A lithography technique that combines laser interference lithography (LIL) and photolithography, which can be a valuable technique for the low cost production of microscale and nanoscale hybrid mask molds, is proposed. LIL is a maskless process which allows the production of periodic nanoscale structures quickly, uniformly, and over large areas. A 257 nm wavelength Ar-Ion laser is utilized for the LIL process incorporating a Lloyd's mirror one beam inteferometer. By combining LIL with photolithography, the non-selective patterning limitation of LIL are explored and the design and development of a hybrid mask mold for nanoimprint lithography process, with uniform two-dimensional nanoscale patterns are presented. Polydimethylsiloxane is applied on the mold to fabricate a replica of the stamp. Through nanoimprint lithography using the manufactured replica, successful transfer of the patterns is achieved, and selective nanoscale patterning is confirmed with pattern sizes of around 180 nm and pattern aspect ratio of around 1.44:1.
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http://dx.doi.org/10.1166/jnn.2011.4363 | DOI Listing |
J Voice
December 2024
Professor in the Speech, Language and Hearing Sciences Department of the Federal University of Sergipe - Lagarto Campus, Lagarto, Brazil. Electronic address:
Objective: To compare the vocal symptomatology of professors from a federal university who engaged in distance, hybrid, and face-to-face teaching during and after the Coronavirus Disease 2019 (COVID-19) pandemic period.
Method: The study included 40 university professors, 20 men and 20 women, whose symptomatology was monitored at three time points: during the distance teaching period due to social isolation caused by COVID-19, in hybrid teaching (partial return), and upon returning to face-to-face teaching, which required the use of face masks and posed contamination risks.
Results: The hybrid phase presented the highest absence of vocal complaints/discomfort, and most participants did not need to be reassigned due to vocal problems.
IEEE Open J Eng Med Biol
November 2024
Biomedical Information Processing LabÉcole de Technologie Supérieure, University of Québec Montréal H3C 1K3 Canada.
Remote patient monitoring has emerged as a prominent non-invasive method, using digital technologies and computer vision (CV) to replace traditional invasive monitoring. While neonatal and pediatric departments embrace this approach, Pediatric Intensive Care Units (PICUs) face the challenge of occlusions hindering accurate image analysis and interpretation. In this study, we propose a hybrid approach to effectively segment common occlusions encountered in remote monitoring applications within PICUs.
View Article and Find Full Text PDFBiomed Opt Express
December 2024
Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China (UESTC), Huzhou 313001, China.
The problems of complex background, low quality of finger vein images, and poor discriminative features have been the bottleneck of feature extraction and finger vein recognition. To this end, we propose a feature extraction algorithm based on the open-set testing protocol. In order to eliminate the interference of irrelevant areas, this paper proposes the idea of segmentation-assisted classification, that is, using the rough mask of the finger vein to constrain the feature learning process so that the network can focus on the vein area and learn greater weight for the vein.
View Article and Find Full Text PDFIndian J Anaesth
November 2024
Anaesthesiology, Apollo Hospital, Bengaluru, Karnataka, India.
Background And Aims: The conventional CE clamp technique may not effectively provide bag-mask ventilation (BMV) in the hands of inexperienced providers. Hence, we compared the efficacy of two-handed CE versus a hybrid technique.
Methods: One hundred thirty-two American Society of Anesthesiologists (ASA) I-II adult patients were randomised into groups A and B.
Comput Biol Med
December 2024
Department of Technical Education Uttar Pradesh, India.
Health care images contain a variety of imaging information that has specific features, which can make it challenging to assess and decide on the methods necessitated to safeguard the highly classified visuals from unauthorized exposure during transmission in a communication channel. As a result, this proposed approach utilizes a variety of techniques that will enhance the quality of textual healthcare images, communicate information securely, and interpret textual data from healthcare visuals without difficulty. Natural interference, primarily on the receiver side, reduces text-based healthcare image contrast, and numerous artifacts and adjacent picture element values impede diagnosis.
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