高校安全文化建设现状及对策研究——以L大学为例

为了改善L大学安全状况,提高L大学安全文化建设水平,采用文献对比分析法研究高校安全文化定义及其理论实质,从狭义的角度提出高校安全文化是高校管理的一系列安全理念,具体化为32条高校安全文化核心元素。以L大学为研究样本,定性分析其安全文化建设内容;编制高校安全文化定量测量量表,对其安全文化建设水平进行定量测量。评价结果表明L大学安全文化建设存在缺欠,提出了实用性对策措施和建议。     

事故人因分析的六层次模型构建和实例应用

本文试图用六个层次来划分引发事故的人因因素,从而能够更为准确地定位不同层次组织中可能存在的不安全行为,最终为预防事故服务。分析表明:预防安全生产事故,不仅仅需要解决较低层次的原因,还需要深入挖掘较高层级的原因。根据事故发生的各层级原因,指定合理的事故预防措施,能够有效的避免安全事故的发生。     

中国分省的碳排放责任分担机制探讨

中国省际间、地区间经济联系密不可分,大量的CO_2随着国内外频繁的贸易活动在省际间转移。本文针对以生产直接排放为基准界定区域排放责任的弊端,将基于消费的排放纳入排放责任体系,探讨了中国省级层面的碳排放责任分担机制。根据各地区经济发展水平、资源禀赋等特征,建立了中国省级层面动态分区域的碳排放责任分担模型,并计算了2007年各省份的碳排放责任分担量,为区域碳排放责任的分担提供了新的视角和依据,对其他环境污染责任的分担具有借鉴意义。     

Spatial evolution and specialization division of crop planting structure in counties of Tibet,China北大核心CSCD

从农业区域系统的角度分析农作物的空间集聚和专业化,可为农业产业结构调整及优化提供决策依据.以西藏粮食作物、油料作物、蔬菜和饲草4类作物为研究对象,基于1995-2020年西藏农业统计年鉴农作物播种面积数据分析西藏农作物种植面积时序变化,基于1995-2018年统计年鉴农作物播种面积数据和74个县域空间单元,综合运用重心模型、基尼系数、区位熵及空间自相关模型,通过ArcGIS软件分析西藏作物种植空间变化及专业化格局.结果显示:(1)西藏粮食作物种植面积占比历年均占绝对优势,但呈逐年下降趋势,油料作物种植面积整体呈波动性小幅上升,蔬菜和青饲料种植面积逐年明显增长.粮食作物、经济作物(含油料作物和蔬菜)、饲料作物比例从1995年的86:12:2调整到2020年的68:17:14.(2)1995-2015年间西藏粮食和油料生产重心较为稳定,未出现较大范围的地理迁移,其他农作物重心迁移距离较大,从东南向西北迁移416.7 km.(3)西藏农作物均呈现一定程度的空间集聚和区域专业化生产格局,但在研究期内生产集聚及专业化水平呈下降趋势.(4)将西藏粮食、油料和其他农作物划分为绝对优势区、比较优势区、优势衰退区、潜力优势区、不具优势区、优势退出区、可种植区和无种植区8种类型.本研究表明西藏农作物种植结构调整明显,基于生产格局及演变趋势划定了专业化分区,可引导农作物生产布局优化,对有效保障西藏地区粮食安全具有重要意义.(图6表5参26)     

金工实习在安全系统工程教学中的应用

金工实习作为同期开设的实践课程,为学生辨识危险源和分析风险提供了平台,有利于"做中学"教学模式的开展。实践表明,在安全系统工程教学过程中应用金工实习做实践分析可取得较高的教学效果。     

Spatiotemporal patterns and other impacting factors on wheat production of Tibet,China北大核心CSCD

Wheat is the second-largest food crop in Tibet, China. Along with economic development, the pattern of wheat production in Tibet has changed dramatically, potentially affecting the balance of grain supply and demand, as well as food security. A clear understanding of the spatiotemporal patterns and other factors affecting wheat production can provide a necessary basis for the scientific management and efficient production of wheat. Based on the wheat yield from 1990 to 2020 in 74 county-level units of Tibet, this study analyzed the spatial and temporal change patterns of Tibetan wheat production and its impacting factors using the Gini coefficient, center of gravity move method, advantage index, exploratory spatial data analysis (ESDA), and geographically weighted regression model (GWR). Results showed that: (1) the total wheat production in Tibet rose from 1990 to 1999, fluctuated, and then decreased from 1999 to 2020. The production areas are mainly concentrated in the southern Tibetan Valley and counties in the Three Rivers region of eastern Tibet. (2) The spatial distribution and agglomeration pattern of wheat in Tibet is relatively stable, and the production center shows a slight fluctuation trend from west to east during the 1990-2020 time period. (3) Based on the comprehensive advantage index (CAI), Tibet’s wheat production in advantaged areas, slightly advantaged areas, slightly disadvantaged areas, and disadvantaged areas accounted for 13.5%, 8.1%, 9.5%, and 40.5% of the total production, respectively; indicating that the regional distribution of CAI exhibits spatial agglomeration rather than sporadic distribution. The patterns are HH (high-high), LH (low-high), and random; 29 hot spots are mainly distributed in Lhasa, Shannan, and Nyingchi, while the cold spots are mainly distributed in Xigazê and Ngari; and (4) the impacting factors on Tibet’s wheat production mainly include effective irrigation areas and agricultural mechanization level as positive factors, and regional gross agricultural product as the main negative factor. In addition, rainfall, other grain output, livestock inventory at the end of the year, and the number of non-primary industries also have an impact on wheat production. Wheat planting area in Tibet has been declining in recent years, thus exhibiting a significant pattern of spatial agglomeration. The three dominant factors affecting the emerging spatiotemporal pattern of wheat production in Tibet are the irrigation condition, mechanization, and local economic development levels. Based on the above conclusions, the study suggests building a high-yield wheat area consistent with local conditions by strictly protecting arable land, improving irrigation conditions, and increasing machinery investment. Depending on the counties of high-yield areas, Tibetan farmers and herders should cultivate the bases of wheat production and build a wheat base for local wheat consumption. © 2022 Science Press. All rights reserved.