3D printing of a graphene aerogel with true 3D overhang structures is highlighted. The aerogel is fabricated by combining drop-on-demand 3D printing and freeze casting. The water-based GO ink is ejected and freeze-cast into designed 3D structures. The lightweight (<10 mg cm(-3) ) 3D printed graphene aerogel presents superelastic and high electrical conduction.

importance to unravel the complexity of these systems and to impact a multitude of technological applications ranging from integrated photonic devices to precise medicine. [1-3] Thermocouples and thermistors dominate the market but are inappropriate to probe temperature in live biological systems as physical contact with measured samples is a prerequisite, which disturbs the measurements at sub-millimeter scales. [4] Alternatively, luminescence nanothermometry is emerging as a noninvasive spectroscopic method that allow to probe temperature variation at nanometric spatial resolution and in remote distance, spurring wide interests. [5,6] The contactless and high-resolution nature makes them ideal candidates for temperature evaluation in the early diagnosis of several diseases as well as for providing real-time temperature feedback in thermal (hypothermia or hyperthermia) therapies of malignant cancers. [7-9] Indeed, the potential clinical and preclinical applications fuel a fast development of luminescence nanothermometers particularly for in vivo studies in the nearinfrared (NIR) range. [10] Light in the first biological window (NIR-I, 750-950 nm) or the second biological window (NIR-II, 1000-1700 nm) is known to have minimized scattering and absorption, thus allowing for maximized light Luminescence nanothermometry is promising for noninvasive probing of temperature in biological microenvironment at nanometric spatial resolution. Yet, wavelength-and temperature-dependent absorption and scattering of tissues distort measured spectral profile, rendering conventional luminescence nanothermometers (ratiometric, intensity, band shape, or spectral shift) problematic for in vivo temperature determination. Here, a class of lanthanide-based nanothermometers, which are able to provide precise and reliable temperature readouts at varied tissue depths through NIR-II luminescence lifetime, are described. To achieve this, an inert core/ active shell/inert shell structure of tiny nanoparticles (size, 13.5 nm) is devised, in which thermosensitive lanthanide pairs (ytterbium and neodymium) are spatially confined in the thin middle shell (sodium yttrium fluoride, 1 nm), ensuring being homogenously close to the surrounding environment while protected by the outmost calcium fluoride shell (CaF 2 , ≈2.5 nm) that shields out bioactive milieu interferences. This ternary structure enables the nanothermometers to consistently resolve temperature changes at depths of up to 4 mm in biological tissues, having a high relative temperature sensitivity of 1.4-1.1% °C −1 in the physiological temperature range of 10-64 °C. These lifetime-based thermosensitive nanoprobes allow for in vivo diagnosis of murine inflammation, mapping out the precise temperature distribution profile of nanoprobes-interrogated area.

Bayesian inference provides a powerful approach to system identification and damage assessment for structures. The application of Bayesian method is motivated by the fact that inverse problems in structural engineering, including structural health monitoring, are typically ill-conditioned and ill-posed when using noisy incomplete data because of various sources of modeling uncertainties. One should not just search for a single ''optimal'' value for the vector of model parameters but rather attempt to describe the whole family of plausible model parameters based on measured data using a Bayesian probabilistic framework. In this article, the fundamental principles of Bayesian analysis and computation are summarized; then a review is given of recent state-of-the-art practices of Bayesian inference in system identification and damage assessment for civil infrastructure. Discussions of the benefits and deficiencies of these approaches, as well as potentially useful avenues for future studies, are also provided. Our focus is on meeting challenges that arise from system identification and damage assessment for the civil infrastructure but our presented theories also have a considerably broader applicability for inverse problems in science and technology.

High‐resolution Atmosphere General Circulation Models (AGCMs) are capable of directly simulating realistic tropical cyclone (TC) statistics, providing a promising approach for TC‐climate studies. Active air‐sea coupling in a coupled model framework is essential to capturing TC‐ocean interactions, which can influence TC‐climate connections on interannual to decadal time scales. Here we investigate how the choices of ocean coupling can affect the directly simulated TCs using high‐resolution configurations of the Community Earth System Model (CESM). We performed a suite of high‐resolution, multidecadal, global‐scale CESM simulations in which the atmosphere (∼0.25° grid spacing) is configured with three different levels of ocean coupling: prescribed climatological sea surface temperature (SST) (ATM), mixed layer ocean (SLAB), and dynamic ocean (CPL). We find that different levels of ocean coupling can influence simulated TC frequency, geographical distributions, and storm intensity. ATM simulates more storms and higher overall storm intensity than the coupled simulations. It also simulates higher TC track density over the eastern Pacific and the North Atlantic, while TC tracks are relatively sparse within CPL and SLAB for these regions. Storm intensification and the maximum wind speed are sensitive to the representations of local surface flux feedbacks in different coupling configurations. Key differences in storm number and distribution can be attributed to variations in the modeled large‐scale climate mean state and variability that arise from the combined effect of intrinsic model biases and air‐sea interactions. Results help to improve our understanding about the representation of TCs in high‐resolution coupled Earth system models, with important implications for TC‐climate applications.

We propose and demonstrate a dynamic Brillouin optical fiber sensing based on the multi-slope assisted fast Brillouin optical time-domain analysis (F-BOTDA), which enables the measurement of a large strain with real-time data processing. The multi-slope assisted F-BOTDA is realized based on the double-slope demodulation and frequency-agile modulation, which significantly increases the measurement range compared with the single- or double- slope assisted F-BOTDA, while maintaining the advantage of fast data processing and being suitable for real-time on-line monitoring. A maximum strain variation up to 5000με is measured in a 32-m fiber with a spatial resolution of ~1m and a sampling rate of 1kHz. The frequency of the strain is 12.8Hz, which is limited by the rotation rate of the motor used to load the force on the fiber. Furthermore, the influence of the frequency difference between two adjacent probe tones on the measurement error is studied theoretically and experimentally for optimization. For a Brillouin gain spectrum with a 78-MHz width, the optimum frequency difference is ~40MHz. The measurement error of Brillouin frequency shift is less than 3MHz over the whole measurement range (241MHz).

A lanthanide-based theranostic agent for image-guided photothermal therapy.

No abstract

To elucidate the effect of rice protein (RP) on the depression of inflammation, growing and adult rats were fed with caseins and RP for 2 weeks. Compared with casein, RP reduced hepatic accumulations of reactive oxygen species (ROS) and nitro oxide (NO), and plasma activities of alanine transaminase (ALT) and aspartate transaminase (AST) in growing and adult rats. Intake of RP led to increased mRNA levels, and protein expressions of phosphoinositide 3 kinase (PI3K), protein kinase B (Akt), nuclear factor-κB 1 (NF-αB1), reticuloendotheliosis viral oncogene homolog A (RelA), tumor necrotic factor α (TNF-α), interleukin-1β (IL-1β), interleukin-6 (IL-6), inducible nitric oxide synthase (iNOS), cyclooxygenase-2 (COX-2), and monocyte chemoattractant protein-1 (MCP-1) were decreased, whereas hepatic expressions of interleukin-10 (IL-10) and heme oxygenase 1 (HO-1) were increased by RP. The activation of NF-κB was suppressed by RP through upregulation of inhibitory κB α (IκBα), resulting in decreased translocation of nuclear factor-κB 1 (p50) and RelA (p65) to the nucleus in RP groups. The present study demonstrates that RP exerts an anti-inflammatory effect to inhibit ROS-derived inflammation through suppression of the NF-κB pathway in growing and adult rats. Results suggest that the anti-inflammatory capacity of RP is independent of age.