一次野外重大活动饮食卫生保障的经验与借鉴

总结一次野外重大活动饮食卫生保障的针对性做法和经验，为以后遂行多样化任务提供参考。从食谱审查、从业人员卫生管理及培训、采购保管、加工制作、餐饮具消毒以及留样备检等环节严格把关，强化常态食品卫生监督；科学分析餐饮环节容易导致疫情传播的风险点，从人、物、环境和预案4个方面开展督导；针对野外食品加工及人员大规模长时间野外就餐，指导餐饮单元选址开设、做好环境卫生管理、保障加工用水及食材安全、保障运输前送环节的食品安全及人员就餐过程卫生、指导智能化餐厨设备使用。提高餐饮单位负责人及从业人员的食品安全意识；提高保障人员的卫生法律素质和专业技术能力，关注新的风险点。加强保障人员自身管理及从业人员的卫生管理，树立良好形象。     

重大活动中食品相关产品安全关键控制点分析

近年来，中国葡萄酒消费量逐年上升，葡萄酒进口额大幅增长。通过比较分析主要葡萄酒进口来源国在我国的发展现状及趋势，发现法国和澳大利亚两国占据中国进口葡萄酒市场的前两位，且澳洲有赶超之势；智利、西班牙、格鲁吉亚三国对华葡萄酒出口潜力较大，市场份额将进一步提升。与中国缔结双边自贸协定等措施促进了相关国家对华葡萄酒出口，品牌及价格是影响进口葡萄酒消费的重要因素。中国进口葡萄酒市场仍存在认知度不高、价格偏高、假冒伪劣产品等问题，需要进一步降低进口葡萄酒的成本，加强市场监管。     

小型煤矿低浓度瓦斯发电技术及应用效果研究

针对云南富源县辖区内大量小型煤矿抽采的低浓度瓦斯未开展有效利用的问题，以区内某小型煤矿为背景，采用现场调研、分析归纳、理论计算相结合的方法对其低浓度瓦斯发电项目展开分析研究。研究表明，某小型煤矿低浓度瓦斯发电项目成功的关键是“瓦斯治理先行”理念主导下的气源保障综合技术体系。在气源得以保障的基础上，该小型煤矿低浓度瓦斯发电项目已经持续高效运行4年，每年创造经济收益约403.2万元，减排CO2约4.47万t；同时促进了煤矿瓦斯治理工作有效落实，提高了煤矿安全生产水平，保障了煤矿产量的达标。     

Applying Feature-Weighted Gradient Decent K-Nearest Neighbor to Select Promising Projects for Scientific Funding

Due to its outstanding ability in processing large quantity and high-dimensional data, machine learning models have been used in many cases, such as pattern recognition, classification, spam filtering, data mining and forecasting. As an outstanding machine learning algorithm, K-Nearest Neighbor (KNN) has been widely used in different situations, yet in selecting qualified applicants for winning a funding is almost new. The major problem lies in how to accurately determine the importance of attributes. In this paper, we propose a Feature-weighted Gradient Decent K-Nearest Neighbor (FGDKNN) method to classify funding applicants in to two types: approved ones or not approved ones. The FGDKNN is based on a gradient decent learning algorithm to update weight. It updatesthe weight of labels by minimizing error ratio iteratively, so that the importance of attributes can be described better. We investigate the performance of FGDKNN with Beijing Innofund. The results show that FGDKNN performs about 23%, 20%, 18%, 15% better than KNN, SVM, DT and ANN, respectively. Moreover, the FGDKNN has fast convergence time under different training scales, and has good performance under different settings.     

FogMed: A Fog-Based Framework for Disease Prognosis Based Medical Sensor Data Streams

Recently, an increasing number of works start investigating the combination of fog computing and electronic health (ehealth) applications. However, there are still numerous unresolved issues worth to be explored. For instance, there is a lack of investigation on the disease prediction in fog environment and only limited studies show, how the Quality of Service (QoS) levels of fog services and the data stream mining techniques influence each other to improve the disease prediction performance (e.g., accuracy and time efficiency). To address these issues, we propose a fog-based framework for disease prediction based on Medical sensor data streams, named FogMed. This framework aims to improve the disease prediction accuracy by achieving two objectives: QoS guarantee of fog services and anomaly prediction of Medical data streams. We build a virtual FogMed environment and conduct comprehensive experiments on the public ECG dataset to validate the performance of FogMed. The experiment results show that it performs better than the cloud computing model for processing tasks with different complexities in terms of time efficiency.     

How does a bank's involvement interplay with a firm's capacity investment? An analysis and comparison of different consortium structures

As nonrecourse project finance (rather than financing on a sovereign basis) is becoming more prevalent worldwide, financing institutions have to collaborate more closely with firms to optimize capacity‐investment and financing decisions. Under this background, this paper presents a stylized Stackelberg games model, taking into account the firm's capacity investment as well as the bank's interest rate and funding ratio decisions. Consortium structures between bank and firm are formalized into five modes based on industry practice, namely, the integrated consortium, pure shareholder funding, bank as leader, full coordination, and bank as follower. The optimality and equilibrium of each of the five modes are analytically derived, and their existence and uniqueness are demonstrated. Valuable economic insights are obtained through both modeling analysis and numerical experiments, with the main findings including the following: (i) a lack of bank financing leads to insufficient capacity investment and poor consortium performance; (ii) interest rate and funding ratio play important but different roles in the bank's risk management; (iii) the bank's proactivity in leading and coordinating the consortium is critical for the two parties’ overall performance; and (iv) if the bank is the follower, the firm's capacity decision is irrelevant to the bank's loan contract, and the consortium cannot be coordinated to the first‐best level of performance.     

A new type of phase change heat storage tank in solar energy combination system

介绍了一种新型笼屉式相变蓄热水箱，通过实验测试对比分析相变蓄热水箱与普通蓄热水箱对太阳能组合系统的太阳能保证率及系统能效比的影响。实验表明：同等水箱容积，使用相变蓄热水箱时太阳能集热系统的小时集热量为普通蓄热水箱的3.7倍，相变蓄热水箱有利于提高太阳能保证率及系统能效比。在太阳能辐照强度相似的情况下，相变蓄热水箱会使太阳能保证率平均提高72%，使系统能效比平均提高26%。同时相变蓄热水箱可减少夜间水箱上部的热损失，使水箱上部水温降减少50%。     

我国住宅产业发展现状与前景

分析了我国住宅产业发展过程中现时存在的问题以及面临的机遇与挑战,概括了推进产业现代化发展的思路和实施途径。     

长江三角洲天然气战略保障体系的构建

为提高天然气的供应安全性,打破行政约束,实现区域联动,构建由多气源互补、主干管网连通、必要的战略储备、有效的需求侧管理以及科学的调度系统等多方面组成的天然气战略保障体系十分迫切。