Micro cam system driven by electrostatic comb-drive actuators based on SOI-MEMS technology

Microsystem Technologies - This paper reports a design and fabrication process of a micro cam system (MCS) with a flat-faced translating follower. The cam rim with cover diameter of 2.4 mm...     

Expression of polysialylated neural cell adhesion molecule by proliferating cells in the subependymal layer of the adult rat, in its rostral extension and in the olfactory bulb

The highly sialylated isoform of the neural cell adhesion molecule is thought to be expressed predominantly in the developing nervous system, where it is implicated in a variety of dynamic events linked to neural morphogenesis. It has become increasingly evident, however, that this "embryonic" neural cell adhesion molecule isoform continues to be expressed in certain adult neuronal systems, and in particular, in those that can undergo structural plasticity. In the present study, we performed light microscopic immunocytochemistry with an antibody specific for polysialylated neural cell adhesion molecule and confirmed our earlier observations [Bonfanti L. et al. (1992) Neuroscience 49, 419-436] showing polysialylated neural cell adhesion molecule-immunoreactive cells in the subependymal layer of the lateral ventricle of the adult rat, a region where cell proliferation continues into the postnatal period. In addition, we used an antibody raised against the proliferating cell nuclear antigen and found that proliferating cells continue to be visible in this area, even in the adult. Double immunolabeling showed that many of these newly generated cells displayed high polysialylated neural cell adhesion molecule immunoreactivity. Cells from a portion of the subependymal layer migrate to the olfactory bulb and contribute to the continual replacement of its granule neurons [Luskin M. B. (1993) Neuron 11, 173-189]. We found polysialylated neural cell adhesion molecule-immunoreactive cells all along the pathway purported to be followed by the newly generated cells to their final destination and in neurons corresponding to granular and periglomerular cells in the olfactory bulb. Our present observations thus support the contention that polysialylation is a feature of neurons capable of dynamic change and may contribute to the molecular mechanisms permitting cell proliferation and migration not only during development but also in the adult.     

The testing of bulls for the polledness gene]

Main regularities have been stated concerning the poll gene inheritance by the progeny of breeding bulls mated with cows of various (homozygous and heterozygous) genotypes by the "poll" or "hornedness" genes.     

The role of protein kinase in C ischemic/reperfused preconditioned isolated rat hearts

Protein kinase C (PKC) has been implicated in the preconditioning-induced cardiac protection in ischemic/reperfused myocardium. We studied the effect of PKC inhibition with calphostin C (25, 50, 100, 200, 400, and 800 nM), a potent and specific inhibitor of PKC, in isolated working nonpreconditioned and preconditioned ischemic/reperfused hearts. In the nonpreconditioned groups, all hearts underwent 30 min of normothermic global ischemia followed by 30 min of reperfusion. In the preconditioned groups, hearts were subjected to four cycles of ischemic preconditioning by using 5 min of ischemia followed by 10 min reperfusion, before the induction of 30 min ischemia and reperfusion. At low concentrations of calphostin C (25, 50, and 100 nM), the PKC inhibitor had no effect on the incidence or arrhythmias or postischemic cardiac function in the nonpreconditioned ischemic/reperfused groups. With 200 and 400 nM of calphostin C, a significant increase in postischemic function and a reduction in the incidence of arrhythmias were observed in the nonpreconditioned ischemic/reperfused groups. Increasing the concentration of calphostin C to 800 NM, the recovery of postischemic cardiac function was similar to that of the drug-free control group. In preconditioned hearts, lower concentrations (< 100 nM) of calphostin C did not change the response of the myocardium to ischemia and reperfusion in comparison to the preconditioned drug-free myocardium. Two hundred and 400 nM of the PKC inhibitor further reduced the incidence of ventricular fibrillation (VF) from the preconditioned drug-free value of 50% to 0 (p < 0.05) and 0 (p < 0.05), respectively, indicating that the combination of the two, preconditioning and calphostin C, affords significant additional protection. Increasing the concentration of calphostin C to 800 nM blocked the cardioprotective effect of preconditioning (100% incidence of VF). The recovery of cardiac function was similarly improved at calphostin C doses of 200 and 400 nM and was reduced at 800 nM (p < 0.05). With 200 and 400 nM of calphostin C, both cytosolic and particulate PKC activity were reduced by approximately 40 and 60%, respectively, in both preconditioned and preconditioned/ischemic/reperfused hearts. The highest concentration of calphostin C (800 nM) resulted in almost a complete inhibition of cytosolic (100%) and particulate (85%) PKC activity correlated with the abolition of preconditioning-induced cardiac protection. In conclusion, calphostin C protects the ischemic myocardium obtained from intact animals, provides significant additional protection to preconditioning at moderate doses, and blocks the protective effect of preconditioning at high concentrations. The dual effects of calphostin C appear to be strictly dose and "enzyme inhibition" related.     

Recognition and analysis of cell nuclear phases for high-content screening based on morphological features

Automated analysis of molecular images has increasingly become an important research in computational life science. In this paper some new and efficient algorithms for recognizing and analyzing cell phases of high-content screening are presented. The conceptual frameworks are based on the morphological features of cell nuclei. The useful preprocessing includes: smooth following and linearization; extraction of morphological structural points; shape recognition based morphological structure; issue of touching cells for cell separation and reconstruction. Furthermore, the novel detecting and analyzing strategies of feed-forward and feed-back of cell phases are proposed based on gray feature, cell shape, geometrical features and difference information of corresponding neighbor frames. Experiment results tested the efficiency of the new method.     

Optimal assembly plan generation: a simplifying approach

The main difficulty in the overall process of optimal assembly plan generation is the great number of different ways to assemble a product (typically thousands of solutions). This problem confines the application of most existing automated planning methods to products composed of only a limited number of components. The presented method of assembly plan generation belongs to the approach called “disassembly” and is founded on a new representation of the assembly process, with introduction of a new concept, the equivalence of binary trees. This representation allows to generate the minimal list of all non-redundant (really different) assembly plans. Plan generation is directed by assembly operation constraints and plan-level performance criteria. The method was tested for various assembly applications and compared to other generation approaches. Results show a great reduction in the combinatorial explosion of the number of plans. Therefore, this simplifying approach of assembly sequence modeling allows to handle more complex products with a large number of parts.     

Fuzzy posterior-probabilistic fusion

The paradigm of the permanence of updating ratios, which is a well-proven concept in experimental engineering approximation, has recently been utilized to construct a probabilistic fusion approach for combining knowledge from multiple sources. This ratio-based probabilistic fusion, however, assumes the equal contribution of attributes of diverse evidences. This paper introduces a new framework of a fuzzy probabilistic data fusion using the principles of the permanence of ratios paradigm, and the theories of fuzzy measures and fuzzy integrals. The fuzzy sub-fusion of the proposed approach allows an effective model for incorporating evidence importance and interaction.     

A spreadsheet approach to facilitate visualization of uncertainty in information

Information uncertainty is inherent in many problems and is often subtle and complicated to understand. Although visualization is a powerful means for exploring and understanding information, information uncertainty visualization is ad hoc and not widespread. This paper identifies two main barriers to the uptake of information uncertainty visualization: firstly, the difficulty of modeling and propagating the uncertainty information; and secondly, the difficulty of mapping uncertainty to visual elements. To overcome these barriers, we extend the spreadsheet paradigm to encapsulate uncertainty details within cells. This creates an inherent awareness of the uncertainty associated with each variable. The spreadsheet can hide the uncertainty details, enabling the user to think simply in terms of variables. Furthermore, the system can aid with automated propagation of uncertainty information, since it is intrinsically aware of the uncertainty. The system also enables mapping the encapsulated uncertainty to visual elements via the formula language and a visualization sheet. Support for such low-level visual mapping provides flexibility to explore new techniques for information uncertainty visualization.     

A spatially constrained fuzzy hyper-prototype clustering algorithm

We present in this paper a fuzzy clustering algorithm which can handle spatially constraint problems often encountered in pattern recognition. The proposed method is based on the notions of hyperplanes, the fuzzy c-means, and spatial constraints. By adding a spatial regularizer into the fuzzy hyperplane-based objective function, the proposed method can take into account additionally important information of inherently spatial data. Experimental results have demonstrated that the proposed algorithm achieves superior results to some other popular fuzzy clustering models, and has potential for cluster analysis in spatial domain.