Citation structure of an emerging research area on the verge of application

A case study of an emerging research area is presented dealing with the creation of organic thin film transistors, a subtopic within the general area called “plastic electronics.” The purpose of this case study is to determine the structural properties of the citation network that may be characteristic of the emergence, development, and application or demise of a research area. Research on organic thin film transistors is highly interdisciplinary, involving journals and research groups from physics, chemistry, materials science, and engineering. There is a clear path to industrial applications if certain technical problems can be overcome. Despite the applied nature and potential for patentable inventions, scholarly publications from both academia and industry have continued at a rapid pace through 2007. The question is whether the bibliometric indicators point to a decline in this area due to imminent commercialization or to insurmountable technical problems with these materials.     

Estimation and vicarious validation of urban vegetation abundance by spectral mixture analysis

Both moderate and high spatial resolution imagery can be used to quantify abundance and distribution of urban vegetation for urban landscape management and to provide inputs to physical process models. Estimation of vegetation fraction from Landsat ETM+ and Quickbird allows for operational monitoring and reconnaissance at moderate resolution with calibration and vicarious validation at higher resolution. Establishing a linear correspondence between ETM-derived vegetation fraction and Quickbird-derived vegetation fraction facilitates the validation task by extending the spatial scale from 30 × 30 m to a more manageable 2.8 × 2.8 m. A comparative analysis indicates that urban reflectance can be accurately represented with a three component linear mixture model for both Landsat ETM+ and Quickbird imagery in the New York metro area. The strong linearity of the Substrate Vegetation Dark surface (SVD) mixture model provides consistent estimates of illuminated vegetation fraction that can be used to constrain physical process models that require biophysical inputs related to vegetation abundance. When Quickbird-derived 2.8 m estimates of vegetation fraction are integrated to 30 m scales and coregistered to Landsat-derived 30 m estimates, median estimates agree with the integrated fractions to within 5% for fractions > 0.2. The resulting Quickbird-ETM+ scatter distribution cannot be explained with estimate error alone but is consistent with a 3% to 6% estimation error combined with a 17 m subpixel registration ambiguity. The 3D endmember fraction space obtained from ETM+ imagery forms a ternary distribution of reflectance properties corresponding to distinct biophysical surface types. The SVD model is a reflectance analog to Ridd's V–I–S land cover model but acknowledges the fact that permeable and impermeable surfaces cannot generally be distinguished on the basis of broadband reflectance alone. We therefore propose that vegetation fraction be used as a proxy for permeable surface distribution to avoid the common erroneous assumption that all nonvegetated surfaces along the gray axis are completely impermeable. Comparison of mean vegetation fractions to street tree counts in New York City shows a consistent relationship between minimum fraction and tree count. However, moderate and high resolution areal estimates of vegetation fraction provide complementary information because they image all illuminated vegetation, including that not counted by the in situ street tree inventory.     

Laser-activated shape memory polymer microactuator for thrombus removal following ischemic stroke: preliminary in vitro analysis

Due to the narrow (3-h) treatment window for effective use of the thrombolytic drug recombinant tissue-type plasminogen activator (rt-PA), there is a need to develop alternative treatments for ischemic stroke. We are developing an intravascular device for mechanical thrombus removal using shape memory polymer (SMP). We propose to deliver the SMP microactuator in its secondary straight rod form (length=4 cm, diameter=350 /spl mu/m) through a catheter distal to the vascular occlusion. The microactuator, which is mounted on the end of an optical fiber, is then transformed into its primary corkscrew shape by laser heating (diode laser, /spl lambda/=800 nm) above its soft-phase glass transition temperature (T/sub gs/=55/spl deg/C). Once deployed, the microactuator is retracted, and the captured thrombus is removed to restore blood flow. The SMP is doped with indocyanine green (ICG) dye to increase absorption of the laser light. Successful deployment of the microactuator depends on the optical properties of the ICG-doped SMP, as well as the optical coupling efficiency of the interface between the optical fiber and the SMP. Spectrophotometry, thermal imaging, and computer simulation aided the initial design effort and continue to be useful tools for optimization of the dye concentration and laser power. Thermomechanical testing was performed to characterize the elastic modulus of the SMP. We have demonstrated laser activation of the SMP microactuator in air at room temperature, suggesting this concept is a promising therapeutic alternative to rt-PA.     

Empirical Method for Determining SOA Gain Based on ASE Characterization

Semiconductor optical amplifiers (SOAs) are often used in fiber-optic systems in which device gain must be adjusted precisely without disturbing the surrounding system. We have developed an unobtrusive technique for measuring SOA gain based on the peak wavelength of the device's amplified spontaneous emission spectrum. This methodology also expedites gain measurements for systems in which an SOA dynamically switches on and off. We further confirm the reliability and robustness of this methodology     

Artificial neural networks for the automated detection of trichloroethylene by passive Fourier transform infrared spectrometry

Artificial neural networks are applied to the automated classification of trichloroethylene (TCE) signatures from passive Fourier transform infrared remote sensing interferogram data. Through the use of three data collection methods, a combination of laboratory and field data is acquired that allows the methodology to be evaluated under a variety of infrared background conditions and in the presence of potentially interfering compounds such as sulfur hexafluoride, methyl ethyl ketone, acetone, carbon tetrachloride, and ammonia. To maximize the computational efficiency of the network optimization, experimental design techniques are employed to develop a training protocol for the network that takes into account the relationships among five variables that are related either to the network architecture or to the training process. This protocol is implemented for the case of a back-propagation neural network (BNN) and is used to develop an optimized network for the detection of TCE. The classification performance of the network is assessed by comparing both TCE detection capabilities and false detection rates to similar classification results obtained with the technique of piecewise linear discriminant analysis (PLDA). When applied to prediction data withheld from the optimization of both the BNN and PLDA algorithms, the BNN method is observed to outperform PLDA overall, with TCE detection rates in excess of 99% and false detection rates less than 0.5%.     

Calibration transfer algorithm for automated qualitative analysis by passive Fourier transform infrared spectrometry

The automated qualitative analysis of passive Fourier transform infrared (FT-IR) remote sensing data is made difficult by the presence in the data of background and instrument-specific variation. For data collected with a single instrument, variation in the data arises from changes in the infrared background radiance, changes in the atmospheric composition within the field-of-view of the spectrometer, and changes in the instrument response function arising from temperature variation in the spectrometer. When more than one spectrometer is used, the variation in detector responses and phase signatures between instruments serves to complicate further the task of implementing an automated processing algorithm for detecting the signature of a target compound. In this work, a combination of signal processing and pattern recognition methodology is applied directly to the interferogram data collected by the FT-IR spectrometer to implement an automated compound detection procedure that is independent of background and instrument-specific variation. The key to this algorithm is the use of highly attenuating digital filters to isolate in the interferogram the frequencies associated with an analyte absorption or emission band while suppressing information at other frequencies. For the test compounds, acetone and sulfur hexafluoride, it is demonstrated that when this digital filtering procedure is coupled with either piecewise linear discriminant analysis or a back-propagation neural network, an automated detection algorithm can be developed with data from a primary instrument and then subsequently used to predict the presence of analyte signatures in data collected with a secondary spectrometer. Correct classification rates in excess of 92% are obtained for both compounds when the algorithm is applied to data collected with the secondary instrument.     

Evaluating the function of hippocampal subregions with high-resolution MRI in Alzheimer's disease and aging

Memory ability declines in older age groups. There is a growing list of physiological processes that target the hippocampal formation in an age-related fashion, and some might underlie the hippocampal component of memory decline. The hippocampal formation is comprised of separate subregions, and physiological processes differentially target these subregions. The ability to evaluate the functional integrity of individual subregions-performing subregional analysis-is a major clinical goal since it can aid in the diagnosis of memory decline, as well as in elucidating mechanisms of disease and testing potential interventions. Because of its superior spatial resolution, magnetic resonance imaging (MRI) is best suited to accomplish this goal. Despite limited success, most functional MRI (fMRI) protocols have difficulty in performing complete subregional analysis of the hippocampal formation. Here we address sources of difficulty by (1) generating T2* -weighted maps of the hippocampal formation with sub-millimeter resolution; and (2) by adapting an approach used by animal investigators to identify the hippocampal subregions using anatomical landmarks. The protocol is tested in patients with Alzheimer's disease and in healthy controls, in an effort to determine whether it can detect neuronal dysfunction. Results showed diminished signal in the hippocampal formation of patients with Alzheimer's disease (AD) compared to controls, and multivariate analysis showed that this difference was most prominent in the entorhinal cortex. The protocol can be used to perform subregional analysis of the hippocampal formation. Testing the protocol in other clinical populations is needed to demonstrate its efficacy in evaluating the neuronal integrity of all hippocampal subregions.     

Risk factors for high blood lead levels among the general population in Taiwan

BACKGROUND: Tacrolimus (FK506) may represent a major advance in the management of allograft rejection after solid organ transplantation. In August 1994 a European heart transplantation pilot study was initiated to assess the efficacy and safety of tacrolimus when administered exclusively through an oral route. METHODS: Eighty-two heart transplant recipients were randomized to treatment (2:1 ratio) with either tacrolimus- (n=54) or cyclosporine-based therapy (n=28). RESULTS: No significant differences were evident between the two treatment groups in either rejection or survival rates at 1 year. Kaplan-Meier estimates of the freedom from rejection were 26.3% and 18.5%, respectively, for the tacrolimus and cyclosporine treatment groups (p=.444). Survival rates were 79.6% and 92.9% (p=.125). At 3 of the 5 centers, patients received antithymocyte globulin during the immediate postoperative period and fared better than those who did not (with acute rejection-free rates of 49.2% and 26.7% for tacrolimus and cyclosporine, respectively [p=.080], as opposed to 7.1% and 8.3% [p=.965]; patient survival rates of 84.6% and 93.3% [p=.382] vs 75.0% and 92.3% [p=.243]). The overall rates of infection, impaired renal function (31.5% vs 21.4%), and glucose intolerance (7.0% vs 4.3%) did not differ significantly between the tacrolimus and cyclosporine treatment groups. Tacrolimus seemed to possess an advantage with regard to a reduced requirement for antihypertensive therapy (59.5% vs 87.5%, p=.025). CONCLUSIONS: Immunosuppression with oral tacrolimus provides a viable alternative to treatment with cyclosporine, particularly when administered in conjunction with antibody therapy. Further studies are warranted to optimize the administration of tacrolimus in this indication.     

Angiotensin II signal transduction pathways

It has been 100 years since the discovery of renin by Tigerstedt and Bergman. Since that time, numerous discoveries have advanced our understanding of the renin-angiotensin system, including the observation that angiotensin II is the effector molecule of this system. A remarkable aspect of angiotensin II is the many different physiological responses this simple peptide induces in different cell types. Here, we focus on the signal transduction pathways that are activated as a consequence of angiotensin II binding to the AT1 receptor. Classical signaling pathways such as the activation of heterotrimeric G proteins by the AT1 receptor are discussed. In addition, recent work examining the role of tyrosine phosphorylation in angiotensin II-mediated signal transduction is also examined. Understanding how these distinct signaling pathways transduce signals from the cell surface will advance our understanding of how such a simple molecule elicits such a wide variety of specific cellular responses.