重组人EC-SOD包涵体的稀释复性及重折叠后蛋白的纯化

目的确定重组人ECSOD包涵体体外稀释复性和复性后蛋白纯化的适宜方法。方法通过对pH、温度、包涵体蛋白浓度、尿素和精氨酸浓度及氧化还原对比率的定性定量分析,研究重组人ECSOD包涵体体外稀释复性的基本条件。采用金属离子亲和柱(IMAC)和肝素亲和柱(Heparinsepharose)对复性蛋白进行纯化,比较纯化效率的差异。结果最佳复性条件为pH8.5,尿素浓度为1.5molL,精氨酸浓度大于0.3molL,GSH∶GSSG=4∶1;复性温度及包涵体蛋白终浓度越高,复性效率越低。IMAC和Heparinsepharose亲和柱均可用来纯化复性蛋白溶液,但Heparinsepharose纯化效率较高。结论确定了重组人ECSOD包涵体体外稀释复性的最佳条件及复性后蛋白纯化的方法。     

重组人白细胞介素-10在大肠杆菌中的表达及生物学活性分析

目的在大肠杆菌中表达重组人白细胞介素-10(Interleukin-10,IL-10),并检测其生物学活性。方法将IL-10基因重组到质粒pET11c中,转化BL21(DE),提取质粒,经酶切鉴定和测序分析;在25℃用低浓度的IPTG诱导表达,对包涵体IL-10稀释复性;经ELISA检测其含量,MC/9细胞增殖法检测其生物学活性。结果工程菌IL-10/pET11c/BL21诱导表达的目的蛋白以可溶性和包涵体两种形式存在,Westernblot鉴定证实为IL-10蛋白,两种形式的IL-10均具有一定的生物学活性。结论已成功地在大肠杆菌中表达了IL-10,为进一步纯化和制备IL-10的基因工程药物打下了基础。     

仿人智能橡胶制品的精密硫化控制

分析了橡胶制品硫化成型的对象特性，选择了硫化成型过程控制策略，研究了控制算法及其工程应用。研究结果表明，选择仿人智能控制作为硫化成型过程的控制策略时，可实现速度快、精度高的控制，且具有极强的鲁棒性。     

Utility of stereoscopic displays for indirect-vision driving and robot teleoperation

The effectiveness of an active shutter-glasses stereoscopic display (SD) and a passive polarised SD was evaluated in a live robot-teleoperation task and a simulated indirect-vision driving task in various terrains. Overall, participants completed their tasks significantly faster with the SDs in three-dimensional (3D) mode than with the SDs in the baseline 2D mode. They also navigated more accurately with the SDs in 3D mode. When the effectiveness of the two types of SDs was examined separately, results showed that the active shutter-glasses SD resulted in faster responses and task completion times than the passive polarised SD, though most of the differences failed to reach statistical significance. Perceived workload when interacting with the two SD systems did not differ significantly between the active versus passive display types or between the 3D and 2D modes of operation; however, participants reported more severe discomfort after interacting with the passive polarised SD.     

A 3D analysis of the joint torques developed during driver's ingress–egress motion

Providing an easy ingress–egress (I/E) movement remains a challenge for car designers. I/E has been largely studied in kinematics, but not in dynamics. This study proposes: (1) to evaluate and describe the motor torques developed in the lower limbs and lumbar joints during I/E motions and (2) to analyse the influence of the car geometry and subject anthropometry. An experiment was performed to observe 15 subjects of three anthropometrical groups getting in and out of a car mock-up simulating three different vehicle configurations. Motor torques were extracted using an inverse dynamics analysis. Both ingress and egress motions were primarily characterised by large torques. Overall, the taller a subject and the lower the seat of the vehicle were, the larger the peak torques were. Moreover, peak torques were higher for egress than ingress. These results are discussed in regard to the current knowledge on I/E ergonomics.     

Recommending suitable learning scenarios according to learners’ preferences: An improved swarm based approach

The paper presents a new approach for recommending suitable learning paths for different learners groups. Selection of the learning path is considered as recommendations to choosing and combining the sequences of learning objects (LOs) according to learners’ preferences. Learning path can be selected by applying artificial intelligence techniques, e.g. a swarm intelligence model. If we modify and/or change some LOs in the learning path, we should rearrange the alignment of new and old LOs and reallocate pheromones to achieve effective learning recommendations. To solve this problem, a new method based on the ant colony optimisation algorithm and adaptation of the solution to the changing optimum is proposed. A simulation process with a dynamic change of learning paths when new LOs are inserted was chosen to verify the method proposed. The paper contributes with the following new developments: (1) an approach of dynamic learning paths selection based on swarm intelligence, and (2) a modified ant colony optimisation algorithm for learning paths selection. The elaborated approach effectively assist learners by helping them to reach most suitable LOs according to their preferences, and tutors – by helping them to monitor, refine, and improve e-learning modules and courses according to the learners’ behaviour.     

金沙江下段植被NDVI变化趋势及其归因

基于MODIS NDVI数据及标准气象站数据、退耕还林资料,辅以空间统计、叠置分析和趋势分析等方法,研究了金沙江下段植被NDVI时空变化特征及其影响因素,结果表明:从年内来看,金沙江下段植被NDVI变化呈单峰型,3月份为最低值0.55,而9月份为最高值0.75,年际上10年以来植被覆盖总体呈现出增长趋势,且这种增长存在显著的空间异质性;研究区植被覆盖较好,植被NDVI平均值为0.65,海拔3 850m以下植被覆盖随海拔上升而增加,超过3 850m后随海拔升高呈降低趋势;年内植被NDVI受降水量的影响较气温更为明显,对两者均有2个月的滞后期,而年际上植被NDVI则受气温变化的影响较降水量更为突出,且大规模的植被恢复工程对金沙江下段植被覆盖的增加有重要贡献。     

Fundamentals of systems ergonomics/human factors

Ergonomics/human factors is, above anything else, a systems discipline and profession, applying a systems philosophy and systems approaches. Many things are labelled as system in today's world, and this paper specifies just what attributes and notions define ergonomics/human factors in systems terms. These are obviously a systems focus, but also concern for context, acknowledgement of interactions and complexity, a holistic approach, recognition of emergence and embedding of the professional effort involved within organization system. These six notions are illustrated with examples from a large body of work on rail human factors.     

HMM-based state classification of a user with a walking support system using visual PCA features

The improvement of safety and dependability in systems that physically interact with humans requires investigation with respect to the possible states of the user’s motion and an attempt to recognize these states. In this study, we propose a method for real-time visual state classification of a user with a walking support system. The visual features are extracted using principal component analysis and classification is performed by hidden Markov models, both for real-time fall detection (one-class classification) and real-time state recognition (multi-class classification). The algorithms are used in experiments with a passive-type walker robot called “RT Walker” equipped with servo brakes and a depth sensor (Microsoft Kinect). The experiments are performed with 10 subjects, including an experienced physiotherapist who can imitate the walking pattern of the elderly and people with disabilities. The results of the state classification can be used to improve fall-prevention control algorithms for walking support systems. The proposed method can also be used for other vision-based classification applications, which require real-time abnormality detection or state recognition.     

Human tracking system based on adaptive multi-feature mean-shift for robot under the double-layer locating mechanism

Human tracking has been a challenging task for robot in the past decades. In this paper, to realize the human following in a cluttered environment, a human tracking system based on adaptive multi-feature mean-shift (AMF-MS) under the double-layer locating mechanism (DLLM) is proposed to solve the problem of distinguishing target, occlusion, and quick turning. The DLLM, considering the course location processing and fine location processing, is designed to estimate the person’s position using the fusion of heterogeneous data. As an ID tag attached on target can be detected by RF antennas, the course locating method can track the target easily and quickly. The Bayes rule is introduced to calculate the probability where the tag exists due to the instability of RF signals. In the fine locating step, the AMF-MS is proposed because it can reduce computational load and represent target by multi-feature histogram function. Meanwhile, we combine extended Kalman filter and AMF-MS to overcome MS’s inability of occlusion. To control the robot following the target person precisely, an intelligent gear shift strategy based on fuzzy control is implemented by analyzing the robot structure. Experiments demonstrate that the proposed approach is robust to handle complex tracking conditions, and show the system has an optimum performance.