Search for: All records

Accurately measuring the viscoelastic properties of biomaterials is critical for understanding their functions in biological systems and optimizing their development for specific applications. Conventional methods often require direct physical contact, which hinders longitudinal studies of sterile samples and impose strict requirements in sample preparation. Here, we introduce tensile acoustic rheometry (TAR), a technique for rapid, contactless characterization of soft viscoelastic biomaterials. TAR uses a dual-mode ultrasound approach to apply an upward force impulse, generating oscillatory tensile and compressive motion in a small, free-standing sample (~30 mm3) with its bottom immobilized on a pre-wetted flat surface by capillary stiction. High frequency ultrasound pulse echo detection is employed to track this motion via the movement of the top surface of the sample in real time. In this study, we developed a theoretical framework of the tensile-compression motion of the sample from which Young’s modulus and viscosity of the sample are determined based on the TAR measurements. TAR was validated across a variety of samples, including engineered hydrogels and commercially available natural food products. Results from TAR measurements aligned closely with theoretical predictions, reported values, and shear wave elastography measurements. These findings underscore the versatility and flexibility of TAR as a robust, versatile rheological method for biomaterial characterization with minimal sample preparation requirements. 

This paper investigates basic trade-offs between energy and delay in wireless communication systems using finite blocklength theory. We first assume that data arrive in constant stream of bits, which are put into packets and transmitted over a communications link. Our results show that depending on exactly how energy is measured, in general energy depends on sqrt{d^{-1}} or sqrt{d^{-1}log d}, where d is the delay. This means that the energy decreases quite slowly with increasing delay. Furthermore, to approach the absolute minimum of -1.59 dB on energy, bandwidth has to increase very rapidly, much more than what is predicted by infinite blocklength theory. We then consider the scenario when data arrive stochastically in packets and can be queued. We devise a scheduling algorithm based on finite blocklength theory and develop bounds for the energy-delay performance. Our results again show that the energy decreases quite slowly with increasing delay. 

Abstract. Subseasonal-to-seasonal (S2S) prediction, especially the prediction of extreme hydroclimate events such as droughts and floods, is not only scientifically challenging, but also has substantial societal impacts. Motivated by preliminary studies, the Global Energy and Water Exchanges(GEWEX)/Global Atmospheric System Study (GASS) has launched a new initiativecalled “Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction” (LS4P) as the first international grass-roots effort to introduce spring land surface temperature(LST)/subsurface temperature (SUBT) anomalies over high mountain areas as acrucial factor that can lead to significant improvement in precipitationprediction through the remote effects of land–atmosphere interactions. LS4P focuses on process understanding and predictability, and hence it is differentfrom, and complements, other international projects that focus on theoperational S2S prediction. More than 40 groups worldwide have participated in this effort, including 21 Earth system models, 9 regionalclimate models, and 7 data groups. This paper provides an overview of the history and objectives of LS4P, provides the first-phase experimental protocol (LS4P-I) which focuses on the remote effect ofthe Tibetan Plateau, discusses the LST/SUBT initialization, and presents thepreliminary results. Multi-model ensemble experiments and analyses ofobservational data have revealed that the hydroclimatic effect of the springLST on the Tibetan Plateau is not limited to the Yangtze River basin but may have a significant large-scale impact on summer precipitation beyond EastAsia and its S2S prediction. Preliminary studies and analysis have alsoshown that LS4P models are unable to preserve the initialized LST anomaliesin producing the observed anomalies largely for two main reasons: (i) inadequacies in the land models arising from total soil depths which are tooshallow and the use of simplified parameterizations, which both tend to limit the soil memory; (ii) reanalysis data, which are used for initial conditions, have large discrepancies from the observed mean state andanomalies of LST over the Tibetan Plateau. Innovative approaches have beendeveloped to largely overcome these problems.