Electrohydrodynamic-inkjet-printed high-resolution complex 3D structures with multiple functional inks are demonstrated. Printed 3D structures can have a variety of fine patterns, such as vertical or helix-shaped pillars and straight or rounded walls, with high aspect ratios (greater than ≈50) and narrow diameters (≈0.7 μm). Furthermore, the formation of freestanding, bridge-like Ag wire structures on plastic substrates suggests substantial potentials as high-precision, flexible 3D interconnects.
[1] The hot debate over the influence of global warming on tropical cyclone (TC) activity in the western North Pacific over the past several decades is partly due to the diversity of TC data sets used in recent publications. This study investigates differences of track, intensity, frequency, and the associated long-term trends for those TCs that were simultaneously recorded by the best track data sets of the Joint Typhoon Warning Center (JTWC), the Regional Specialized Meteorological Center (RSMC) Tokyo, and the Shanghai Typhoon Institute (STI). Though the differences in TC tracks among these data sets are negligibly small, the JTWC data set tends to classify TCs of category 2-3 as category 4-5, leading to an upward trend in the annual frequency of category 4-5 TCs and the annual accumulated power dissipation index, as reported by Webster et al. (2005) and Emanuel (2005). This trend and potential destructiveness over the period are found only with the JTWC data set, but downward trends are apparent in the RSMC and STI data sets. It is concluded that the different algorithms used in determining TC intensity may cause the trend discrepancies of TC activity in the western North Pacific.
The widespread distribution of smartphones, with their integrated sensors and communication capabilities, makes them an ideal platform for point-of-care (POC) diagnosis, especially in resourcelimited settings. Molecular diagnostics, however, have been difficult to implement in smartphones. We herein report a diffractionbased approach that enables molecular and cellular diagnostics. The D3 (digital diffraction diagnosis) system uses microbeads to generate unique diffraction patterns which can be acquired by smartphones and processed by a remote server. We applied the D3 platform to screen for precancerous or cancerous cells in cervical specimens and to detect human papillomavirus (HPV) DNA. The D3 assay generated readouts within 45 min and showed excellent agreement with gold-standard pathology or HPV testing, respectively. This approach could have favorable global health applications where medical access is limited or when pathology bottlenecks challenge prompt diagnostic readouts.T he rapid dissemination of electronic communication devices such as smartphones, tablets, and wearable electronics, all with integrated sensors, creates new possibilities for inexpensive point-of-care (POC) diagnostics and care delivery. One example is detecting cancer in low-and middle-income countries where limited resources and geographical constraints often lead to missed opportunities for intervention, resulting in mortalities even with treatable cancers (1). Current efforts to control cancer thus focus on implementing population-based early screening programs; a key element for success is a cost-effective, robust diagnostic platform that can be readily deployed into POC settings (2). Whereas conventional microscopy of human samples (smears, aspirates, biopsies, blood) is the most widely used to diagnose cancer, its POC adaptation is limited by inherent drawbacks such as bulky optics, requirements for trained microscopists, and operatordependent variability.Recent advances in digital sensors and computational approaches have introduced new microscopy techniques. Digital holography, in particular, has emerged as one alternative to conventional bright-field microscopy. Following the initial description of lens-free holography by Kreuzer's group (3), various diffractionbased imaging systems have been developed (4-8). The majority of recent work, however, is based on identifying targets by their inherent morphology (e.g., blood cells, bacteria, Caenorhabditis elegans) (4, 9-14). We reasoned that it would be possible to impart molecular specificity to improve disease detection and phenotyping akin to other molecular profiling strategies (15, 16).Here we describe a digital diffraction diagnostics (D3)-a computational analysis of distinct diffraction patterns generated by microbeads that bind to biological target of interest. The strategy can detect a broad range of targets (SI Appendix, Table S1): soluble proteins, nucleic acids, or cellular proteins. To provide effective POC operation at remote sites, we adopted a client-server model:...
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