Plasma removal of Parylene C

Parylene C, an emerging material in microelectromechanical systems, is of particular interest in biomedical and lab-on-a-chip applications where stable, chemically inert surfaces are desired. Practical implementation of Parylene C as a structural material requires the development of micropatterning techniques for its selective removal. Dry etching methods are currently the most suitable for batch processing of Parylene structures. A performance comparison of three different modes of Parylene C plasma etching was conducted using oxygen as the primary reactive species. Plasma, reactive ion and deep reactive ion etching techniques were explored. In addition, a new switched chemistry process with alternating cycles of fluoropolymer deposition and oxygen plasma etching was examined to produce structures with vertical sidewalls. Vertical etch rates, lateral etch rates, anisotropy and sidewall angles were characterized for each of the methods. This detailed characterization was enabled by the application of replica casting to obtain cross sections of etched structures in a non-destructive manner. Application of the developed etch recipes to the fabrication of complex Parylene C microstructures is also discussed

FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors

Face Super-Resolution (SR) is a domain-specific super-resolution problem. The specific facial prior knowledge could be leveraged for better super-resolving face images. We present a novel deep end-to-end trainable Face Super-Resolution Network (FSRNet), which makes full use of the geometry prior, i.e., facial landmark heatmaps and parsing maps, to super-resolve very low-resolution (LR) face images without well-aligned requirement. Specifically, we first construct a coarse SR network to recover a coarse high-resolution (HR) image. Then, the coarse HR image is sent to two branches: a fine SR encoder and a prior information estimation network, which extracts the image features, and estimates landmark heatmaps/parsing maps respectively. Both image features and prior information are sent to a fine SR decoder to recover the HR image. To further generate realistic faces, we propose the Face Super-Resolution Generative Adversarial Network (FSRGAN) to incorporate the adversarial loss into FSRNet. Moreover, we introduce two related tasks, face alignment and parsing, as the new evaluation metrics for face SR, which address the inconsistency of classic metrics w.r.t. visual perception. Extensive benchmark experiments show that FSRNet and FSRGAN significantly outperforms state of the arts for very LR face SR, both quantitatively and qualitatively. Code will be made available upon publication.Comment: Chen and Tai contributed equally to this pape

Risk Factors for Invasive Cryptococcus neoformans Diseases: A Case-Control Study

Background: Cryptococcus neoformans is a ubiquitous environmental fungus that can cause life-threatening meningitis and fungemia, often in the presence of acquired immunodeficiency syndrome (AIDS), liver cirrhosis, diabetes mellitus, or other medical conditions. To distinguish risk factors from comorbidities, we performed a hospital-based, density-sampled, matched case-control study. Methods: All new-onset cryptococcal meningitis cases and cryptococcemia cases at a university hospital in Taiwan from 2002–2010 were retrospectively identified from the computerized inpatient registry and were included in this study. Controls were selected from those hospitalized patients not experiencing cryptococcal meningitis or cryptococcemia. Controls and cases were matched by admission date, age, and gender. Conditional logistic regression was used to analyze the risk factors. Results: A total of 101 patients with cryptococcal meningitis (266 controls) and 47 patients with cryptococcemia (188 controls), of whom 32 patients had both cryptococcal meningitis and cryptococcemia, were included in this study. Multivariate regression analysis showed that AIDS (adjusted odds ratio [aOR] = 181.4; p < 0.001), decompensated liver cirrhosis (aOR = 8.5; p = 0.008), and cell-mediated immunity (CMI)-suppressive regimens without calcineurin inhibitors (CAs) (aOR = 15.9; p < 0.001) were independent risk factors for cryptococcal meningitis. Moreover, AIDS (aOR = 216.3, p < 0.001), decompensated liver cirrhosis (aOR = 23.8; p < 0.001), CMI-suppressive regimens without CAs (aOR = 7.3; p = 0.034), and autoimmune diseases (aOR = 9.3; p = 0.038) were independent risk factors for developing cryptococcemia. On the other hand, diabetes mellitus and other medical conditions were not found to be risk factors for cryptococcal meningitis or cryptococcemia. Conclusions: The findings confirm AIDS, decompensated liver cirrhosis, CMI-suppressive regimens without CAs, and autoimmune diseases are risk factors for invasive C. neoformans diseases