汉江上游干支流沉积物细菌群落多样性和影响因素

为了解汉江上游干支流沉积物细菌多样性以及确定性过程和随机性过程在沉积物细菌群落构建过程中的相对重要性,基于Illumina高通量测序技术,分析了环境因子对细菌群落组成的影响,采用非度量多维尺度(NMDS)排序探究了季节之间沉积物细菌群落的差异,并结合中性群落模型和标准化随机率量化了确定性过程和随机过程对群落构建的影响。结果表明:汉江上游及其支流细菌群落主要由变形菌门(Proteobacteria)、拟杆菌门(Bacteroidetes)、蓝藻门(Cyanophyta)、浮霉菌门(Planctomycetes)和酸杆菌门(Acidobacteria)等组成；细菌群落在不同季节有显著差异；地理距离和环境因子对细菌群落结构影响较小,确定性过程并未在细菌群落组成中起到主导作用；随机过程很大程度上影响了群落在秋季和春季的组成,是沉积物细菌群落构建的主导因素。     

国际橄榄理事会的定位和使命及相关标准（网络首发、推荐阅读）

The International Olive Council(IOC) is an international intergovernmental organization dedicated to olive oil and table olives, aiming at modernizing olive production, coordinating olive policies, improving the regulation of international trade, defending the quality of the olive sector and promoting olive oil and table olives to increase their consumption. The IOC grants recognition of laboratories and tasting panels in annual trials when they meet the conditions given in the decisions adopting the IOC certificate for laboratories for the physico–chemical testing of olive oil and laboratories for the sensory analysis of virgin olive oils. The IOC establishes analysis methods applying to olive oils and olive pomace oils for purity, quality and organoleptic assessment. The IOC elaborates guides of storage conditions for olive oils and olive pomace oils, of managing virgin olive oil tasting panels and of sensory testing laboratories. In future works, the IOC includes activities to identify analytical criteria for detecting fraud and guaranteeing the quality of olive oils and olive pomace oils.     

模具设计与制造专业群虚拟仿真实训基地建设路径研究

针对模具设计与制造专业群实训教学开展过程中存在的问题,开展专业群虚拟仿真实训基地的建设,通过精密模具智能制造生产线仿真实训工厂、模具数字化设计及智能成型单元综合应用平台、开放共享课程资源等3个方面内容的建设,引入行业新技术、新工艺、新标准,确保虚拟仿真教学资源与学生职业能力培养相一致。基地建设依托智能制造新技术,以培养高层次复合型技术技能人才为主线,满足实训教学为核心,多方共享为目标,助力区域经济发展,服务"鲁班工坊"国际化建设,最终实现虚拟仿真实训基地区域示范性效果。     

An IoT-Aware System for Managing Patients’ Waiting Time Using Bluetooth Low-Energy Technology

It is a common observation that whenever patients arrives at the front desk of a hospital, outpatient clinic, or other health-associated centers, they have to first queue up in a line and wait to fill in their registration form to get admitted. The long waiting time without any status updates is the most common complaint, concerning health officials. In this paper, UrNext, a location-aware mobile-based solution using Bluetooth low-energy (BLE) technology is presented to solve the problem. Recently, a technology-oriented method, the Internet of Things (IoT), has been gaining popularity in helping to solve some of the healthcare sector’s problems. The implementation of this solution could be illustrated through a simple example of when a patient arrives at a clinic for a consultation. Instead of having to wait in long lines, that patient will be greeted automatically, receive a push notification of an admittance along with an estimated waiting time for a consultation session. This will not only provide the patients with a sense of freedom but would also reduce the uncertainty levels that are generally observed, thus saving both time and money. This work aims to improve the clinics’ quality of services, organize queues and minimize waiting times, leading to patients’ comfort while reducing the burden on nurses and receptionists. The results demonstrate that the presented system is successful in its performance and helps achieves a pleasant and conducive clinic visitation process with higher productivity.     

Convolutional Neural Network Auto Encoder Channel Estimation Algorithm in MIMO-OFDM System

Higher transmission rate is one of the technological features of prominently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO–OFDM). One among an effective solution for channel estimation in wireless communication system, specifically in different environments is Deep Learning (DL) method. This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder (CNNAE) classifier for MIMO-OFDM systems. A CNNAE classifier is one among Deep Learning (DL) algorithm, in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another. Improved performances are achieved by using CNNAE based channel estimation, in which extension is done for channel selection as well as achieve enhanced performances numerically, when compared with conventional estimators in quite a lot of scenarios. Considering reduction in number of parameters involved and re-usability of weights, CNNAE based channel estimation is quite suitable and properly fits to the video signal. CNNAE classifier weights updation are done with minimized Signal to Noise Ratio (SNR), Bit Error Rate (BER) and Mean Square Error (MSE).     

超高效液相色谱⁃四极杆⁃飞行时间质谱对含PET食品接触材料中可迁移非挥发性物质的筛查研究

采用超高效液相色谱⁃四极杆⁃飞行时间高分辨质谱（UPLC⁃Q⁃TOF）对4类不同类型的含聚对苯二甲酸乙二醇酯（PET）材质的食品接触材料在4 %乙酸和50 %乙醇模拟物中的迁移出的非挥发性未知物进行筛查解析。结果表明，产品在4 %乙酸模拟物的迁移风险远小于50 %乙醇模拟物，主要迁移物质为聚合单体形成的寡聚物，抗氧剂、润滑剂、胶黏剂等加工助剂以及生产加工、迁移过程中形成的非有意添加物（NIAS）物质；纯PET材质的产品迁移物质较少，多层复合材料迁移物质较多。复合材质的产品中，PET材质可能在生产时添加了己二酸、癸二酸、新戊二醇等物质，进行了改性处理；此外，部分迁移物质会与模拟物中的乙醇发生反应，生成新的NIAS物质。     

Thermodynamic calculation and microstructure characterization of spinel formation in MgO–Al2O3–C refractories

In this paper, by simulating the gas phase conditions inside the MgO–Al₂O₃–C refractories during continuous casting process and combining with thermodynamic analysis, as well as SEM analysis, the gas-gas and gas-solid formation of MA spinel were clarified in carbon containing refractories. Thermodynamic calculations showed that gas partial pressure of CO, O₂ and Mg could meet the formation and stable existence conditions of MA spinel in MgO–Al₂O₃–C refractories under service environment, and nitrogen could not affect the formation of MA spinel at 1550 °C in the thermodynamic condition. The formation processes of MA spinel were analyzed experimentally under embedding carbon atmosphere. The carbon-coated alumina powders in MgO–Al₂O₃–C refractories prevented the direct contact between magnesia and alumina. Mg gas was formed by carbon thermal reaction, then reacted with alumina (gas-solid) and gas containing aluminum (gas-gas) to generate MA spinel. Through gas-gas or gas-solid reaction, the formation of MA spinel was effectively controlled. By means of SEM analysis, a two-layer structure with dense outer spinel layer and loose inner layer was formed in MgO–Al₂O₃–C refractories.     

“方变圆”变径筒状结构滑模施工技术

为解决塔式光热的核心构筑物吸热塔"方变圆"变径超高筒体结构施工难题,选用一套可变形的滑模平台系统,通过操作系统上可调千斤顶支座、门架横向液压千斤顶装置、多处可调节模板角度和收缩模板的丝杆等,使得滑模根据施工需求可在一定的范围内调节模板倾角、间距,并逐步完成收缩变形,其理论滑模允许偏角20°,最终高效完成异形结构施工。该滑模系统刚度大、承载及堆料能力强、空间大、机械化程度高,施工操作简单,安全性高,适应沙漠极端环境。全过程仅需使用一套滑模体系,就能完成方形段、方变圆的变形段及圆形段施工,大大提高了施工效率,为类似环境下相似结构的施工提供了一定的参考。