基于医疗联盟链的数据安全保护方法

随着互联网的飞速发展,医疗数据爆炸性增长,大量的医疗数据面临着安全共享问题.本文提出了一种基于医疗联盟链的数据安全保护方法,其中包括提出了一种安全认证与访问控制模型,并将查询逻辑分离存储技术引入该模型中,同时描述了基于医疗联盟链的认证凭据和访问权限数据的存储和访问.基于医疗联盟链的安全认证与访问控制模型包含了三个角色,第一角色是患者,第二角色是医护人员,第三角色是医疗联盟链.通过查询逻辑分离存储技术保护患者数据隐私,查询逻辑分离技术与医疗联盟链技术紧密结合,满足了不同医院之间医疗数据共享的需求,保障了患者的数据隐私和医护人员查阅数据的权限.     

摄动理论在腐蚀管线随机地震反应分析中的应用

埋地管线的腐蚀情况十分复杂,具有随机性的特点,从而导致其在地震激励下的反应必然具有随机性。本文在管线腐蚀离散状态模型和弹性地基梁原理的基础上,利用随机摄动理论推导给出了腐蚀管线在地震激励下位移和应力的解析表达式,并进行了均值和标准差的计算。实例分析中将该方法计算结果与Monte Carlo模拟方法计算结果进行了对比。结果表明,利用随机摄动方法可以快速、精确地求得腐蚀管线的随机地震反应。     

经济地理学视角下的旅游发展理论演进

经济地理学是一门非常活跃和发展演化很快的学科.近30年来,经济地理学的发展演化带动了旅游发展理论的演变.回顾旅游发展理论研究的进展,依次有依附理论、生命周期理论、社区研究方法、福特主义、弹性专业化和全球商品链理论,这些理论在旅游方面的应用和研究,从时间和数量上都明显滞后于生产实践活动,说明旅游研究还处于经济地理学科"边缘化"的地位.在今天经济全球化的背景下,旅游产业在迅猛发展之时,旅游发展理论的建设更应与经济地理学紧密结合,由"边缘"走向"核心".     

4种酞酸酯在龙须菜-篮子鱼食物链中的积累放大研究

在模拟受控条件下,利用气相色谱方法研究分析了4种酞酸酯类化合物在龙须菜(Gracilaria lemane-iformis)-篮子鱼(Siganus oramin)食物链中的积累、分布和放大状况。结果表明,4种酞酸酯在龙须菜组织内的积累表现为:邻苯二甲酸二异辛酯(DEHP)>邻苯二甲酸二丁酯(DBP)>邻苯二甲酸二乙酯(DEP)>邻苯二甲酸二甲酯(DMP)。侧链最长的DEHP在龙须菜藻体内的含量随暴露时间的延长呈增加的趋势,30 d体内积累量可达2.35 mg/kg(鲜质量);侧链最短的DMP在龙须菜藻体内的质量比随时间变化差异不显著,约为0.05 mg/kg;在30 d的暴露中,4种酞酸酯DMP,DEP,DBP和DEHP在篮子鱼体内总质量比分别为0.08,0.41,1.72,3.11 mg/kg。其中DBP和DEHP在鱼内脏组织中有较高的积累和分布,分别为1.14 mg/kg和1.83 mg/kg,其次为鱼残体组织,肌肉组织中含量最低。DEHP和DBP在龙须菜和篮子鱼体不同组织中均有一定程度的富集(生物富集系数FBC均大于1)。其中DEHP和DBP在内脏组织中的FBC值分别高达9.16和5.68,在龙须菜-篮子鱼这个简单食物链传递中DEHP和DBP在篮子鱼内脏组织中存在放大现象。     

矿产资源开发整合与区域矿业经济发展浅析——以潍坊市滨海新区卤水资源为例

对矿产资源开发进行整合是集中解决矿山布局不合理,实现规模化、集约化开发的重要手段,是调整矿业结构、促进矿业经济增长方式转变的有效途径。潍坊市滨海新区通过对卤水资源进行整合,初步实现了卤水资源的规模化开采和集约化经营,并在培育矿业龙头企业的基础上,注重矿业产业链的延伸和完整化,构建生态海洋化工产业集群,从而形成比较优势和核心竞争力,促进区域矿业经济发展。     

Sequence analysis and quantitative detection of Norwalk-like viruses in cultured oysters of China

We isolated 4 Norwalk-like viruses (NLVs) contaminated oysters from 33 Chinese oysters collected from local commer-cial sources of Shandong Province. After amplification of the RNA-dependent RNA polymerase (RdRp) region of NLVs genomes with RT-PCR, the open reading frame 1 (ORF1) of the RdRp was sequenced and subjected to multiple-sequence alignment. The re-suits showed that NLVs in the four isolates belong to genogroup Ⅱ. The sequence comparison showed that the similarity between four Chinese oyster isolates were higher than 99.0%, which indicated that NLVs prevalent in close areas have high homogeneity in genome sequences. In addition, the most conserved sequences between diverse NLVs were used to design primers and TaqMan probes, then the real-time quantitative PCR assay was performed. According to the standard curve of GII NLVs, the original amounts (copies) of NLVs in positive patient's fecal isolate, positive Japanese oyster isolate, and the Chinese oyster isolate were 8.9×108, 1.25×108 and 4.7×101 respectively. The detecting limit of NLVs was 1×101 copies. This study will be helpful for routine diagnosis of NLVs pathogens in foods and thus for avoiding food poisoning in the future.     

苹果手机零部件全球价值链的价值分配与中国角色演变

产品内分工已成为支配当代企业分工与产品生产的重要模式。研究智能手机生产网络价值分配格局,对辨析中国大陆企业在移动通讯产业价值链中所处地位与演进具有重要意义。论文利用2012—2017年苹果公司供应商数据,以其零部件价值含量与技术要求为测度标准,分析了苹果手机零部件全球价值链的分配特征以及中国大陆企业在其中的地位变化。发现：高价值环节的供应商主要以美国、日本、韩国为主,而中低价值环节则以中国台湾、日本和中国大陆供应商为主,且中国大陆与中国台湾在中间环节占据重要地位。处于价值链高端的供应商分支数量在中国大陆和美国缩减明显,日本、韩国较为稳定,中国台湾增加明显。在价值链的中低端环节,供应商分支趋向中国大陆集中。印度、巴西以及越南等地成为新的中低端价值环节转移承接地。近年来,中国大陆在苹果手机价值链的高端环节得到了提升,长三角、珠三角、京津冀、成渝、中原地区等地逐渐形成了苹果供应商分支的集聚区域,呈现出零部件生产的区域分工特征。长三角(上海-苏州为核心)与珠三角(深圳-东莞为核心),承接了价值链多个生产环节,是中国大陆嵌入苹果手机生产网络的主要阵地。成渝地区既承接了芯片类企业布局,也承接了价值链低端的组装代工和包装服务环节,呈现出在价值链两端双向承接的特征。环渤海、福建及湖南等地主要承接苹果手机价值链的中间环节,而中原地区主要以苹果手机组装与包装服务为主,承接价值链的低端环节。最后,论文从创新驱动、政府作用与外资等方面探讨了影响中国大陆地位提升的因素。     

传统村落景观基因信息链与自动识别模型构建——以陕西省为例

传统村落作为活的文化遗产,承载了大量历史记忆,是地域文化景观基因识别与模型构建研究的重要切入点。以陕西省71个国家级传统村落为例,基于景观基因理论建立陕西省传统村落景观基因识别体系,识别出陕西省传统村落景观基因特征;运用类型学原理和N级编码理论对景观基因进行编码,构建陕西省传统村落景观基因信息链并生成基因谱系;借鉴生物学中“胞-链-形”DNA碱基序列模型,提取出环境基因、建筑基因、农耕文化基因和宗族文化基因四个公共基因作为景观基因元（胞）,以村内道路系统作为基因链,构建传统村落景观基因DNA模型与自动识别模型,以此对传统村落的区位、类型、特征和文化基因进行自动识别。为传统村落景观基因信息有效传承与存储,以及乡村建设动态发展提供理论借鉴。     

Simulation of urban expansion via integrating artificial neural network with Markov chain – cellular automata

Accurate simulations and predictions of urban expansion are critical to manage urbanization and explicitly address the spatiotemporal trends and distributions of urban expansion. Cellular Automata integrated Markov Chain (CA-MC) is one of the most frequently used models for this purpose. However, the urban suitability index (USI) map produced from the conventional CA-MC is either affected by human bias or cannot accurately reflect the possible nonlinear relations between driving factors and urban expansion. To overcome these limitations, a machine learning model (Artificial Neural Network, ANN) was integrated with CA-MC instead of the commonly used Analytical Hierarchy Process (AHP) and Logistic Regression (LR) CA-MC models. The ANN was optimized to create the USI map and then integrated with CA-MC to spatially allocate urban expansion cells. The validated results of kappa and fuzzy kappa simulation indicate that ANN-CA-MC outperformed other variously coupled CA-MC modelling approaches. Based on the ANN-CA-MC model, the urban area in South Auckland is predicted to expand to 1340.55 ha in 2026 at the expense of non-urban areas, mostly grassland and open-bare land. Most of the future expansion will take place within the planned new urban growth zone.     

Examining the sensitivity of spatial scale in cellular automata Markov chain simulation of land use change

Understanding the spatial scale sensitivity of cellular automata is crucial for improving the accuracy of land use change simulation. We propose a framework based on a response surface method to comprehensively explore spatial scale sensitivity of the cellular automata Markov chain (CA-Markov) model, and present a hybrid evaluation model for expressing simulation accuracy that merges the strengths of the Kappa coefficient and of Contagion index. Three Landsat-Thematic Mapper remote sensing images of Wuhan in 1987, 1996, and 2005 were used to extract land use information. The results demonstrate that the spatial scale sensitivity of the CA-Markov model resulting from individual components and their combinations are both worthy of attention. The utility of our proposed hybrid evaluation model and response surface method to investigate the sensitivity has proven to be more accurate than the single Kappa coefficient method and more efficient than traditional methods. The findings also show that the CA-Markov model is more sensitive to neighborhood size than to cell size or neighborhood type considering individual component effects. Particularly, the bilateral and trilateral interactions between neighborhood and cell size result in a more remarkable scale effect than that of a single cell size.