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The rational Krylov subspace methods can improve the computational speed compared to conventional time-stepping approaches for calculating 3-D transient electromagnetic (TEM) method forward modeling. However, the rational Krylov subspace method simulates only the step-off response. Because primary source waveforms have nonnegligible effects on the induced responses, it is crucial to model the response induced by any given source waveform. The electric field (e) and the time derivative of the magnetic induction ( $\mathrm {d} {\mathbf { b}} / \mathrm {d}t$ ) are commonly measured TEM responses. Case studies also show the magnetic induction ( $\bf b$ ) response measured by magnetometers has a good resolution for exploring conductive mineral deposits. Therefore, modern TEM forward modeling algorithms should be able to simulate different types of responses. We present a new algorithm for TEM modeling using the rational Krylov subspace method. The following improvements are implemented in our approach: 1) the algorithm can efficiently compute the e and $\mathrm {d} {\mathbf { b}} / \mathrm {d}t$ responses, and especially the $\bf b$ response, which was less considered in other 3-D TEM studies; 2) a convolution approach is employed that allows the Krylov subspace method to simulate the source waveform effects on all three types of responses; and 3) we present the approach for computing the initial condition of b in cases of using galvanic sources. This work extends the flexibility of existing 3-D TEM modeling algorithms. Numerical examples demonstrate that the new algorithm is accurate and computationally efficient.

For compensating the primary field coupling from the transmitting coil and the sensing coil, the bucking coil is often used to achieve pure secondary field for the helicopter transient electromagnetic (HTEM) system. Traditionally, the distributed capacitance of the bucking coil and the transmitting coil is ignored and pay few attentions to study it. In fact, it has very important influence on the turn-off current of the transmitter and the transient electromagnetic (TEM) field of the system. In this article, a novel distributed capacitance model of the HTEM coils is theoretically established at the first time, its effects on the turn-off current and the TEM field are analyzed in detail. It finds that the turn-off current in the transmitting coil and the bucking coil are not equal caused by the distributed capacitance although they are connected in series. The field experiments are completed and proved that the measured TEM fields agree very well with the simulated results based on the distributed capacitance model. This is very helpful to optimize the early-time TEM field and promote the shallow TEM data interpretation capability for the HTEM surveying.

DNA as an exceptional data storage medium offers high information density. However, DNA storage requires specialized equipment and tightly controlled environments for storage. Fast encapsulation within minutes for enhanced DNA stability to do away with specialized equipment and fast DNA extraction remain a challenge. Here, we report a DNA microlibrary that can be encapsulated by metal–organic frameworks (MOFs) within 10 min and extracted (5 min) in a single microfluidic chip for automated and integrated DNA-based data storage. The DNA microlibrary@MOFs enhances the stability of data-encoded DNA against harsh environments. The encoded information can be read out perfectly after accelerated aging, equivalent to being readable after 10 years of storage at 25 °C, 50% relative humidity, and 10 000 lx sunlight radiation. Moreover, the library enables fast retrieval of target data via flow cytometry and can be reproduced after each access.

The transient electromagnetic (TEM) method utilizes artificial transmitters and measures electromagnetic (EM) responses to reveal the resistivity information of the subsurface. The current waveform of transmitters has nonnegligible effects on induced fields. Therefore, 3-D TEM forward modeling algorithms need the capability of simulating arbitrary waveforms to obtain accurate responses. In time-stepping-based 3-D TEM forward modeling, the source term (ST) approach is frequently used, which employs the source current density to model the waveform variation during time-stepping. The ST approach, however, requires fine-time discretization to describe complex waveforms, which could significantly raise the computational cost. We present a robust convolution (Conv) approach that computes the convolution between the time derivative of the waveform and the step-off response to incorporate the waveform effects in 3-D TEM modeling. The Conv approach does not discretize the waveform using time steps. Hence, it is advantageous when modeling full-waveform cases. The developed algorithm is based on the finite-element (FE) method using unstructured grids and the implicit backward Euler approach. Both galvanic and inductive transmitters are incorporated. Ground and airborne TEM surveys are tested using an actual airborne TEM waveform, a full waveform of the $2^{(n)}$ -sequence pseudorandom signal, and various synthetic waveforms. Accuracy is validated against the 1-D and 3-D solutions of published studies. The ST and Conv approaches are compared. Synthetic examples show that the latter approach simplifies the waveform incorporation in TEM modeling and substantially improves time-stepping efficiency without sacrificing accuracy.

This study presents an autoencoder-embedded optimization (AEO) algorithm which involves a bi-population cooperative strategy for medium-scale expensive problems (MEPs). A huge search space can be compressed to an informative low-dimensional space by using an autoencoder as a dimension reduction tool. The search operation conducted in this low space facilitates the population with fast convergence towards the optima. To strike the balance between exploration and exploitation during optimization, two phases of a tailored teaching-learning-based optimization (TTLBO) are adopted to coevolve solutions in a distributed fashion, wherein one is assisted by an autoencoder and the other undergoes a regular evolutionary process. Also, a dynamic size adjustment scheme according to problem dimension and evolutionary progress is proposed to promote information exchange between these two phases and accelerate evolutionary convergence speed. The proposed algorithm is validated by testing benchmark functions with dimensions varying from 50 to 200. As indicated in our experiments, TTLBO is suitable for dealing with medium-scale problems and thus incorporated into the AEO framework as a base optimizer. Compared with the state-of-the-art algorithms for MEPs, AEO shows extraordinarily high efficiency for these challenging problems, thus opening new directions for various evolutionary algorithms under AEO to tackle MEPs and greatly advancing the field of medium-scale computationally expensive optimization.

Chronic wounds are one of the most serious complications of diabetes mellitus. Even though utilizing nitric oxide (NO) as a gas medicine to repair diabetic wounds presents a promising strategy, controlling the NO release behavior in the affected area, which is vital for NO-based therapy, still remains a significant challenge. In this work, a copper-based metal–organic framework, namely, HKUST-1, has been introduced as a NO-loading vehicle, and a NO sustained release system with the core–shell structure has been designed through the electrospinning method. The results show that the NO is quantificationally and stably loaded in the HKUST-1 particles, and the NO-loaded HKUST-1 particles are well incorporated into the core layer of the coaxial nanofiber. Therefore, NO can be controllably released with an average release rate of 1.74 nmol L–1h–1for more than 14 days. Moreover, the additional copper ions released from the degradable HKUST-1 play a synergistic role with NO to promote endothelial cell growth and significantly improve the angiogenesis, collagen deposition as well as anti-inflammatory property in the wound bed, which eventually accelerate the diabetic wound healing. These results suggest that such a copper-based metal–organic framework material as a controllable NO-releasing vehicle is a highly efficient therapy for diabetic wounds.

The synthesized perovskites are randomly distributed and their optical properties are fixed after synthesis. Here we demonstrate the tailoring of lasing properties of perovskite microwire via micromanipulation. One microwire has been lifted by a tungsten probe and repositioned on a nearby perovskite microplate with one end suspended in air. Consequently, the conventional Fabry–Perot lasers are completely suppressed and a single laser peak has been observed. The numerical calculations reveal that the single-mode laser is formed by the whispering-gallery mode in the transverse plane of microwire. Our research provides a simple way to tailor the properties of microwire postsynthesis.