Development of a chemical vapor sensor using piezoelectric quartz crystals with coated unusual lipids

Piezoelectric quartz crystal sensors were developed using lipids with various properties for highly sensitive detection of chemical vapors. Lipids with varying lengths of alkyl chains were coated onto 10 MHz AT-cut quartz crystal resonators and the response of these modified crystals to chemical vapors were measured. It was shown that hydrophilic compounds, such as ethanol and methanol, could be recognized efficiently by lipids having shorter alkyl chains, whereas lipids with longer alkyl chains showed affinity to more hydrophobic vapors, such as toluene, hexane and cyclohexane. Frequency changes caused by adsorption of alcohols could be enhanced when cholesterol was co-immobilized in the lipid layer. To confirm the assumption that the sensor-response might be affected by the properties of lipids derived from acyl chains, we have examined the effects of two types of newly synthesized unusual lipids on sensor response. When lipids having one triple bond each at different positions on their alkyl chains were coated onto quartz crystals separately, lower responses were observed compared to responses obtained for a sensor with immobilized, saturated phosphatidylcholine. Lipids containing -branched acyl chains, however, showed good affinity for organic vapors, and sensor responses improved 4–5-fold. Moreover, these sensors were shown to have sensitivity of the same order as the humans' sense of smell (10⁻⁵–10⁻⁶ w/w in liquid paraffin) when measured using standard odorants (isovaleric acid, skatole, etc.) for an olfactometry established in Japan.     

Artificial red cells with crosslinked hemoglobin membranes

Artificial cells containing concentrated hemoglobin (Hb) solution were prepared by interfacial polymerization of Hb with glutaraldehyde (GA) in liquid membrane capsules (LMC). A solution containing 30% of Hb was emulsified in mineral oil as red cell-size microdroplets, and this emulsion was dispersed in an aqueous phase containing glutaraldehyde to form LMC. The LMC were semipermeable templates that held the microdroplets of Hb in suspension while GA diffused through the oil to the microdroplet surfaces. The GA crosslinked Hb at the surface of each microdroplet to form an artificial red-cell membrane encapsulating Hb solution. A water-soluble surfactant was used to eject the cells from the LMC and suspend them in saline. Several surfactants were evaluated. Cell size was controlled by agitation speed during preparation of the original emulsion. Cells of 2.52 = ±1.69 μm were prepared. The encapsulated Hb retained capacity to bind and release O₂. The cells had aP ₅₀ of 8.9 torr (1200 Pa) and a capacity of 0.55 cc O₂/g of total Hb, indicating that the crosslinked portion of the Hb did not contribute to O₂ transport.     

自组织神经树用于判别氟化物非晶态形成条件

1人工神经网络──自组织神经树模型人工神经网络（ANN）是八十年代中期迅速兴起的一门非线性科学．它力图模拟人脑的一些基本特性，如自适应性、自组织性、容错性等，已在模式识别、数据处理及自动化控制等领域得到了初步应用，取得了相当好的效果［1，2］．1993年，Tao－Li等提出了自组织神经树网络．它是一个多层树状网络（见图1），每个输入节点与所有神经树的节点（神经元）通过权W相联系，实现对输入信号的非线性降维映射．映射中保持拓扑不变性，即把拓扑意义下相似的输入（即在高维空间中距离较近的输入向量）映射到相同子树的节…     

Toward a new generation of therapeutics

Scientific evidence in the prevention and treatment of various disorders is accumulating regarding probiotics. The health benefits supported by adequate clinical data include increased resistance to infectious disease, decreased duration of diarrhea, management of inflammatory bowel disease, reduction of serum cholesterol, prevention of allergy, modulation of cytokine gene expression, and suppression of carcinogen production. Recent ventures in metabolic engineering and heterologous protein expression have enhanced the enzymatic and immunomodulatory effects of probiotics and, with time, may allow more active intervention among critical care patients. In addition, a number of approaches are currently being explored, including the physical and chemical protection of cells, to increase probiotic viability and its health benefits. Traditional immobilization of probiotics in gel matrices, most notably calcium alginate and κ-carrageenan, has frequently been employed, with noted improvements in viability during freezing and storage. Conflicting reports exist, however, on the protection offered by immobilization from harsh physiologic environments. An alternative approach, microencapsulation in “artificial cells,” builds on immobilization technologies by combining enhanced mechanical stability of the capsule membrane with improved mass transport, increased cell loading, and greater control of parameters. This review summarizes the current clinical status of probiotics, examines the promises and challenges of current immobilization technologies, and presents the concept of artificial cells for effective delivery of therapeutic bacterial cells.     

Sequential injection system with higher dimensional electrochemical sensor signals Part 2. Potentiometric e-tongue for the determination of alkaline ions

An intelligent, automatic system based on an array of non-specific-response chemical sensors was developed. As a great amount of information is required for its correct modelling, we propose a system generating it itself. The sequential injection analysis (SIA) technique was chosen as it enables the processes of training, calibration, validation and operation to be automated simply. Detection was carried out using an array of potentiometric sensors based on PVC membranes of different selectivity. The diluted standard solutions needed for system learning and response modelling are automatically prepared from more concentrated standards. The electrodes used were characterised with respect to one and two analytes, by means of high-dimensionality calibrations, and the response surface of each was represented; this characterisation enabled an interference study of great practical utility. The combined response was modelled by means of artificial neural networks (ANNs), and thus it was possible to obtain an automated electronic tongue based on SIA. In order to identify the ANN which provided the best model of the electrode responses, some of the network's parameters were optimised and its usefulness in determining NH₄⁺, K⁺ and Na⁺ ions in synthetic samples was then tested. Finally, it was used to determine these ions in commercial fertilisers, the obtained results being compared with reference methods.     

A multineuron interaction model for neural networks

A multineuron interaction model (RS model) with an energy function given by the product of the squared distances in phase space between the state of the net and the stored patterns is studied in detail within a mean-field approach. Two limits are considered: when the patterns and antipatterns are stored (as in the Hopfield model), PAS case, and when only the patterns are taken into account, OPS case. TheT=0 solutions for the proper memories are exactly obtained for all finite values of, as a consequence of the energy function: whenever one of the overlaps is exactly one the corresponding equations decouple and no configuration average is required. Special interest is focused on the OPS situation, which presents a peculiar phase space topology. On the other hand, the PAS configuration recovers the Hopfield model in the appropriate limit, while keeping associative memory abilities far beyond the critical values of other models when the full Hamiltonian is considered.     

Modelling the soundscape quality of urban waterfronts by artificial neural networks

The renewal of the urban waterfronts has become a major focus of attention for politicians and decision makers in the city’s management programs. The recognition of the patterns that define the waterfronts’ identity is essential to select new strategies of intervention for the environmental recovery. In order to create adequate environments for everyday life within a sustainable development, new links between human senses, human perception and design need to be created. Within this wide approach, the landscape and the soundscape play a significant role and can become a key driving force in the implementation of the changes. New techniques have to be tested to identify the sonic and visual parameters capable to explain the specificity of a waterfront. With this purpose, an artificial neural network (ANN) was developed, and the relative importance of the input variables was evaluated. The collected database was also analysed by multiple linear regression (MLR) to compare the outcomes of both models. The urban waterfront of Naples (Italy) was chosen as case study. The results obtained show that the performance of the neural network is better than the one of the linear regression (rANN = 0.949, rMLR = 0.639). The interpretation of the relative importance method is also quite satisfactory in the ANN.