Therapeutic effect of a combination of montelukast and vitamins A and D drops in children with bronchial asthma, and its influence on quality of life

Purpose: To investigate the efficacy of a combination of montelukast and vitamins A and D drops in bronchial asthma children, and its effect on quality of life.Methods: Sixty bronchial asthma children from June 2018 to June 2020 were collected and randomized into study group and control group (30 cases in each group). Control group received montelukast sodium (chewable tablets), while the study group received vitamins A and D drops (capsules) plus. Clinical efficacy, lung function, serum inflammatory factors, and quality of life were evaluated and compared.Results: Compared with control group, total treatment effectiveness was higher and the symptom remission period was shorter in the study group (p < 0.05). Post-treatment, the parameters of FEV1 and FVC increased in both groups, but higher in the study group (p < 0.05). Serum levels of CRP and IL-4 in both groups decreased after treatment, while serum IL-10 levels were significantly up-regulated. Compared with control group, the levels of these indicators were improved in the study group (p < 0.05). Post-treatment Chinese Version of Pediatric Quality of Life Asthma Specific Scale (PedSQL) score was higher than before treatment, with higher values (for all indicators) in the study group (p < 0.05).Conclusion: The combination therapy of montelukast and vitamins A and D drops produces good clinical efficacy in children with bronchial asthma. It significantly shortens the time taken for relief of clinical symptoms, improves lung function, reduces inflammatory response, controls asthma, and improves the quality of life of the patients

Nonlinear Modeling and Analysis of Pressure Wave inside CEUP Fuel Pipeline

Operating conditions dependent large pressure variations are one of the working characteristics of combination electronic unit pump (CEUP) fuel injection system for diesel engines. We propose a precise and accurate nonlinear numerical model of pressure inside HP fuel pipeline of CEUP using wave equation (WE) including both viscous and frequency dependent frictions. We have proved that developed hyperbolic approximation gives more realistic description of pressure wave as compared to classical viscous damped wave equation. Frictional effects of various frequencies on pressure wave have been averaged out across valid frequencies to represent the combined effect of all frequencies on pressure wave. Dynamic variations of key fuel properties including density, acoustic wave speed, and bulk modulus with varying pressures have also been incorporated. Based on developed model we present analysis on effect of fuel pipeline length on pressure wave propagation and variation of key fuel properties with both conventional diesel and alternate fuel rapeseed methyl ester (RME) for CEUP pipeline

Household, community, sub-national and country-level predictors of primary cooking fuel switching in nine countries from the PURE study

Introduction. Switchingfrom polluting (e.g. wood, crop waste, coal)to clean (e.g. gas, electricity) cooking fuels can reduce household air pollution exposures and climate-forcing emissions.While studies have evaluated specific interventions and assessed fuel-switching in repeated cross-sectional surveys, the role of different multilevel factors in household fuel switching, outside of interventions and across diverse community settings, is not well understood. Methods.We examined longitudinal survey data from 24 172 households in 177 rural communities across nine countries within the Prospective Urban and Rural Epidemiology study.We assessed household-level primary cooking fuel switching during a median of 10 years offollow up (∼2005–2015).We used hierarchical logistic regression models to examine the relative importance of household, community, sub-national and national-level factors contributing to primary fuel switching. Results. One-half of study households(12 369)reported changing their primary cookingfuels between baseline andfollow up surveys. Of these, 61% (7582) switchedfrom polluting (wood, dung, agricultural waste, charcoal, coal, kerosene)to clean (gas, electricity)fuels, 26% (3109)switched between different polluting fuels, 10% (1164)switched from clean to polluting fuels and 3% (522)switched between different clean fuels

Gender differences in self-care maintenance and its associations among patients with chronic heart failure

Objectives: To identify the gender differences in self-care maintenance and its associations among chronic heart failure patients using the Information-Motivation-Behavioral Skills model. Methods: Two hundred and ten patients (54.0% female) with chronic heart failure participated in this cross-sectional study. Self-care, knowledge of heart failure, social support and illness perception were measured using the Self-Care of Heart Failure Index, the questionnaire of heart failure knowledge, the Perceived Social Support Scale, and the Revised Illness Perception Questionnaire, respectively. Results: Mean scores for self-care maintenance were 51.4 ± 14.8 in men and 55.6 ± 14.1 in women (t = −2.066, P < 0.05). Associated factors of self-care maintenance were social support and self-care confidence in men and the knowledge of heart failure, self-care management and self-care confidence in women. The relationship between social support and self-care maintenance was meditated by self-care confidence in men, whereas the relationship between knowledge of heart failure and self-care maintenance was meditated by self-care management and self-care confidence in women. Conclusions: Self-care maintenance were inadequate in both genders with chronic heart failure. Interventions for enhancing social support and self-care confidence in men patients, and strengthening knowledge of heart failure, self-care management and self-care confidence in women patients, may facilitate self-care maintenance. Keywords: Heart failure, Illness perception, Knowledge, Self-care, Social suppor

Remotely sensed rice yield prediction using multi-temporal NDVI data derived from NOAA's-AVHRR.

Grain-yield prediction using remotely sensed data have been intensively studied in wheat and maize, but such information is limited in rice, barley, oats and soybeans. The present study proposes a new framework for rice-yield prediction, which eliminates the influence of the technology development, fertilizer application, and management improvement and can be used for the development and implementation of provincial rice-yield predictions. The technique requires the collection of remotely sensed data over an adequate time frame and a corresponding record of the region's crop yields. Longer normalized-difference-vegetation-index (NDVI) time series are preferable to shorter ones for the purposes of rice-yield prediction because the well-contrasted seasons in a longer time series provide the opportunity to build regression models with a wide application range. A regression analysis of the yield versus the year indicated an annual gain in the rice yield of 50 to 128 kg ha(-1). Stepwise regression models for the remotely sensed rice-yield predictions have been developed for five typical rice-growing provinces in China. The prediction models for the remotely sensed rice yield indicated that the influences of the NDVIs on the rice yield were always positive. The association between the predicted and observed rice yields was highly significant without obvious outliers from 1982 to 2004. Independent validation found that the overall relative error is approximately 5.82%, and a majority of the relative errors were less than 5% in 2005 and 2006, depending on the study area. The proposed models can be used in an operational context to predict rice yields at the provincial level in China. The methodologies described in the present paper can be applied to any crop for which a sufficient time series of NDVI data and the corresponding historical yield information are available, as long as the historical yield increases significantly