低风险疾病情境下农村居民健康信息规避行为研究

[目的/意义]本研究旨在揭示低风险疾病情境下农村居民健康信息规避的程度、策略、成因及其关联。[方法/过程]研究采用理论抽样方法和半结构化访谈法收集了江苏省45位农村居民的相关数据。研究采用开放式编码和主轴编码方法对访谈数据进行分析,同时采用社会网络分析软件对规避策略和成因之间的关系进行可视化展示。[结果/结论]（1）农村居民在低风险疾病情境下存在全面型和选择型两种不同程度的健康信息规避。其中,全面型健康信息规避主要发生在信息需求阶段,具体的规避策略为完全不治疗;而选择型信息规避发生在信息获取阶段,具体的规避策略为自己治疗或者拖延治疗。（2）该情境下农村居民健康信息规避的成因主要包括感知风险、对信息源的信任、健康信息素养水平、文化水平、情绪、经济水平、小世界、时间和医疗资源的可及性。（3）农民健康信息规避的成因与规避策略存在特定的关联。文化水平和医疗资源的可及性只对完全不治疗规避策略有影响;情绪因素只对拖延治疗规避策略有影响;健康信息素养水平只对自己治疗规避策略有影响。该研究可为改善农村居民的健康状况提供指导建议。     

蜂花粉营养液的营养成分分析

蜂花粉营养液以油菜花粉和蜂蜜为原料,经过先进的生产工艺制备而成.本文主要对其营养成分进行了分析,该营养液的营养成分搭配合理,含有17种氨基酸,其中包括8种必需氨基酸,氨基酸总量为575.2 mg/100mL;钙31.90 mg/100mL、钾77.46 mg/100mL、钠6.16 mg/100mL、镁19.12 mg/100mL、锌0.14 mg/100mL、铁0.14 mg/100mL、锰0.13 mg/100mL、铜0.053 mg/100mL;尼克酸0.24 mg/100mL、维生素B2 0.01mg/100mL、维生素B6 0.74 mg/100mL、维生素C 0.75 mg/100mL.     

生态养老背景下木结构建筑发展探析

木结构建筑具有自然舒适、绿色环保、节能保温以及防震减灾等特点,在生态养老领域具有很好的发展前景。介绍了木结构建筑概况,分析了老年人的生态养老需求,从适老化、绿色智能和文旅康养等方面,对木结构老年建筑发展进行展望与讨论,提出了完善相关标准规范和政策建议,为促进我国木结构老年建筑发展提供参考。     

健康家兔肠道中乳酸菌的分离鉴定

本试验选用MRS、MRS+10%家兔硬粪浸出液和MRS+10%泡菜汁3种选择培养基,对健康家兔肠道的乳酸菌群分别进行需氧和厌氧培养,根据可培养细菌菌落特征、染色特性、显微镜形态观测,共分离出7株乳酸菌株,其中需氧菌2株,厌氧菌5株。结合生化试验初步鉴定,需氧菌株分别为乳酸乳球菌和短乳杆菌,厌氧菌株分别为嗜酸乳杆菌,嗜粪乳杆菌,肠乳杆菌,乳酸乳杆菌和弯曲乳杆菌。本实验为弄清健康家兔肠道的有益菌群,以便下一步制作更易于在畜禽的肠道中定植存活的复合动物微生态制剂做准备。     

中兽医药技术是猪只康养最佳供给体系

在我国养猪业面临产品安全和环境污染两大瓶颈的情势下,如何使所生产的猪肉食用卫生,所排粪污环境安全,纯天然、无污染、广效低毒、绿色环保的中兽医药学为破解这两大瓶颈提供了技术支撑。充分发挥我国传统的中兽医药技术的特色和优势,构建以中兽医药为主体的猪只康养技术供给体系,旨在集生产管理"适其天性"、所喂药料"无污染"、治疗药物"纯天然"、预防措施治"未病"、治疗方法"和谐调节"和四季保健"药饲同源"于一体的技术供给体系,从源头上破解这两大难题,从而实现猪只康养,环境安全,猪肉安康,凸显出中兽医药是猪只康养的最佳供给体系。     

不同剂量伊曲康唑制剂对犬血常规及肝肾功能的影响

旨在评价不同剂量伊曲康唑-环糊精制剂通过皮下注射途径对健康比格犬肝肾功能及血常规的影响。选用体重±10 kg的健康纯种比格犬32只,按试验要求随机分为4组,每组8只,建立稳定的生活制度。分别按照0.25 mg/kg、0.75 mg/kg和1.25 mg/kg剂量,皮下注射伊曲康唑制剂,3日1次,连续7次,对照组注射生理盐水。于试验过程中第0、5、10、15、19天采集相关样品,对犬临床表现、血常规指标、血液生化指标、尿常规指标及肝肾功能进行全面的评价。结果表明,给药组与对照组相比,除白细胞相关指标外,其余指标都在正常范围内。给药组在试验过程中均出现白细胞升高现象,但在试验结束后5 d内均恢复正常。因此,伊曲康唑-环糊精制剂作为犬皮下注射剂型,具有良好的安全性和耐受性,操作方便,动物依从性好,适合兽医临床应用。     

Optimum Planting System for Energy Saving and Healthy Demanded

It is proved that planting is effective to improve environment both indoor and outdoor resulted from the functions of plants to clean air and save energy. So the contradiction between saving energy and comfort,healthy demanded by people can be solved by planting. The planting have being emphasized and expanded during recent years,but in the planting plan,just the function of beautifying the environment is concerned and the function of ecological and saving energy are neglected. The analysis on the ooptimum system of planting is to make the planting system as an organic composition in the effectiveness structure and space layout of the city. Based on the study on equivalent relation of different effects on environment, the optimum system of planting structure will be determined in order to achieve the integrated effects of planting on environment.     

酸性乳饮料稳定性影响因素分析

分析了影响酸性乳饮料稳定性的因素,并提出了相应的控制措施。     

Prediction of pine mistletoe infection using remote sensing imaging: A comparison of the artificial neural network model and logistic regression model

In this study, the prediction of pine mistletoe distribution in Scots pine ecosystems was explored using remote sensing variables to compare the multilayer perceptron (MLP) artificial neural network (ANN) and logistic regression (LR) model performances. For this purpose, 109 sample plots were distinguished in pure Scots pine forests (natural) in the Eastern Black Sea Region of Turkey. Distinguishing mistletoe-infected stands (69) and uninfected stands (40) was performed with field observations. The variables acquired from Landsat 8 (Level 1) images were used as independent variables for independent-sample t-test, MLP ANN and LR models. Remote sensing variables indicated that mistletoe-infected stands were in drier areas with a lower vegetation-leaf area index. Based on the performance results of both models, the sensitivity (SEN), specificity (SPE), positive predictive value (PPV), negative predictive value (NPV) and accuracy of the MLP ANN model were superior to those of the LR model. The prediction percentages (SEN, SPE, PPV and NPV) of mistletoe-infected stands were better than the prediction percentages of uninfected stands. The prediction accuracies of LR and MLP ANN models were 74.3% and 89.6%, respectively. However, all remote sensing variables were included in the prediction equation of the MLP ANN model, while the thermal infrared 1 (TIRS1) variable was included in the LR model. In the MLP ANN model, the TIRS1 variable also had the highest normalized importance (100%). The area under the curve (AUC) value for identifying the mistletoe-infected stands of Scots pine forests used by the MLP ANN model (0.892 ± 0.034) was higher than in the LR model (0.838 ± 0.039), explaining the more accurate predictions obtained from the MLP ANN model. The MLP ANN model showed much better performance than the LR model. The results of this study are expected to make important contributions to the identification of potential mistletoe-infected areas.