Resistivity profiles

A.irbome Basic Chemical Contamination. A critical, and at-first pu22ling problem, was encountered during early manufacturing trials of CA resists. Sporadically, severely distorted resist profiles would be formed in positive-tone CA resists, displaying what seemed to be a cap on the upper surface of the resist image (Fig. 26). In severe cases this cap or T-top would appear as a kin or cmst over the entire wafer surface that prevented development of the pattern. The magnitude of the effect varied dramatically between laboratories and appeared to grow more severe as the time interval between exposure and post-exposure bake was increased. 

Texture in antagonism where aliosterically modified receptors may have different conformations from each other may lead to differences in resistance profiles with chronic treatment. 

Shimura K, Kodama E, Sakagami Y, Matsuzaki Y, Watanabe W, Yamataka K, Watanabe Y, Ohata Y, Doi S, Sato M, Kano M, Ikeda S, Matsuoka M (2008) Broad antiretroviral activity and resistance profile of the novel human immunodeficiency virus integrase inhibitor elvitegravir (JTK-303/GS-9137). J Virol 82 764-774... 

Another nucleoside analogue belonging to the same class as lamivudine is tel-bivudine. Clinical resistance to telbivudine has to be studied in more detail, but the first in vivo data and several in vitro results suggest that tebivudine s resistance profile is quite similar to that of lamivudine (Lok et al. 2007). 

These examples illustrate the power of proper ANN feature space optimization. In all the examples discussed, the limits of the type of information that could be gleaned from the Salmonella PyMAB spectra were probed. The PD-ANN s automated optimization removed the issue of methodological uncertainty and enabled a focus on questions of Py-MAB-MS spectral information content and its potential use for rapid strain ID. Question Does Py-MAB-MS data support Serovar classification Answer Yes. How about PFGE classification Yes. How about antibiotic resistance profile Answer Perhaps, if one first eliminates stronger contributions to spectral variation and then, by design and grouping, limits the possibilities to only a few classes. 

Lee K, Klein-Szanto AJ, Kruh GD. Analysis of the MRP4 drug resistance profile in transfected NIH3T3 cells. J Natl Cancer Inst 2000 92(23) 1934-1940. 

The field is now poised to move into a new phase that will address opportunities for improvement on the profiles of RAL and EVG. These "next generation" drugs will need to deliver notable advantages in resistance profile along with having a high genetic barrier to resistance [51,52]. 

In general, most converters are tested on the bench with the electronic load set to constant current (CC mode). True, that s not benign, nor as malignant as it gets. But the implied expectation is that converters should at least work in CC mode. They should, in particular, have no startup issues with this type of load profile. But even that may not be the end of the story Some loads can also vary with time. For example, an incandescent bulb has a resistive profile, but its cold resistance is much lower than its hot resistance. That s why most bulbs fail towards the end of their natural lifetime just when you throw the wall switch to its ON position. And if the converter is powering a system board characterized by sudden variations in its instantaneous supply current demand, that can cause severe problems to the converter, too. The best known example of this is an AC-DC power supply inside a computer. The 12V rail goes to the hard disk, which can suddenly demand very high currents as it spins up, and then lapse back equally suddenly into a lower current mode. 

Principal component analysis (PCA) of the soil physico-chemical or the antibiotic resistance data set was performed with the SPSS software. Before PCA, the row MPN values were log-ratio transformed (ter Braak and Smilauer 1998) each MPN was logio -transformed, then, divided by sum of the 16 log-transformed values. Simple linear regression analysis between scores on PCs based on the antibiotic resistance profiles and the soil physico-chemical characteristics was also performed using the SPSS software. To find the PCs that significantly explain variation of SFI or SEF value, multiple regression analysis between SFI or SEF values and PC scores was also performed using the SPSS software. The stepwise method at the default criteria (p=0.05 for inclusion and 0.10 for removal) was chosen. 

Antibiotic resistance profiles of the bacterial communities reflected the effects of deforestation and the land degradation (Fig. 2). The degradation was significant (p=0.05) as a source of variation for the numbers of soil bacterial cells resistant to lasalocid, penicillin, spectinomycin and trimethoprim, and marginally significant (0.50 Significant differences between two average values were observed for some antibiotics. When compared with the BG soil bacterial community, the DEF soil bacterial community had more bacterial cells resistant to dapson, kanamycin, lasalocid, nafcillin, penicillin, spectinomycin, streptomycin and trimethoprim. 

PCA of the Antibiotic Resistance Profiles to Find PCs that Explain the Land Degradation... 

Multiple regression analysis between the SFI or the SEF values and the PC scores gave the following formulae that describe the land degradation gradient based on the antibiotic resistance profiles. 

Significant Soil Environmental Factors Related to the Changes in Antibiotic Resistance Profile... 

Changes in Antibiotic Resistance Profile of Soil Bacterial Community 331... 

Fig. 3. Principal component score plots based on the antibiotic resistance profiles. The diamond ( ), the open square (o) and the triangle (A) indicate BG, DDF and DEF, respectively. The value in the parenthesis indicates the percentage of the variability explained by the principal component.

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