More Like this

1. OpenSTED: Inexpensive and open-source implementation of Dynamic Intensity Minimum (DyMIN) for Stimulated Emission Depletion (STED) microscopy

   https://doi.org/10.1364/NTM.2021.NW4C.3  

   Meyer, Stephanie A.; Siemens, Mark E.; Gopinath, Juliet T.; Restrepo, Diego; Gibson, Emily A. (January 2021, Biophotonics Congress 2021)

   The DyMIN method reduces photobleaching, a problem in STED microscopy. Labs implementing custom-built STED microscopes would greatly benefit from DyMIN capabilities. We present an inexpensive, open-source version utilizing an FPGA and multiplexer. 

   more » « less
2. OpenSTED: Inexpensive and open-source implementation of Dynamic Intensity Minimum (DyMIN) for Stimulated Emission Depletion (STED) microscopy

   Meyer, S (July 2021, Biophotonics Congress 2021)

   null (Ed.)

   The DyMIN method reduces photobleaching, a problem in STED microscopy. Labs implementing custom-built STED microscopes would greatly benefit from DyMIN capabilities. We present an inexpensive, open-source version utilizing an FPGA and multiplexer. 

   more » « less
3. Spatial resolution enhancement in photon-starved STED imaging using deep learning-based fluorescence lifetime analysis

   https://doi.org/10.1039/d3nr00305a  

   Chen, Yuan-I; Chang, Yin-Jui; Sun, Yuansheng; Liao, Shih-Chu; Santacruz, Samantha R.; Yeh, Hsin-Chih (June 2023, Nanoscale)

   In this work, a deep learning-based method, STED-flimGANE, is introduced to achieve enhanced STED imaging resolution under a low STED-beam power and photon-starved conditions. 

   more » « less
4. Two-photon Fiber STED Microscope Using Polarization Maintaining Fiber

   https://doi.org/10.1364/CLEO_SI.2021.SW2D.2  

   Heffernan, Brendan M.; Riley, Peter; Supekar, Omkar D.; Meyer, Stephanie A.; George, Nicholas M.; Restrepo, Diego; Siemens, Mark E.; Gibson, Emily A.; Gopinath, Juliet T. (April 2021, Conference on Lasers and Electro-Optics)

   null (Ed.)

   We demonstrate a two photon (2P) fiber STED microscope in which the excitation and STED light are delivered to the sample in polarization maintaining (PM) fiber. 

   more » « less
5. Spatio-Temporal Expanding Distance Asymptotic Framework for Locally Stationary Processes

   https://doi.org/10.1007/s13171-020-00213-4  

   Chu, Tingjin; Liu, Jialuo; Zhu, Jun; Wang, Haonan (January 2020, Sankhya A)

   Spatio-temporal data indexed by sampling locations and sampling time points are encountered in many scientific disciplines such as climatology, environ- mental sciences, and public health. Here, we propose a novel spatio-temporal expanding distance (STED) asymptotic framework for studying the proper- ties of statistical inference for nonstationary spatio-temporal models. In particular, to model spatio-temporal dependence, we develop a new class of locally stationary spatio-temporal covariance functions. The STED asymp- totic framework has a fixed spatio-temporal domain for spatio-temporal pro- cesses that are globally nonstationary in a rescaled fixed domain and locally stationary in a distance expanding domain. The utility of STED is illus- trated by establishing the asymptotic properties of the maximum likelihood estimation for a general class of spatio-temporal covariance functions. A simulation study suggests sound finite-sample properties and the method is applied to a sea-surface temperature dataset. 

   more » « less