodialysis patients often move back and forth between wards and hemodialysis rooms because of the treatment needed. Hemodialysis patients are a special group of hospitalized patients, most of them are elderly patients. The overall basic diseases of the patients vary very much, and the cause of the disease is complex. Moreover, the chronic inflammation progresses slowly, and immune function declines. Some of the patient are seriously ill or even hav organ failure. All these factors affect the patients in general. Therefore, the transfer safety of patients during hospitalization is facing great challenges. The researchers reviewed the status of transshipment research in Chinese hemodialysis patients and laid the foundation for the research and development of related handover tools and perfect handover mode in the future.
This meta-analysis aimed to evaluate the effects of walking exercise on bowel preparation in patients undergoing colonoscopy.
PubMed, Web of Science, EMBASE, Ovid, The Cochrane Library, Wanfang Data, China National Knowledge Infrastructure, Chinese Science and Technology Periodical Database, and Chinese BioMedical Database were searched from their inception to January 2019. Randomized controlled trials (RCTs) and controlled clinical trials (CCTs) examining the effects of walking exercise in patients undergoing colonoscopy were considered for inclusion. After screening literature, extracting data and evaluating methodological quality, RevMan 5.3 software was used for meta-analysis.
Five studies (four RCTs and one CCTs) involved 984 participants were included. The results of meta-analysis demonstrated that the walking exercise group showed significantly higher improvements in the rate of adequate bowel preparation than the control group (risk ratio [RR] = 1.28, 95% confidence interval [CI] [1.03–1.58], P < 0.05). In addition, the walking exercise group had lower incidence of vomiting (RR = 0.39, 95% CI [0.23–0.68], P < 0.01) and abdominal pain (RR = 0.51, 95% CI [0.29–0.90], P < 0.05) with lower heterogeneity.
This systematic review and meta-analysis provided specific evidence that walking exercise during bowel preparation can improve the rate of adequate bowel preparation and reduce the incidence of vomiting and abdominal pain in patients undergoing colonoscopy. Since the conclusion of this meta-analysis was drawn based on the limited number of high-quality RCTs, more rigorous RCTs should be conducted in the future.
Objective Patients with H1N1 virus infection were hospitalized and quarantined, and some of them developed into acute respiratory failure, and were transfered to the medical intensive care unit of Beijing Ditan Hospital, Capital Medical University in Beijing, China.
Methods The clinical features and preliminary epidemiologic findings among 30 patients with confirmed H1N1 virus infection who developed into acute respiratory failure for ventilatory support were investigated.
Results A total of 30 patients (37.43 ± 18.80 years old) with 2009 influenza A (H1N1) related acute respiratory distress syndrome (ARDS) received treatment with mechanical ventilation, 15 cases of whom were male and 17 cases died of ARDS. Fatal cases were significantly associated with an APACHE Ⅱ score (P = 0.016), but not with PaO2/FIO2 (P = 0.912) and chest radiograph (P = 0.333). The most common complication was acute renal failure (n = 9). Five patients received extracorporeal membrane oxygenation (ECMO), 3 of whom died and the others survived. The major causes of death were multiple organ dysfunction syndrome (MODS) (39%), intractable respiratory failure (27%) and sepsis (20%).
Conclusions Most patients with respiratory failure due to influenza A (H1N1) virus infection were young, with a high mortality, particularly associated with APACHE ∥ score, secondary infection of lung or type 2 diabetes mellitus.
Objective Various immune cells in patients with CHB have been demonstrated to play critical roles in HBV infection. The goal of this study is to observe changes in Th17, Treg, Th1 and B lymphocytes from peripheral blood and to evaluate immune status of CHB patients undergoing antiviral treatment.
Methods Total of 49 CHB patients, 19 asymptomatic carriers and 29 healthy donors were included in our present study. The frequencies of peripheral Th17 cells (CD3+CD4+IL-17+Tcells), Treg cells (CD3+CD4+CD25+CD127- T cells), Th1 cells (CD3+CD4+IFN-γ T cells) and B lymphocytes in chronic hepatitis B (CHB) were analyzed by flow cytometry.
Results The frequency of Th17 cells increased after treatment for 6 months, but there was no statistically significant difference of IL-17 expression between baseline and 6 months after treatment. The frequencies of Treg cells, momory B cells and total CD19+ B cells decreased after antiviral treatment. The frequencies of Th1 cells and plasma cells increased after antiviral treatment.
Conclusions This study highlights that the reestablishment of immune function during antiviral treatment in CHB patients, which caused by the antiviral drugs or the patients themselves. CHB patients may exhibit varied responses to these antiviral drugs. It is essential to supplement immune therapy during the antiviral treatment, but Th17 may play a limited role in inflammation during antiviral treatment, targeting Th17 therapy may not be useful for CHB treatment. More time and more experiments are critical to explain it.
We propose and apply a simplified nowcasting model to understand the correlations between social attention and topic trends of scientific publications.
First, topics are generated from the obesity corpus by using the latent Dirichlet allocation (LDA) algorithm and time series of keyword search trends in Google Trends are obtained. We then establish the structural time series model using data from January 2004 to December 2012, and evaluate the model using data from January 2013. We employ a state-space model to separate different non-regression components in an observational time series (i.e. the tendency and the seasonality) and apply the “spike and slab prior” and stepwise regression to analyze the correlations between the regression component and the social media attention. The two parts are combined using Markov-chain Monte Carlo sampling techniques to obtain our results.
The results of our study show that (1) the number of publications on child obesity increases at a lower rate than that of diabetes publications; (2) the number of publication on a given topic may exhibit a relationship with the season or time of year; and (3) there exists a correlation between the number of publications on a given topic and its social media attention, i.e. the search frequency related to that topic as identified by Google Trends. We found that our model is also able to predict the number of publications related to a given topic.
First, we study a correlation rather than causality between topics’ trends and social media. As a result, the relationships might not be robust, so we cannot predict the future in the long run. Second, we cannot identify the reasons or conditions that are driving obesity topics to present such tendencies and seasonal patterns, so we might need to do “field” study in the future. Third, we need to improve the efficiency of our model by finding more efficient variable selection models, because the stepwise regression method is time consuming, especially for a large number of variables.
This paper analyzes publication topic trends from three perspectives: tendency, seasonality, and correlation with social media attention, providing a new perspective for identifying and understanding topical themes in academic publications.
To the best of our knowledge, we are the first to apply the state-space model to examine the relationships between healthcare-related publications and social media to investigate the relationships between a topic’s evolvement and people’s search behavior in social media. This paper thus provides a new viewpoint in the correlation analysis area, and demonstrates the value of considering social media attention in the analysis of publication topic trends.
Annular cavitator with water injection is one of the key parts of the long-range supercavitating vehiclepowered by water ramjet. In this paper, hydrodynamic properties of annular cavitator are studiednumerically. The standard k ~ ε turbulence model is coupled with the Reynolds Averaged Navier-Stokes(RANS) equations to model the natural supercavitation process. The multiphase flow is considered asa mixture of varying density and modeled by the mass exchange equations. To fully understand this process,numerical simulations were performed for different annular cavitators. Computational Fluid Dynamics(CFD) results, including the pressure distribution and forces acting on the cavitator surface, mass flowand pressure loss of water injection, various supercavity sizes, were obtained and analyzed. The pressuredistribution on the cavitator surface was significantly changed which resulted in 4 ~ 6% increase of thetotal drag of the vehicle. The results show that the mass flow and velocity of the injection water is mainlydependent on the tube size, while the total pressure loss of the water injection is mostly related to the outletpressure. Supercavity generated by annular cavitator is smaller than that of the discal one. Based on thecorrelation analysis of the supercavity size and other factors, it could be concluded that the contraction ofthe cavity size is mainly caused by the diffluent mass flow of the water injection.
The study of the flow characteristics of the solid-fluid two phase flow in the cutter suction dredger is very important for exploring the slurry formation mechanism and optimizing the operational parameters. In this study, standard k-ε model and Multiple Reference Frame are applied to numerically simulate flow field in and around the cutting system, then with the steady convergent result of the simulation as the initial condition, Discrete Phase Mode is used to solve the particle motion equation by fully coupling the continuous phase and the particles. The influence of suction flow velocity and cutter’s rotating speed on particles suction are analyzed, and effectively suctioned particles numbers are also quantitatively studied. The simulation result shows that the DPM model is able to simulate the movement of particles in and around the cutter suction dredger’s cutting system, in the fluid flow filed velocity vector and pressure distribution on different planes show different characteristics, and under higher suction velocity and lower cutter rotating speed more particles are suctioned into the suction inlet. The results can help better understand flow characteristics of solid-fluid 2-phase-flow of cutter suction dredger’s cutting system, and provide theoretical support for relative system design and operational parameters optimization.
A number of deep neural networks have been proposed to improve the performance of document ranking in information retrieval studies. However, the training processes of these models usually need a large scale of labeled data, leading to data shortage becoming a major hindrance to the improvement of neural ranking models’ performances. Recently, several weakly supervised methods have been proposed to address this challenge with the help of heuristics or users’ interaction in the Search Engine Result Pages (SERPs) to generate weak relevance labels. In this work, we adopt two kinds of weakly supervised relevance, BM25-based relevance and click model-based relevance, and make a deep investigation into their differences in the training of neural ranking models. Experimental results show that BM25-based relevance helps models capture more exact matching signals, while click model-based relevance enhances the rankings of documents that may be preferred by users. We further proposed a cascade ranking framework to combine the two weakly supervised relevance, which significantly promotes the ranking performance of neural ranking models and outperforms the best result in the last NTCIR-13 We Want Web (WWW) task. This work reveals the potential of constructing better document retrieval systems based on multiple kinds of weak relevance signals.
Enolases are enzymes in the glycolytic pathway, which catalyse the reversible conversion of D-2-phosphoglycerate into phosphoenol pyruvate in the second half of the pathway. In this research, the effects of α-enolase (ENO1) on steroid reproductive-related hormone receptor expression and on hormone synthesis of primary granulosa cells from goose F1 follicles were studied.
Material and Methods
Primary granulosa cells from the F1 follicles of eight healthy 8-month-old Zi geese were separated and cultured. An ENO1 interference expression vector was designed, constructed and transfected into primary cultured granulosa cells. The mRNA expression levels of follicle-stimulating hormone receptor (FSHR), luteinising hormone receptor (LHR), oestrogen receptor α (ER α), oestrogen receptor β (ER β), growth hormone receptor (GHR) and insulin-like growth factor binding protein-1 (IGFBP-1) in the cells were evaluated as were the secretion levels of oestradiol, activin, progesterone, testosterone, inhibin and follistatin in cell supernatant.
α-enolase gene silencing reduced the expression of FSHR, LHR, ERα, ERβ, GHR, and IGFBP-1 mRNA, potentiated the secretion of oestrogen, progesterone, testosterone, and follistatin of granulosa cells, and hampered the production of activin and inhibin.
ENO1 can regulate the reactivity of granulosa cells to reproductive hormones and regulate cell growth and development by adjusting their hormone secretion and reproductive hormone receptor expression. The study provided a better understanding of the functional action of ENO1 in the processes of goose ovary development and egg laying.