A thermomechanical investigation of highly cold-drawn polycarbonate

A new technique detecting molecular motions in drawn polymers was applied to highly cold-drawn polycarbonate of bisphenol A. It is shown that the sample exhibits thermal shrinkage in three steps with the temperature increase up to above the glass transition temperature. The molecular relaxation at the highest temperature is due to the glass transition. The other two molecular motions at the lower temperature are those of main chain in the glassy state and they correspond to the molecular motions as revealed in dielectric measurement by Sacher.¹ By using the general theory of the thermal analysis by Ozawa,² the apparent activation energies of these molecular motions were obtained: for the highest temperature 110 kcal/mole, and for the lowest temperature, 33.5 kcal/mole. The impact strength and the cold workability of this polymer are also discussed in relation to these molecular motions.     

Adenosine triphosphate (ATP) and other nucleotides stimulate the hydrolysis of phosphatidylethanolamine in intact fibroblasts

Addition of adenosine triphosphate (ATP) to [¹⁴C]ethanolamine-prelabeled NIH 3T3 fibroblasts resulted in rapid formation of [¹⁴C]ethanolamine from the prelabeled cellular phosphatidylethanolamine (PtdEtn) pool. After 2-min exposure, 10 μM ATP had near maximal effects on PtdEtn hydrolysis. Several other nucleotides, including UTP, ITP, and the stable ATP analog adenosine 5′-O-(3-thiotriphosphate) (ATPγS), also had stimulatory effects on PtdEtn hydrolysis with a potency comparable to that observed with ATP. The same nucleotides which acted on PtdEtn hydrolysis also had similar stimulatory effects on the hydrolysis of phosphatidylcholine (PtdCho) in [¹⁴C]choline-labeled cells. In isolated membranes, Mg²⁺ greatly enhanced the stimulatory effects of ATP and ATPγS, but not of other nucleotides, on the hydrolysis of PtdEtn and PtdCho. Results indicate that in isolated membranes, both ATP and ATPγS stimulate phospholipid hydrolysis by two different mechanisms, but in intact cells only one of these mechanisms appears to be responsive to externally added nucleotides.     

Feeding-stimulant activity of algal glycerolipids for marine herbivorous gastropods

Phagostimulant activity of glycerolipids such as digalactosyldiacylglycerol (DGDG), 6-sulfoquinovosyldiacylglycerol (SQDG), phosphatidylcholine (PC), phosphatidylethanolamine (PE), etc., have been examined using the Avicel plate method for three kinds of marine herbivorous gastropods, the abaloneHaliotis discus, the turban shellTurbo cornutus, and the topshellOmphalius pfeifferi. DGDG showed strong activity for all the test animals. SQDG was much less active than the other glycerolipids for abalone. The turban shell and the top shell responded more or less sensitively to all tested glycerolipids at doses of 10–20g/sample zone.Chemical Studies on Phagostimulants for Marine Gastropods. Part VIII. For Part VII, see Sakata et al. (1988a).     

A Non-Line-of-Sight mitigation localization algorithm for sensor networks using clustering analysis

Non-Line-of-Sight propagation of wireless signal has an impact on measured distances in range-based localization and will bias the final localization results. A new localization algorithm is proposed in this paper to mitigate Non-Line-of-Sight errors when there are more than enough anchor nodes deployed around the node to be located. This algorithm utilizes multi-round clustering analysis to filter the pre-located estimators which derive from all possible subsets of measured distances. In each round, the method density-based spatial clustering of applications with noise is adopted. Simulations show that the proposed algorithm can effectively improve localization accuracy not only when the measured distances with Non-Line-of-Sight error are minor but also under the condition that all of them suffer random Non-Line-of-Sight error.     

Telerobot-enabled HUB-CI model for collaborative lifecycle management of design and prototyping

The HUB-CI model is investigated in a telerobotic system in a client/server network to manage the lifecycle of engineering design and prototyping. The purpose of this platform is to support collaborative engineering design and proof of concept to enhance distributed team collaboration and resource utilization. The suggested platform is exemplified in two collaboration support tools and a physical prototyping platform. Structured Co-Insight Management is developed to support innovative idea exchanges and the consensus decision-making during the design process. Conflict/error detection management helps preventing conflicts and errors during the lifecycle of design and development. Physical collaboration over the network occurs when a team controls the telerobot operation during prototyping and testing in design cycles. A pilot system is implemented with a group project for the design of an electronic circuit (including both hardware and software designs). The functional assessment method is used to compare this platform to other collaborative design tools. The system presented offers unique qualitative advantages as an integrated collaboration support system.     

Influence of tetraalkylammonium cations on the electroreduction of nickel(II) in thiocyanate solutions

Influence of tetrabutyl-, tetrapentyl- and tetraisopentylammonium ions on the reduction of nickel(II) in thiocyanate solutions at the dropping mercury electrode has been investigated. These tetraalkylammonium ions, at their low concentrations, inhibit the reduction of nickel(II). However, at their high concentrations, the strong inhibiting effect disappers with the formation of a new wave corresponding to the reduction of a negatively charged nickel(II) thiocyanate complex, which is stabilized by the formation of ion pair with tetraalkylammonium cation. The variation of the reduction current with tetraalkalylammonium concentration was explained by taking into consideration both the change of the total charge of nickel(II) thocyanate complex involved in the reduction process and the simultaneous adsorption of tetraalkylammonium and thiocyanate ions on the mercury electrode.     

Guinea pig bone marrow cells treated with platelet-activating factor generate factor(s) which affects their DNA synthesis and microbicidal activity

We have previously reported that platelet-activating factor (PAF) induces proliferation and microbicidal activity of guinea pig bone marrow cells. In the present study, we have found that the conditioned medium of PAF- or nonmetabolizable PAF agonist-treated guinea pig bone marrow cells augmented DNA synthesis and induced microbicial activity of bone marrow cells. A PAF specific antagonist, CV-6209, inhibited generation of the active conditioned medium by PAF. Addition of the PAF antagonist only partially suppressed the augmentative effect of the active conditioned medium on DNA synthesis; this is consistent with the fact that, because of the rapid breakdown, no appreciable amount of PAF remained in the conditioned medium of PAF-treated cells. Although mouse bone marrow cells did not respond to PAF unlike guinea pig cells, their DNA synthesis was significantly enhanced by the conditioned medium of PAF-treated guinea pig bone marrow cells. Thus, some newly generated factor(s) distinct from the originally inoculated PAF seemed to modulate the bioactions of PAF on bone marrow cells. An appreciable amount of PAF was produced by calcium ionophore-treated guinea pig bone marrow cells. These findings indicate that PAF synthesized in guinea pig bone marrow cells induces generation in the cells of some factor(s) which affects proliferation or microbicidal activity. Presented at The Third International Conference on Platelet-Activating Factor and Structurally Related Ether Lipids, Tokyo, Japan, May 1989.     

Locally linear discriminant embedding: An efficient method for face recognition

In this paper an efficient feature extraction method named as locally linear discriminant embedding (LLDE) is proposed for face recognition. It is well known that a point can be linearly reconstructed by its neighbors and the reconstruction weights are under the sum-to-one constraint in the classical locally linear embedding (LLE). So the constrained weights obey an important symmetry: for any particular data point, they are invariant to rotations, rescalings and translations. The latter two are introduced to the proposed method to strengthen the classification ability of the original LLE. The data with different class labels are translated by the corresponding vectors and those belonging to the same class are translated by the same vector. In order to cluster the data with the same label closer, they are also rescaled to some extent. So after translation and rescaling, the discriminability of the data will be improved significantly. The proposed method is compared with some related feature extraction methods such as maximum margin criterion (MMC), as well as other supervised manifold learning-based approaches, for example ensemble unified LLE and linear discriminant analysis (En-ULLELDA), locally linear discriminant analysis (LLDA). Experimental results on Yale and CMU PIE face databases convince us that the proposed method provides a better representation of the class information and obtains much higher recognition accuracies.     

Web proxy cache replacement scheme based on back-propagation neural network

Web proxy caches are used to reduce the strain of contemporary web traffic on web servers and network bandwidth providers. In this research, a novel approach to web proxy cache replacement which utilizes neural networks for replacement decisions is developed and analyzed. Neural networks are trained to classify cacheable objects from real world data sets using information known to be important in web proxy caching, such as frequency and recency. Correct classification ratios between 0.85 and 0.88 are obtained both for data used for training and data not used for training. Our approach is compared with Least Recently Used (LRU), Least Frequently Used (LFU) and the optimal case which always rates an object with the number of future requests. Performance is evaluated in simulation for various neural network structures and cache conditions. The final neural networks achieve hit rates that are 86.60% of the optimal in the worst case and 100% of the optimal in the best case. Byte-hit rates are 93.36% of the optimal in the worst case and 99.92% of the optimal in the best case. We examine the input-to-output mappings of individual neural networks and analyze the resulting caching strategy with respect to specific cache conditions.