儿茶酚–(胺)表面化学介导的一氧化氮催化释放涂层研究

目的 在316L不锈钢(SS)表面构建原位一氧化氮(NO)催化释放涂层,使其能特异选择性地抗凝血、抑制平滑肌细胞(SMCs)增生,从而促进内皮细胞(ECs)生长。方法 在弱碱性水溶液中,选用多巴胺(DA)和己二胺(HD)为前驱体,利用多巴胺邻二苯酚结构自聚合沉膜的能力、多巴胺与己二胺的酚–(胺)表面化学,通过简单的一锅法在316L SS表面构建富氨基粘附涂层DA/HD。再通过碳二亚胺化学交联反应,共价接枝螯合Cu²⁺的1,4,7,10–四氮杂环十二烷–1,4,7,10–四羧酸(DOTA),最后获得均匀且稳定的NO催化释放涂层(命名为Cu-DOTA@DA/HD)。结果 DA/HD涂层表面的氨基密度高达22 nmol/cm²,实现了Cu-DOTA的有效固定,其NO催化释放速率可达5.2×10^–10 mol/(cm²·min)。Cu-DOTA@DA/HD涂层显著地抑制了血小板的粘附和激活,也能有效抑制血栓的形成,其表面血栓总质量由316L SS的(40.3±10.3) mg降低至(3.0±0.4) mg。...     

The EC Directive on Drinking Water (EEC 80/778)

The background to and technical deficiencies of the EC Drinking Water Directive are discussed. Although the inadequacies of the Directive are becoming increasingly recognized, there is no doubt that it has had a major impact on the UK water industry, much of which will be beneficial in the long term. However, it has provided a significant challenge to water suppliers on technical and environmental issues, as well as in new areas such as publicity and customer awareness. The water industry should be seen to be responding to the situation vigorously and positively to meet the spirit of the Directive, whilst seeking technical refinements which will make it a more practicable piece of legislation for the future.     

采用“欧洲规范3”对圆形空心截面钢拱的设计

讨论采用"欧洲规范3"对沿拱水平方向均布竖向荷载作用下的末端销接或固接的空心圆形横截面钢拱的设计方法,并提出了修正系数,以提高对此类拱结构设计的准确性。     

Feature extraction and soft computing methods for aerospace structure defect classification

This study concerns the effectiveness of several techniques and methods of signals processing and data interpretation for the diagnosis of aerospace structure defects. This is done by applying different known feature extraction methods, in addition to a new CBIR-based one; and some soft computing techniques including a recent HPC parallel implementation of the U-BRAIN learning algorithm on Non Destructive Testing data. The performance of the resulting detection systems are measured in terms of Accuracy, Sensitivity, Specificity, and Precision. Their effectiveness is evaluated by the Matthews correlation, the Area Under Curve (AUC), and the F-Measure. Several experiments are performed on a standard dataset of eddy current signal samples for aircraft structures. Our experimental results evidence that the key to a successful defect classifier is the feature extraction method – namely the novel CBIR-based one outperforms all the competitors – and they illustrate the greater effectiveness of the U-BRAIN algorithm and the MLP neural network among the soft computing methods in this kind of application.     

Monitoring the presence of residues of tetracyclines in baby food samples by HPLC-MS/MS

Tetracyclin is a group of antimicrobial permitted in animal food production, but their concentrations in food of animal origin should not exceed 100 μg kg⁻¹ (in meat and milk). Although the detection of these substances above these limits involves fines and jail for the producer, residues of tetracyclines are still being detected in food a potential risk to consumer health, especially babies.In the past, baby foods were carefully prepared at homes. However, modern lifestyles have led to the commercialization of ready-made baby food. Generally, these products are made with vegetable and meat from different animals, such as pork, chicken or beef. The presence of tetracyclines in meat at concentrations above 100 μg kg⁻¹ is forbidden in Europe by the Regulation 37/2010. Consequently this concentration is also applicable to the portion of meat present in baby food. Even if the presence of tetracyclines is controlled regularly in meat, they should also be monitored in baby food as babies are vulnerable to such as drugs.A rapid analytical method based on high-performance liquid chromatography coupled to a tandem mass spectrometer (HPLC-MS/MS) for quantification of four tetracyclines (tetracycline, chlortetracycline, doxycycline and oxytetracycline) in baby food is presented. The tetracyclines are extracted with EDTA-McIlvaine buffer, acidified at pH 4.0, followed by liquid–liquid extraction with ethyl acetate. The final extract is analysed within 19 min on a Sunfire HPLC column from Waters. Validation was performed according to the Commission Decision 2002/657/EC. The mean accuracy was 103 μg kg⁻¹, and the mean precision, was less than 23% for all the tetracyclines. The method was tested on 31 prepared baby food samples containing vegetable and beef. The presence of oxytetracycline was detected in one of the samples at a concentration of 5 μg kg⁻¹.     

Development and validation of an analytical method for the determination of arsenic,cadmium and lead content in powdered infant formula by means of quadrupole Inductively Coupled Plasma Mass Spectrometry

Cadmium (Cd), lead (Pb) and arsenic (As) can enter the food chain through the environment and/or as a consequence of the manufacturing process making foodstuffs the main human exposure route to these chemical elements. The risk associated with this exposure is of such a big concern for human health that the European Food Safety Agency recommends to reduce the exposure to Cd and Pb so as to protect especially vulnerable subgroups of population (e.g., infants). Therefore, the setting of new maximum levels (MLs) for chemical elements in infant formulae (e.g., for Cd) or the reconsideration of the existing ML for Pb is under discussion. On this basis, the availability of analytical methods, precise, accurate and sensitive enough to quantify low concentration values, is a key point especially for official control laboratories that have to state the sample compliance using a fully validated method with an associated uncertainty compliant with the requirements specified in the pertinent regulations. This work describes the development and validation of an analytical method to quantify As, Cd and Pb in powdered infant formulae based on animal protein at values of concentration close to the MLs that are likely to be set. The results obtained make the method suitable for a precise and accurate determination of these chemical elements at these low concentration values. In particular, the results for limit of quantification (LoQ) were respectively (μg kg⁻¹): As 6.2, Cd 1.2 and Pb 4.5. While for the recovery rates the following percentages were obtained: As 105%, Cd 98% and Pb 108%. The expanded uncertainties were found extremely satisfactory (Cd 13% and Pb 19%). The LoQ and the uncertainty for Pb meet the requirements set in Commission Regulation (EC) No. 333/2007 and following amendments being lower than the maximum values allowed. Even for Cd the expanded uncertainty resulted adequate in relation with the low concentration considered.     

Optimization of millimeter wave system in ITER Equatorial EC H&CD Launcher

A high power (20 MW) and CW millimeter wave (mm-wave) injection is planned for Electron Cyclotron Heating and Current Drive (EC H&CD) in ITER. An optimization of the mm-wave system for the ITER EC H&CD Equatorial Launcher (EL) is performed. The optimization of the system is aimed to obtain the maximum transmission efficiency on the condition that 1.8 MW injection per waveguide, ∼20 cm in beam radius at the resonance layer and narrow opening of the Blanket Shielding Module (BSM). The transmission efficiency of 99.1% from the end of the waveguide inside the launcher to the output of the BSM is achieved.The mm-wave propagation with high order modes is also calculated by using an experimentally obtained high power mm-wave beam pattern that includes 95%HE₁₁, 0.6%LP₁₁, 0.2%LP₀₂ and 4.2% other higher order modes. The analysis predicts the 1–2% additional loss will be induced by the high order modes.     

Automated configuration support for infrastructure migration to the cloud

With an increasing number of cloud computing offerings in the market, migrating an existing computational infrastructure to the cloud requires comparison of different offers in order to find the most suitable configuration. Cloud providers offer many configuration options, such as location, purchasing mode, redundancy, and extra storage. Often, the information about such options is not well organised. This leads to large and unstructured configuration spaces, and turns the comparison into a tedious, error-prone search problem for the customers. In this work we focus on supporting customer decision making for selecting the most suitable cloud configuration—in terms of infrastructural requirements and cost. We achieve this by means of variability modelling and analysis techniques. Firstly, we structure the configuration space of an IaaS using feature models, usually employed for the modelling of variability-intensive systems, and present the case study of the Amazon EC2. Secondly, we assist the configuration search process. Feature models enable the use of different analysis operations that, among others, automate the search of optimal configurations. Results of our analysis show how our approach, with a negligible analysis time, outperforms commercial approaches in terms of expressiveness and accuracy.