scholarly journals Air Pollutants’ Concentrations Are Associated with Increased Number of RSV Hospitalizations in Polish Children

2021 ◽  
Vol 10 (15) ◽  
pp. 3224
Author(s):  
August Wrotek ◽  
Artur Badyda ◽  
Piotr O. Czechowski ◽  
Tomasz Owczarek ◽  
Piotr Dąbrowiecki ◽  
...  
Keyword(s):  
Air Pollutants ◽  
Regression Models ◽  
Short Term ◽  
Air Contamination ◽  
Basic Model ◽  
Annual Periodicity ◽  
Interaction Scheme ◽  
Full Interaction ◽  
Syncytial Virus ◽  
General Regression

Respiratory syncytial virus (RSV) contributes significantly to pediatric hospitalizations. An association between air pollution and an increased number of RSV cases has been suggested. We sought to evaluate the short-term impact of air pollutants on RSV hospitalizations in Polish children in the period 2010–2019. Daily concentrations of PM10 and PM2.5 (particulate matter with an aerodynamic diameter less than or equal to 10 μm and 2.5 μm, respectively) and nitrogen dioxide (NO2) were analyzed in general regression models (GRM) to establish their influence and full interaction scheme. Significant seasonal and annual periodicity among 53,221 hospitalizations was observed; finally, data from the 2012–2019 RSV high-risk seasons created models for seven agglomerations. The addition of PM2.5, PM10, and NO2 to the basic model for RSV seasonality explained 23% (4.9–31%, univariate model) to 31.4% (8.4–31%, multivariate model) of the variance in RSV hospitalizations. A 10 μg/m3 increase in PM2.5, PM10, and NO2 concentrations was associated with 0.134 (0.087–0.16), 0.097 (0.031–0.087), and 0.212 (0.04–0.29) average increases in hospitalizations, respectively. In the multivariate models, PM2.5, PM10, and NO2 alone, as well as PM2.5–NO2, PM2.5–PM10, and PM10–NO2 interactions, were associated with hospitalizations in some of the locations, while the metaregression showed statistically significant interactions between each of the pollutants, and between the pollutants and the year of the study. The inclusion of PM2.5, PM10, and NO2 in GRM explains a significant number of RSV hospitalizations. The pollutants act alone and interact together in a varied manner. Reducing air contamination might decrease the costs of hospital healthcare.

scholarly journals A novel causality-centrality-based method for the analysis of the impacts of air pollutants on PM2.5 concentrations in China

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bocheng Wang
Keyword(s):  
Air Pollutants ◽  
Regression Models ◽  
Large Population ◽  
Vital Role ◽  
Superior Performance ◽  
Causal Direction ◽  
Northern Cities ◽  
Main Components ◽  
Surrounding Areas ◽  
Centrality Analysis

AbstractIn this paper, we analyzed the spatial and temporal causality and graph-based centrality relationship between air pollutants and PM2.5 concentrations in China from 2013 to 2017. NO2, SO2, CO and O3 were considered the main components of pollution that affected the health of people; thus, various joint regression models were built to reveal the causal direction from these individual pollutants to PM2.5 concentrations. In this causal centrality analysis, Beijing was the most important area in the Jing-Jin-Ji region because of its developed economy and large population. Pollutants in Beijing and peripheral cities were studied. The results showed that NO2 pollutants play a vital role in the PM2.5 concentrations in Beijing and its surrounding areas. An obvious causality direction and betweenness centrality were observed in the northern cities compared with others, demonstrating the fact that the more developed cities were most seriously polluted. Superior performance with causal centrality characteristics in the recognition of PM2.5 concentrations has been achieved.

Reasoning over temporal knowledge graph with temporal consistency constraints

2021 ◽  
pp. 1-10
Author(s):  
Xiaojun Chen ◽  
Shengbin Jia ◽  
Ling Ding ◽  
Yang Xiang
Keyword(s):  
Short Term Memory ◽  
Knowledge Graph ◽  
Temporal Consistency ◽  
Short Term ◽  
Basic Model ◽  
Consistency Constraints ◽  
Memory Network ◽  
Long Short Term Memory ◽  
Relation Prediction ◽  
Time Information

Knowledge graph reasoning or completion aims at inferring missing facts by reasoning about the information already present in the knowledge graph. In this work, we explore the problem of temporal knowledge graph reasoning that performs inference on the graph over time. Most existing reasoning models ignore the time information when learning entities and relations representations. For example, the fact (Scarlett Johansson, spouse Of, Ryan Reynolds) was true only during 2008 - 2011. To facilitate temporal reasoning, we present TA-TransRILP, which involves temporal information by utilizing RNNs and takes advantage of Integer Linear Programming. Specifically, we utilize a character-level long short-term memory network to encode relations with sequences of temporal tokens, and combine it with common reasoning model. To achieve more accurate reasoning, we further deploy temporal consistency constraints to basic model, which can help in assessing the validity of a fact better. We conduct entity prediction and relation prediction on YAGO11k and Wikidata12k datasets. Experimental results demonstrate that TA-TransRILP can make more accurate predictions by taking time information and temporal consistency constraints into account, and outperforms existing methods with a significant improvement about 6-8% on Hits@10.

scholarly journals The Effect of Remittances on Poverty in the Emerging Countries of the European Union

2019 ◽  
Vol 11 (12) ◽  
pp. 3265 ◽  
Author(s):  
Anca Mehedintu ◽  
Georgeta Soava ◽  
Mihaela Sterpu
Keyword(s):  
European Union ◽  
Statistical Analysis ◽  
Economic Crisis ◽  
Regression Models ◽  
Emerging Countries ◽  
Time Dependent ◽  
The European Union ◽  
Short Term ◽  
Growth Trend ◽  
Poverty Threshold

In this paper we study the evolution of remittances and risk of poverty threshold for nine emerging countries in the European Union and analyzed the evolution and trend of the share of remittances in the risk of poverty threshold. The analysis was performed on data taken from the Eurostat database for the period 2005–2017. The statistical analysis of the data showed that the evolution of both remittances and risk of poverty threshold was heavily influenced by the global economic crisis. Although after the crisis, the risk of poverty threshold has seen a growing trend in all emerging countries, the remittances have experienced sinuous variations, dramatic declines for some of the countries (drastically for Romania and Latvia) and significant increases for others (Hungary). The results of the analysis using time-dependent regression models lead to the conclusion that, although the share of remittances in risk of poverty threshold diminished abruptly after the 2009 economic crisis, in the short term it is expected to maintain a growth trend for most of the analyzed countries (Bulgaria, Czechia, Hungary, Lithuania, Poland, Romania, and Slovakia), followed downward tendency after 2018 for Bulgaria and Romania, and after 2020 for Hungary and Lithuania. For Latvia and Estonia, both quadratic and cubic models estimate a decreasing evolution.

Short-Term Multinodal Load Forecasting Using a Modified General Regression Neural Network

2011 ◽  
Vol 26 (4) ◽  
pp. 2862-2869 ◽  
Author(s):  
Kenji Nose-Filho ◽  
Anna Diva Plasencia Lotufo ◽  
Carlos Roberto Minussi
Keyword(s):  
Neural Network ◽  
Load Forecasting ◽  
General Regression Neural Network ◽  
Short Term ◽  
General Regression

scholarly journals A comparison of surgical pulmonary embolectomy and catheter-directed lysis for life-threatening pulmonary emboli

2019 ◽  
Vol 30 (3) ◽  
pp. 388-393 ◽  
Author(s):  
Amalia A Winters ◽  
Michael J McDaniel ◽  
Jose N Binongo ◽  
Rena C Moon ◽  
Wissam A Jaber ◽  
...  
Keyword(s):  
Regression Models ◽  
Pulmonary Emboli ◽  
Short Term ◽  
Pulmonary Embolectomy ◽  
Treatment Groups ◽  
Catheter Directed Thrombolysis ◽  
Risk Patients ◽  
Life Threatening ◽  
Rv Function

Abstract OBJECTIVES Patients with life-threatening pulmonary emboli (PE) have traditionally been treated with anticoagulation alone, yet emerging data suggest that more aggressive therapy may improve short-term outcomes. The purpose of this study was to compare postoperative outcomes between catheter-directed thrombolysis (CDL) and surgical pulmonary embolectomy (SPE) in the treatment of life-threatening PE. METHODS A retrospective single-centre observational study was conducted for patients who underwent SPE or CDL at a single US academic centre. Preprocedural and postprocedural echocardiographic data were collected. Unadjusted regression models were constructed to assess the significance of the between-group postoperative differences. RESULTS A total of 126 patients suffered a life-threatening PE during the study period [60 SPE (47.6%), 66 CDL 52.4%]. Ten (24.4%) SPE patients and 10 (15.2%) CDL patients had massive PEs marked by preprocedural hypotension. Six (10.0%) SPE patients and 4 (6.0%) CDL patients suffered a preprocedure cardiac arrest (P = 0.41). In-hospital mortality rate was 3.3% (2) for SPE, and 3.0% (2) for CDL (P = 0.99). SPE patients were more likely to require prolonged ventilation (15.0% vs 1.5%, P = 0.01). No significant differences were found in other major complications. At baseline echocardiography, 76.9% of SPE patients and 56.9% of CDL patients had moderate or severe right ventricular (RV) dysfunction. Both treatment groups showed marked and durable improvement in echocardiographic markers of RV function from baseline at midterm follow-up. CONCLUSIONS Both SPE and CDL can be applied to well-selected high-risk patients with low rates of morbidity and mortality. Further research is necessary to delineate which patients would benefit most from either SPE or CDL following a life-threatening PE.

Land Use Regression Models for Ultrafine Particles and Black Carbon Based on Short-Term Monitoring Predict Past Spatial Variation

2015 ◽  
Vol 49 (14) ◽  
pp. 8712-8720 ◽  
Author(s):  
Denise R. Montagne ◽  
Gerard Hoek ◽  
Jochem O. Klompmaker ◽  
Meng Wang ◽  
Kees Meliefste ◽  
...  
Keyword(s):  
Land Use ◽  
Spatial Variation ◽  
Black Carbon ◽  
Ultrafine Particles ◽  
Regression Models ◽  
Short Term ◽  
Land Use Regression ◽  
Term Monitoring ◽  
Carbon Based

scholarly journals Short-Term Effects of Ambient Air Pollution On Daily Emergency Room Visits for Abdominal Pain: A Time-Series Study in Wuhan, China

2021 ◽  
Author(s):  
Yaqi Liu ◽  
Yi Jiang ◽  
Manyi Wu ◽  
Sunghar Muheyat ◽  
Dongai Yao ◽  
...  
Keyword(s):  
Air Pollution ◽  
Time Series ◽  
Abdominal Pain ◽  
Air Pollutants ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Emergency Room Visits ◽  
Short Term ◽  
Time Series Study ◽  
Series Study

Abstract Background There are few studies focused on the correlations between ambient air pollution and abdominal pain, especially in emergency departments in China. Method: Daily data (from January 1, 2016 to December 31, 2018), including air pollution concentration (SO2, NO2, PM2.5, PM10, CO, and O3) and meteorological variables, for daily emergency room visits (ERVs) were collected in Wuhan, China. We conducted a time-series study to investigate the potential correlation between six ambient air pollutants and ERVs for abdominal pain and their effects, in different genders, ages and seasons. Results A total of 16,306 abdominal pain ERVs were identified during the study period. A 10-µg/m3 increase in concentration of SO2, NO2, PM2.5, PM10, CO, and O3 corresponded respectively to incremental increases in abdominal pain of 6.12% (95% confidence interval [CI]: -0.44-13.12), 1.65% (95%CI: -0.25-3.59), 1.12% (95%CI: -0.18-2.44), 0.38% (95%CI: -1.09-1.87), 9.87% (95%CI:3.14–17.05) and 1.11% (95%CI: 0.03–2.21). We observed significant correlations between CO and O3 and daily abdominal pain ERVs increase, and positive but insignificant correlations between the other pollutants and ERVs. The effects were stronger mainly for females (especially SO2 and O3) and younger people (especially CO and O3). The correlations of PM2.5 and PM10 were stronger in cool seasons, while the correlation of CO was stronger in warm seasons. Conclusion Our time-series study suggested that short-term exposure to air pollution (especially CO and O3) was positively correlated with ERVs for abdominal pain in Wuhan, China, and that their effects varied by season, gender and age. These data can add evidence on how air pollutants affect the human body, and may prompt hospitals to take specific precautions on polluted days and maintain order in emergency departments made busier due to the pollution.

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